Development ofmicrostructure-based tools for alloy

and rolling process design

(Microtools)

doi:10.2777/4415

Developm

ent of microstructure-based tools for alloy and rolling process design (M

icrotools)EU

EUR 26212

KI-NA-26212-EN

-N

Project Microtools developed tools to construct processing regime maps combining temperature-time-deformation history with enhanced knowledge of the metallurgical mechanisms during hot rolling, to design improved rolling schedules and chemistries. The dependence of the austenite recrystallisation and precipitation kinetics on the elements Mn, Si, Al and Nb at levels relevant to plate and advanced high strength strip steels was studied using thermomechanical testing and detailed metallography and integrated into equations for use in hot rolling models. The softening retardation potential of the alloying elements investigated was found to decrease in the order Nb>>Al>Si. A new methodology for quantifying the recrystallised austenite fraction using EBSD maps and austenite grain reconstruction software was developed. Processing regime maps were constructed for representative plate and hot rolled strip rolling schedules from which pilot rolling trials were designed and performed to successfully validate the new models.

Studies and reports

Research and Innovation EUR 26212 EN

EUROPEAN COMMISSION Directorate-General for Research and Innovation Directorate G — Industrial Technologies Unit G.5 — Research Fund for Coal and Steel

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European Commission

Research Fund for Coal and SteelDevelopment of microstructure-based tools

for alloy and rolling process design(Microtools)

S. V. Parker, R. C. Beaverstock, Z. Husain, G. ClaxtonTata Steel UK Limited

Swinden Technology Centre, Moorgate, Rotherham, S60 3AR, UNITED KINGDOM

S. Cobo, L. Lutz, S. JolyArcelorMittal Maizières Research SA

Voie Romaine, BP30320, 52783 Maizières les Metz Cedex, FRANCE

Z. Aretxabaleta, B. Pereda, B. LópezCentro de Estudios e Investigaciones Técnicas de Guipuzcoa (CEIT)

Materials Department, PO Box 1555, 20018 San Sebastián, SPAIN

B. Pohu, G. LannooCentre de Recherches Métallurgiques (CRM)

Technologiepark 903c, 9052 Zwijnaarde (Gent), BELGIUM

Grant Agreement RFSR-CT-2009-00011 1 July 2009 to 31 December 2012

Final report

Directorate-General for Research and Innovation

2013 EUR 26212 EN

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CONTENTS

1. FINAL SUMMARY ........................................................................................................................................5

1.1 OBJECTIVES ...............................................................................................................................................5 1.2 MAIN RESULTS...........................................................................................................................................5 1.3 CONCLUSIONS..........................................................................................................................................14 1.4 APPLICATIONS .........................................................................................................................................15

2. SCIENTIFIC AND TECHNICAL DESCRIPTION OF THE RESULTS ................................................16

2.1 OBJECTIVES OF THE PROJECT...................................................................................................................16 2.2 COMPARISON OF INITIALLY PLANNED ACTIVITIES AND WORK ACCOMPLISHED .........................................16 2.3 DESCRIPTION OF ACTIVITIES AND DISCUSSION .........................................................................................18 2.3.1 WP1: PROJECT COORDINATION ...............................................................................................................19 2.3.2 WP2: PROVISION OF MATERIALS.............................................................................................................19

2.3.2.1 Task 2.1: Production of laboratory casts.......................................................................................20 2.3.2.2 Task 2.2: Laboratory rolling..........................................................................................................21 2.3.2.3 Task 2.3: Provision of industrial material .....................................................................................21

2.3.3 WP3: THERMOMECHANICAL TESTING .....................................................................................................21 2.3.3.1 Task 3.1: Definition of test programme .........................................................................................22 2.3.3.2 Task 3.2: Solute drag effect on static recrystallisation kinetics.....................................................30 2.3.3.3 Task 3.2: Round robin exercise......................................................................................................53 2.3.3.4 Task 3.3: Solute drag effect on dynamic recrystallisation kinetics ................................................59 2.3.3.5 Task 3.4: Grain growth kinetics.....................................................................................................63 2.3.3.6 Task 3.5: Strain induced precipitation effects................................................................................64 2.3.3.7 Task 3.6: Determination of critical temperatures for recrystallisation .........................................67

2.3.4 WP4: MICROSTRUCTURE ANALYSIS ........................................................................................................75 2.3.4.1 Task 4.1: Quantification of recrystallised fraction ........................................................................76 2.3.4.2 Task 4.2: Quantification of austenite grain structure and distribution .........................................86 2.3.4.3 Task 4.3: Quantification of precipitates.......................................................................................106

2.3.5 WP 5: MODELLING AND CONSTRUCTION OF PROCESSING MAPS .............................................................116 2.3.5.1 Task 5.1: Assessment of current model capabilities.....................................................................116 2.3.5.2 Task 5.2: Modelling of static recrystallisation kinetics ...............................................................120 2.3.5.3 Task 5.3: Modelling of dynamic recrystallisation kinetics...........................................................147 2.3.5.4 Task 5.4: Modelling of austenite grain size .................................................................................149 2.3.5.5 Task 5.5: Modelling of recrystallisation-precipitation interactions ............................................158 2.3.5.6 Task 5.6: Construction of processing regime maps .....................................................................162

2.3.6 WP6: APPLICATION AND VALIDATION ...................................................................................................169 2.3.6.1 Task 6.1: Design of validation tests .............................................................................................169 2.3.6.2 Task 6.2: Single and double hit validation tests ..........................................................................175 2.3.6.3 Task 6.3: Multipass validation tests.............................................................................................175 2.3.6.4 Task 6.4: Pilot rolling trials.........................................................................................................186 2.3.6.5 Task 6.5: Validation against pilot mill and industrial mill data ..................................................190

2.4 CONCLUSIONS........................................................................................................................................193 2.5 EXPLOITATION AND IMPACT OF THE RESEARCH RESULTS .......................................................................200

2.5.1 Application of the project results .....................................................................................................200 2.5.2 List of publications and conference presentations ...........................................................................200

3. LIST OF FIGURES.....................................................................................................................................201

4. LIST OF TABLES.......................................................................................................................................207

5. LIST OF REFERENCES............................................................................................................................209

6. LIST OF ACRONYMS AND ABBREVIATIONS ...................................................................................211

3

MICROTOOLS: Development of Microstructure-Based Tools for Alloy and Rolling Process

Design for Hot Rolled Steels

1. Final Summary

1.1 Objectives

Project MICROTOOLS aimed to develop tools to construct processing regime maps combining

temperature-time-deformation history with enhanced knowledge of the operational metallurgical

mechanisms during hot rolling. These tools will help design improved and new rolling schedules and

steel chemistries, to exploit the increased metallurgical understanding of the underlying mechanisms

without compromising mill productivity. The compositional dependence of the austenite microstructure

evolution (recrystallisation and precipitation kinetics) for major alloying elements (Mn, Si, Al, Nb) was

studied using thermomechanical testing and high resolution characterisation techniques, and integrated

into hot rolling models. Application to strip and plate steel production was demonstrated.

The main objectives of the project were as follows:

1. Investigation of the effects of the alloy elements Mn, Si, and Nb on the recrystallisation

behaviour of austenite in hot rolled steels by thermomechanical testing, both individually and

in combination, extending the range to levels relevant to modern high strength steels.

2. Assessment for the first time of the effects of Al additions on the static recrystallisation

kinetics via both solute drag and possible interactions with Nb precipitation kinetics.

3. Improvement of the recrystallisation equations for the effect of low strain deformations (<0.2)

4. Development of enhanced predictive equations/models for the recovery, recrystallisation and

precipitation kinetics, austenite grain size and recrystallisation critical temperatures.

5. Development of a tool for modelling austenite grain size distributions.

6. Development of more physically based models for investigation of specific mechanisms, such

as strain induced precipitation.

7. Construction of processing regime maps which combine temperature-time-deformation history

with enhanced knowledge of the operational metallurgical mechanisms.

8. Application of these maps to help design improved and new rolling schedules or alloys to take

advantage of increased metallurgical understanding of the underlying mechanisms and avoid

non-optimal rolling schedules.

9. Validation of the developed tools (equations and maps) for the production of strip and plate

steels by pilot rolling trials.

1.2 Main results

The main results of the project are summarised here. The full details of each Task are described in

Section 2.3. The project was divided into six Work Packages which interact as shown in Figure 1.

WP1: Eight coordination meetings of all the partners have been held during the project, hosted by each

partner in turn.

5

Partner Name C Si Mn Nb Al

AM C1Mn2 0.1 0 2 0 0.03

C1Mn1Nb7 0.1 0 1 0.07 0.03

C1Mn2Nb7 0.1 0 2 0.07 0.03

C1Mn2Nb3 0.1 0 2 0.03 0.03

Tata C1Mn1 0.1 0.25 1 0 0.03

C1Mn1Nb3 0.1 0.25 1 0.03 0.03

C1Mn1Nb1 0.1 0.25 1 0.01 0.03

C2Mn1Nb3 0.2 0.25 1 0.03 0.03

CEIT C2Mn2Al1 0.2 0 2 0 1

C2Mn2Al2 0.2 0 2 0 2

C2Mn2Nb3Al2 0.2 0 2 0.03 2

C2Mn2Nb7Al2 0.2 0 2 0.07 2

C2Mn2 0.2 0 2 0 0.03

C2Mn2Nb3Al1 0.2 0 2 0.03 1

CRM C2Mn2Si1 0.2 1 2 0 0.03

C2Mn2Si2 0.2 2 2 0 0.03

C2Mn2Nb3Si2 0.2 2 2 0.03 0.03

C2Mn2Nb7Si2 0.2 2 2 0.07 0.03

C2Mn2Nb3Si0 0.2 0 2 0.03 0.03

Figure 1: Project work packages and

interactions

Table 1: Nominal compositions of project steels (wt%)

WP2: Provision of Materials

Tasks 2.1 and 2.2: Production of laboratory casts and laboratory rolling and Task 2.3: Provision

of industrial material

One of the main objectives of the project was to study the effects of Mn, Si, Nb and Al additions on the

recrystallisation of austenite and the precipitation of Nb(C,N). A matrix of casts based around a

reference steel containing 0.1C, 1.0Mn, 0.03Al, 0.005N, 0.02P wt% was defined. The nominal

chemistries are shown in Table 1. This enabled the study of the effects of Mn, Si and Al individually,

the interaction effect of each element with Nb and the influence of increasing the amount of Nb on the

interaction effect. The steels were divided into 4 groups to distribute the work between the partners.

CEIT concentrated on studying the effect of Al, one of the first times this has been investigated in

detail; CRM on the effect of Si and Tata and AM on the effects of Nb at low and high Mn levels,

respectively. A total of 19 laboratory ingots were cast between the project partners and rolled down to

plate or strip material on pilot rolling mills to provide the steels for study in the project. Each partner

produced their own steels apart from CEIT whose steels were supplied by Tata. Additional casts were

produced by CRM for the validation pilot strip rolling trials in WP6. An industrially cast Nb

microalloyed steel for the validation plate rolling trials in WP6 was obtained from a Tata plate mill

with a chemistry within the range of the project steels.

WP3: Thermomechanical testing

Task 3.1: Definition of test programme

A large thermomechanical test programme to study static recrystallisation kinetics was carried out

using hot torsion and uniaxial Gleeble compression testing machines at each of the partners. The

effects of Nb, Al, Si, Mn and C content, strain, temperature, strain rate and austenite grain size on static

recrystallisation kinetics and recrystallised austenite grain size were investigated. Low strain

deformations (<0.1) and austenite grain growth after recrystallisation were considered by Tata. The

effects of Si, Mn and Nb content, temperature and strain rate on dynamic recrystallisation behaviour

were also studied at CRM and AM. Specific tests were designed to enable the study of Nb precipitation

in steels alloyed with Si or Al and compare their behaviour with the equivalent CMnNb steels (CEIT,

CRM). Samples were quenched out after interrupted torsion tests. Finally, multipass hot torsion tests

6

were performed on most of the project steels to determine the critical temperatures for recrystallisation

as a function of chemistry, strain and interpass time (CEIT, CRM).

Two sets of round robin tests were also initiated to compare the results obtained from the different

thermomechanical simulation machines of the partners. The first set compared the results from the

three torsion machines used in the project. The second test compared both the torsion and uniaxial

compression machines, and the methods of stress relaxation and double hit testing for determination of

the softening kinetics.

Task 3.2: Solute drag effect on static recrystallisation kinetics

Initial tests at each partner were performed to define the initial (reheated) austenite grain sizes for the

tests. The aim was to obtain a small (~50µm), medium (~100µm) and large (>200µm) grain size in

each set of steels to study the effect of this parameter on recrystallisation kinetics. Although this was

achieved in the Nb steels, it turned out to be impossible to obtain a grain size larger than 100µm in the

Al steels and smaller than 200µm in the Si steels even after an initial roughing treatment. Therefore

these two series of steel could only be studied at one level of initial grain size.

The softening data measured by each of the partners were fitted to an Avrami relationship and the

parameter t50, the time to 50% recrystallisation, and the exponent n were derived for each test

condition, for use in the modelling tasks in WP5. Stress relaxation tests on the C1Mn1 series of Nb

steels showed that the rate of softening decreased with decreasing strain (0.35 � 0.05), temperature

(1150 � 950°C) or strain rate (10 � 0.1/s), or increasing Nb content (0 � 0.03 wt%).

Recrystallisation was the dominant softening mechanism for deformation at temperatures of 1050°C

and above, apart from some tests at 0.05 strain which showed only recovery. Deformation at 950°C led

to recrystallisation in the C1Mn1 steel but mostly recovery in the Nb steels. The retardation of

softening in the Nb steels compared to the CMn steel was attributed to Nb solute drag at deformation

temperatures of 1050°C and above. At 950°C, as well as solute drag, an additional contribution due to

precipitation could be identified in the softening curves. No significant effect of increasing the C

content from 0.1 to 0.2 wt% was found on the softening kinetics in the absence of precipitation. Only a

weak effect of initial austenite grain size on the recrystallisation kinetics was found. This contradicts

other published data but no explanation for these results could be found.

Double hit torsion tests on the C1Mn2 series of Nb steels showed similar trends with temperature,

strain and initial austenite grain size as the C1Mn1 steels. With addition of 0.03 wt% Nb, softening was

significantly retarded at a temperature of 950°C due to precipitation, whereas at 0.07 wt% Nb this

retardation started at temperatures as high as 1050°C.

Double-hit torsion tests were carried out in the 1065-925ºC temperature range with the C2Mn2,

C2Mn2Al1 and C2Mn2Al2 steels to investigate the effect of Al in solid solution. The results showed

that the softening kinetics were retarded by Al addition, which was related to different mechanisms

depending on the temperature and Al content. For 1wt% Al the softening delay was due to Al solute

drag effect at all the temperatures investigated. Increasing to 2wt% Al, at high temperatures the

retardation was also due to solute drag, but at temperatures below 1000ºC, γ→α phase transformation

occurred concurrently with softening, leading to a higher retardation effect.

The effect of silicon on static recrystallisation kinetics (SRX) was obtained from stress-strain curves of

the double hit test torsion technique using the back extrapolation method. The effect of niobium in

slowing down the recrystallisation kinetics due to solute drag effect was clearly observed. At 0.7 strain,

dynamic recrystallisation was initiated in the steels without Nb additions. Comparison for one

deformation condition between steels containing zero and 1%Si revealed that Si slows down

recrystallisation. However, comparing the kinetics of steels containing 1% and 2%Si showed no clear

effect of Si on SRX kinetics, indicating a saturation effect of Si, in agreement with other results

published in the literature.

The round robin tests on steel C2Mn1Nb3 to compare test techniques showed slightly faster

recrystallisation kinetics were obtained from stress relaxation tests compared with double hit

compression tests on the Gleeble machine. This is in agreement with previous work. The round robin

7

tests on steel C1Mn1Nb7 to compare the torsion machines revealed important differences in flow stress

mainly attributed to differences in temperature measurements (location in sample, thermocouple or

pyrometer) and the adopted temperature control criterion, but also to differences in the strain hardening

behaviour. The differences in flow stress between the partners have led to differences in softening

kinetics both in terms of t50 and n parameters. An additional comparison between softening data from

torsion tests using an external database to the project showed only small differences in softening

compared with AM results. Further work would be required to fully resolve the discrepancies between

the torsion test results. Alternatively, it could be argued that the building of a common database with

contributions from different torsion machines may not be a reliable approach for constructing or fitting

a single predictive model.

Task 3.3: Solute drag effect on dynamic recrystallisation kinetics

A series of single hit hot torsion tests were performed to study the effect of Si and Mn on the critical

and peak strains for dynamic recrystallisation. Strain rates between 0.1 and 1.0/s and temperatures from

950 to 1050°C were applied. The second derivative method was used to analyse the data (Section

2.3.3.4).

Task 3.4: Grain growth kinetics

A matrix of tests was performed on steels C1Mn1, C1Mn1Nb1 and C1Mn1Nb3 to investigate the

austenite grain growth kinetics for hold times of up to 900s after deformation at temperatures between

1150 – 950°C and strains of 0.2 or 0.1. No significant grain growth was observed in any of the tests,

even at the higher temperatures where recrystallisation had clearly completed. At lower temperatures or

strains, it is likely that recovery and/or incomplete recrystallisation had occurred. The results, which

were reproducible, were consistent with previous experiments for Nb microalloyed steels but contrary

to experience for the C1Mn1 steel.

Task 3.5: Strain induced precipitation effects

Double-hit torsion tests were carried out with the C2Mn2Al1Nb3, C2Mn2Al2Nb3 and C2Mn2Al2Nb7

steels in the 1065-900ºC temperature range to investigate the effect of Nb(C,N) strain-induced

precipitation on the softening kinetics of Al steels. At temperatures below 1065ºC the softening

obtained for these steels was significantly delayed and did not complete in the range of interpass times

investigated. An arrest in the softening curves was detected, and in some tests, after a certain holding

time, the softening levels increased again. Samples were quenched out at different conditions and their

microstructure and precipitation state analysed using TEM. Similar interrupted torsion tests were

performed on the C2Si0Mn2Nb3, C2Si2Mn2Nb3, C1Mn1Nb7 and C1Mn2Nb7 steels to evaluate the

influence of Si and Mn on Nb precipitation. Single hit tests were performed at 1050, 1000 and 950°C

with an applied strain of 0.35. Hold times of up to 10000s were investigated as well as a sample

quenched before applying the deformation to define the initial precipitation state of the austenite.

Task 3.6: Determination of critical temperatures for recrystallisation

The critical recrystallisation temperatures were determined using multipass torsion tests for steels

C1Mn1Nb3, C2Mn1Nb3, and the Si and Al series of steels. 20-24 hits with the same deformation (in

the range 0.1 – 0.5 strain) and interpass time (5 – 100s) were applied at decreasing temperatures at

20°C intervals. The critical temperatures are defined as: the recrystallisation limit temperature (RLT),

the lowest temperature above which recrystallisation between passes is complete (85 or 95%

recrystallisation criteria), and the recrystallisation stop temperature (RST), the highest temperature at

which recrystallisation is completely absent (usually taken as 5% recrystallised fraction). Between

these limits, there is a temperature regime within which partial recrystallisation occurs. The no-

recrystallisation temperature, Tnr, was also determined, by plotting the mean flow stress (MFS) for each

pass against inverse temperature in the standard way. The RLT and RST were determined from plots of

the anisothermal fractional softening at each pass, calculated from the flow curves, against temperature.

Full details of these procedures are given in Section 2.3.3.7.

In the C1Mn1Nb3 and C2Mn1Nb3 steels, decreasing the interpass time from 30 to 10 seconds led to an

increase in both Tnr and RLT. Decreasing the applied strain per pass from 0.3 to 0.1 led to incomplete

softening between passes throughout the entire schedule. Increasing the C content from 0.1 to 0.2 wt%

8

slightly increased both the Tnr and RLT temperatures and decreased the Ar3 temperature. In the 2wt%Al

steels, some of the specimens broke during the test due to low ductility and as a result the tests could

not be completed. 1 or 2wt% Al addition resulted in an increase of the recrystallisation critical

temperatures, the amount of which depended strongly on the Al content. 1wt% Al led to a slight

increase in the Tnr of ∼30ºC, whilst 2wt% Al addition resulted in a significantly larger increase, from

∼120 to 200ºC. For the 1wt% Al steel, the Tnr was further increased by 100-120ºC with 0.03%Nb

addition. However, the Tnr was almost unaffected by 0.03%Nb or 0.07%Nb addition to the 2%Al steel.

Increasing the Si content from 1 to 2 wt% did not affect the recrystallisation regimes. Addition of Nb to

the Si steels significantly raised the RST thus reducing the width of the partial recrystallisation regime.

WP4: Microstructure analysis

The microstructure of torsion and uniaxial compression specimens quenched at different conditions

was examined by optical microscopy to reveal the prior austenite grain structure by all the partners.

The specimens were sectioned and prepared by the classical techniques of polishing and etching. The

austenite grain boundaries were revealed using an aqueous solution of picric acid whilst 2% Nital was

used when ferrite was present. Grain sizes and distributions were determined using the mean equivalent

circle diameter (ECD) parameter, measured with the help of image analysis software. Micrographs

were taken from the etched specimens and the grain boundaries were traced so that the software could

detect them. In specimens where the grain boundaries were difficult to detect, the ASTM chart

comparison method was used instead. In selected samples, Transmission Electron Microscopy (TEM)

was used to analyse any precipitates in carbon extraction replicas. Electrolytic matrix dissolution

techniques have also been applied to a limited number of samples to analyse the amount of Nb

precipitated.

Task 4.1: Quantification of recrystallised fraction

The recrystallised fraction in the Al steels was quantified in torsion specimens quenched after

deformation and different holding times for one softening condition (C2Mn2Al1 steel, T=1065ºC,

ε=0.35). In the initial softening stages, the recrystallised fraction was lower than the softening

determined mechanically, but at longer interpass times the two values converged. However, due to the

similar size of the initial and the recrystallised grain sizes the results were only approximate.

A new methodology for quantifying the recrystallised fraction has been developed and applied at AM

in this project based on the application of software developed for the reconstruction of austenite

microstructures from EBSD maps of martensitic structures and the use of a criterion for distinguishing

recrystallised and non-recrystallised grains based on the mean misorientation angle in the reconstructed

austenite grains. The first steps toward validation of this methodology for recrystallised fraction

determination have been made with encouraging results revealed by the comparison of the calculated

values with softening fraction data derived from double hit torsion tests. Further work is required to

consolidate the application of this methodology including: increasing indexation rates in original maps,

increasing the number of maps and/or reconstructed grains for statistical validation and further

improving the proposed criterion for identifying recrystallised grains.

Task 4.2: Quantification of austenite grain structure and distribution

The reheated or recrystallised austenite grain sizes were characterised in the samples tested in the

Mn1Nb series steels. An initial grain size of ~100µm could be obtained in all the steels and conditions

to obtain smaller and larger grain sizes were also established. The austenite grain size was refined by

deformation and recrystallisation in all four Mn1Nb steels, the grain size being smaller at larger strains

and lower deformation temperatures. A weak effect of Nb content on the recrystallised grain size was

observed.

Thermodynamic calculations carried out with the Thermo-Calc software (TCFE 6 database) to

investigate the effect of Al on the microstructures of the steels investigated indicated that Al is a strong

ferrite stabiliser; according to the software, 1%Al addition (C2Mn2Al1 steel) raises the Ae3

temperature from 780ºC to 900ºC, while 2%Al addition results in a further increase of up to 1030ºC.

The initial microstructure present before the torsion tests was analysed in specimens quenched directly

after the reheating treatment. The initial austenite grain sizes measured in the Si steels were around

9

230µm. The initial austenite grain sizes measured in the Al steels were 56 - 104 µm, and a slight grain

refinement effect due to Al and Nb addition was observed. In the 2%Al steels, a small amount of ferrite

was also present in the reheated specimens but as this was less than 5% it was not considered to affect

the softening behaviour of the steels. The microstructural evolution of the steels during static softening

was investigated. For the 2%Al steels, at temperatures below 1000ºC, γ�α phase transformation was

found to be concurrent with softening increase, leading to the high softening retardation observed for

these steels at the lowest temperatures. The recrystallised microstructure was characterised in the tests

in which the softening was not affected by phase transformation. No significant effect of temperature

on the recrystallised grain size was observed, whilst decreasing the applied strain led to an increase in

the austenite grain size.

The microstructure evolution of the steels during the multipass torsion tests was investigated in

specimens quenched at different points of the deformation schedule. In the 2wt% Al steels, evidence of

γ�α phase transformation was observed at temperatures close to the Tnr. The high Tnr increment

observed for these steels was attributed to the onset of transformation.

Task 4.3: Quantification of precipitates

Carbon replicas extracted from C2Mn2Al1Nb3, C2Mn2Al2Nb3 and C2Mn2Al2Nb7 specimens

quenched after the soaking treatment were investigated by TEM to determine the initial precipitation

state before the torsion tests. A significant amount of undissolved precipitates was only found in

C2Mn2Al2Nb7, in good agreement with the predictions of the solubility products found in the

literature.

The precipitation state of C2Mn2Al2Nb3, C2Mn2Al2Nb7 and C2Mn2Al1Nb3 specimens quenched

after deformation and different holding times was investigated. After deformation at 1000ºC, the

precipitates found in the martensite (quenched austenite) and in the ferrite were scarce denoting a

limited effect of strain-induced precipitation at this temperature. However, at lower temperatures a

significant number of strain-induced precipitates were found both at the plateau onset and finish times.

Precipitates were found both in the ferrite and martensite phases, although they were coarser and more

abundant in the ferrite. The martensite precipitate size decreased significantly with decreasing the

deformation temperature. Comparison with the C2Mn1Nb3 steel after deformation at the same

temperatures indicated that strain induced precipitation kinetics appeared to be slightly delayed in the

Al containing steel.

The strain-induced precipitation evolution during the multipass torsion tests was investigated by

characterising the precipitation state of AlNb specimens quenched two passes below the Tnr. In the

Al2Nb3 steel with an interpass time of 100s the precipitates found were scarce. In the Al2Nb7 steels

with an interpass time of 30s, a significantly larger amount of precipitates were found in the ferrite and

martensite phases, although they were relatively coarse. Finally, for the Al1Nb3 steel and interpass

time of 30s, a very small number of precipitates were found, suggesting that solute drag could be the

main mechanism leading to strain-accumulation in this case.

The electrolytic matrix dissolution technique was used to analyse the amount of Nb precipitated in

torsion samples quenched directly after deformation for selected Si and Mn series steels. For steels

C2Si0Mn2Nb3 and C2Si2Mn2Nb3 the results indicated that increasing the Si content decreased the

growth rate of the precipitates.

WP5: Modelling and construction of processing maps

Task 5.1: Assessment of current model capabilities

The partners all had their own empirical models, developed over many years experience, at the start of

the project. Those of Tata, CEIT and CRM (StripCam) all have a similar basis on the work of Sellars

for the calculation of austenite recrystallisation and precipitation kinetics. CEIT have also worked on

extending the physically based model proposed by Zurob within the project, whilst Tata have

considered approaches to modeling solute drag. A comparison exercise was carried out at the start of

the project to benchmark the capabilities and limitations of the existing models and to clarify in detail

10

where specific improvements were required. The main areas identified included: recrystallisation

kinetics at low strains (<0.1) for CMn and Nb steels (Tata); recrystallised austenite grain size and grain

size after grain growth too large (Tata); improved effect of solute Nb and addition of a precipitation

model into StripCam (CRM); introduction of the effect of Al additions into both the empirical and

physically-based models CEIT).

Task 5.2: Modelling of static recrystallisation kinetics

The experimental results from Task 3.2 were analysed for each series of steels to determine new

coefficients for the static recrystallisation equations in the empirical models. Improvements have been

made to the coefficients used in the Tata static recrystallisation equations using the results from the

Mn1Nb steels. A weaker effect of strain and initial austenite grain size on the time for 50%

recrystallisation (t50) was found compared with the existing equation, but the effect of strain rate was

similar. The new t50 equation can be applied to both CMn and Nb microalloyed steels and has been

extended to more accurately predict the effect of lower strain deformations (below 0.1), which are

important for plate mill rolling. The activation energy for recrystallisation was found to be a function

of Nb content and smaller than in the current model, but consistent with other published data. The

Solute Retardation Parameter (SRP) for Nb derived from the t50 data was in good agreement with other

published values. An average Avrami exponent n of 1.09 was obtained, slightly higher than in the

current model.

An equation for the recrystallisation start time has been determined by analysing the contributions of

recovery as well as recrystallisation to the softening curves, and was found to be a function of

temperature, strain and Nb content. The behaviour is similar to published work, and shows the

importance of nucleation kinetics to the overall recrystallisation behaviour.

The retarding effect of Al in solid solution on the static softening has been quantified in terms of the

SRP, excluding the tests in which phase transformation or strain-induced precipitation took place. The

value obtained has been implemented in a semi-empirical equation developed in previous work at CEIT

for the prediction of the times for 50% softening. The equation gives a good fit for the C2Mn2 and all

the Al and AlNb steels investigated. The retardation effect of 1 wt% Al was found to be equivalent to

that of 0.027 wt% Nb. The relative retarding potential of the elements decreased in the order

Nb>>Al>Si, which is in agreement with previous published work.

A physical model has been applied to analyse the effect of Al in solid solution in the static softening

kinetics in cases where recovery and recrystallisation softening mechanisms take place. An expression

for the grain boundary mobility of the C2Mn2 steel has been derived and the effect of Al in solid

solution on the recrystallisation kinetics quantified by means of the Cahn model. The results obtained

suggest that as well as retarding recrystallisation, Al also affects the recovery kinetics.

The StripCam model has been improved by adding a criterion that defines the start of precipitation (5%

Nb precipitated) and thus the retardation of the static recrystallisation kinetics. The t50 equation was

modified to incorporate a temperature dependent effect of Nb in solid solution, in the same way as the

CEIT model, which significantly improved the predictions of the model when compared against t50

measurements from the project partners. Good agreement with the predictions of the CEIT model was

also obtained. No effect of Si was added to the equation as none was determined in the experimental

work in Task 3.2.

Task 5.3: Modelling of dynamic recrystallisation kinetics

The data from the dynamic recrystallisation tests on the Si and Mn steels in Task 3.3 have been

analysed to model the peak stress, saturation stress and critical strain. Peak stress increased with

decreasing temperature, increasing strain rate and increasing Si content. The effect of strain rate on the

saturation stress was slightly higher than in the existing StripCam equation. Increasing Nb content led

to an increase in the activation energy but increasing Si had the opposite effect. The influence of strain

rate on the critical strain was found to be consistent with the StripCam equation. Si addition was found

to increase the critical strain for dynamic recrystallisation.

11

Task 5.4: Modelling of austenite grain size

Improvements have been made to the coefficients used in the statically recrystallised austenite grain

size equation of Tata based on the experimental results from WP4. A weaker dependence of

recrystallised grain size on initial grain size and strain rate was found compared with the current model,

but the effect of strain was identical. No dependence of recrystallised grain size on deformation

temperature was found, unlike the current model but consistent with other models in the literature

including that of CEIT. The new equation produced a much better fit with the experimental data. The

recrystallised austenite grain size in the Al steels has been compared with the different models found in

the literature. A good fit was obtained with the equation proposed by Fernandez et. al. for microalloyed

steels. Analysis of the grain growth data did not produce consistent results with which to improve the

grain growth equation. Exponents derived in previous Tata work have been applied and produced

reasonable predictions for the current data.

Task 5.5: Modelling of recrystallisation-precipitation interactions

The new Tata model from Task 5.2 predicted the correct trends in recrystallisation critical temperatures

(RLT, RST, Tnr) with strain and interpass time but the RLT was too low compared with the temperature

derived from multipass torsion test results on the Nb steels. Better prediction of the softened fraction

derived from the torsion data, including partial recrystallisation at all temperatures at 0.1 strain, was

obtained by using the (higher) strain exponent from the CEIT model in the t50 equation. The effect of C

in the model, via the solubility product term for Nb(C,N) precipitation used in the time for 5%

precipitation equation, on the recrystallisation behaviour was much stronger than was indicated by the

torsion tests. Precipitation pinning was predicted to stop recrystallisation at higher temperatures than

observed experimentally.

Due to the occurrence of γ�α transformation after deformation the data corresponding to the Al2Nb

steels could not be considered in order to investigate the effect of Al on the strain-induced precipitation

kinetics. Therefore, only the results obtained for the C2Mn2Al1Nb3 and C2Mn1Nb3 steels were

analysed. The TEM replica analysis carried out suggested that the onset of strain-induced precipitation

was retarded for C2Mn2Al1Nb3 compared to the C2Mn1Nb3 steel. This could be due to the higher Al

or Mn content in C2Mn2Al1Nb3, or to the absence of free N, which is expected to be pinned in the

form of AlN in this steel.

Task 5.6: Construction of processing regime maps

The recrystallisation critical temperatures (Tnr, RLT, RST and Ar3) obtained from the multipass torsion

tests were plotted in the form of processing regime maps in order to compare the potential for strain

accumulation of the different steels studied in the project. In steels C1Mn1Nb3 and C2Mn1Nb3, the

increase in C from 0.1 to 0.2 wt% widened the temperature range over which strain accumulation with

no recrystallisation can occur. The calculated maps using the new Tata model showed a much wider

range of temperatures at which complete recrystallisation occurred and a narrower range for partial

recrystallisation. Better prediction of the processing regimes derived from the torsion tests was

obtained by using the strain exponent from the CEIT model in the t50 equation. The processing maps

indicated that strain accumulation potential was slightly increased by 1wt% Al addition to the C2Mn2

steel, and further enhanced by 0.03%Nb addition. The 2wt% Al steels also showed a high potential for

strain accumulation similar to that obtained for the C2Mn2Al1Nb3 steel; however, due to the loss of

ductility observed for these steels this is not expected to be of practical applicability.

Processing maps predicting the grain size and the accumulated strain have been constructed for plate

and strip rolling conditions using the CEIT model for different steel compositions. In the plate rolling

simulations, for the three compositions considered, the results indicated that the final austenite grain

size tended to decrease with increasing the End Hold Temperature (EHT) and thicker final gauges. This

seems to be related with the configuration of the hot rolling schedules. At EHT above 900ºC, the

smallest final austenite grain sizes were obtained for the C2Mn2Al1Nb3 steel, while the C2Mn2Al1

steel resulted in the coarsest microstructure. This is related to the strain accumulation potential of the

three steels.

12

In the strip simulations, for the three compositions considered, as the final gauge decreased smaller

grain sizes and higher accumulated strain levels were obtained. This can be directly related to the larger

strain applied in order to obtain thinner final gauges. Finally, finer microstructures were obtained in the

C1Mn1Nb7 steel rather than C1Mn1Nb3, as a result of the higher potential for strain accumulation due

to enhanced solute drag effect and strain-induced precipitation for the 0.07%Nb steel. The results

obtained for the C2Mn2Al1Nb3 and C1Mn1Nb7 steels were very similar.

WP6: Application and validation

Task 6.1: Design of validation tests

Several sets of validation tests were defined:

• Multi-hit Gleeble uniaxial compression tests, to validate the recrystallisation kinetics equations

• Multi-hit Gleeble uniaxial compression tests, quenched out after different passes or hold times,

to validate the recrystallised austenite grain size and grain growth equations (Tata)

• Multi-pass torsion simulations of simulated industrial plate and hot strip mill schedules, to

validate the fraction softened between passes (CEIT)

• Multi-pass torsion simulations of actual industrial plate mill schedules, to validate the fraction

softened between passes (CEIT)

• Laboratory plate mill rolling trials, to validate the predicted processing regime maps for

recrystallised fraction and austenite grain size (Tata)

• Pilot hot strip mill rolling trials, to validate the predicted processing regime maps for

recrystallised fraction and austenite grain size (CRM/AM)

Task 6.2: Single and double hit validation tests

A large number of single and double hit tests had already been performed in Task 3.2 as part of the

model development work. The validation tests were designed to concentrate on applying these results

to multi-hit deformation tests, which are more representative of the conditions where the models will

be applied.

Task 6.3: Multipass validation tests

The validation tests at Tata were performed on a standard Nb microalloyed industrial plate steel, with a

similar chemistry to the project steel C1Mn1Nb3. The fraction softened in the multi-hit Gleeble tests

was accurately predicted by the new Tata model for two different pass strains and interpass times

typical of plate rolling. The multi-hit austenite grain size Gleeble validation tests showed good

agreement between the measured austenite grain sizes and the predictions of the new model at three

temperatures and two applied strains.

The multi-pass torsion simulations of industrial plate schedules were performed by CEIT on steel

C1Mn1Nb3 using schedules supplied by Tata for representative 25mm and 50mm gauge plates. The

results indicated that complete recrystallisation was not occurring during the roughing passes. The new

Tata model produced reasonable predictions of the fraction softened in these simulations, which were

further improved by using the higher strain exponent from the CEIT model in the t50 equation.

The predictions of the simulations performed with the CEIT model to build the processing maps were

validated by multipass torsion tests intended to simulate real plate and strip hot rolling schedules. Plate

rolling simulations were carried out with the C2Mn2Al1Nb3 and C2Mn2Al1 steels for EHT of 900 and

1000ºC and final gauges of 50 and 30mm. In good agreement with the processing maps, refined

microstructures were obtained for the highest EHT simulations. For C2Mn2Al1Nb3, good agreement

between the microstructural measurements and the model predictions were obtained, whereas in the

case of the C2Mn2Al1 steel the model tended to predict coarser grain sizes than the experimental

results. Strip rolling torsion simulations were carried out with the C2Mn2Al1Nb3 steel, for the same

Finish Rolling Temperature, 900ºC, and two different gauges, 6 and 3 mm. The predictions of the

model showed very good agreement with the experimental grain size and softening results.

13

Task 6.4: Pilot rolling trials

Validation trials were performed on the Tata pilot plate rolling mill using industrial slab material from

a Nb microalloyed plate grade. Six plates were rolled using different rolling schedules identified from

the processing regime maps based on an industrial plate rolling schedule, with samples quenched out at

intermediate and final passes to study the austenite grain size evolution. Two EHTs of 1000 and 950°C

and final plate gauges of 30 and 50mm were investigated. Good agreement was obtained between the

measured and predicted austenite grain sizes in the plates where it was possible to measure them. The

difference in austenite grain structure between plates rolled to 40mm with an EHT of 1000°C

(recrystallised grains) and 950°C (pancaked grains) was correctly predicted by the model.

Validation trials were performed on the CRM pilot strip mill using a laboratory cast of steel

C2Mn2Al1Nb3. Four strips were rolled to different FRT and final gauges of 2-6mm, identified from

the processing regime maps based around an industrial hot strip mill schedule supplied by AM.

Samples were quenched out 5s after the final pass for microstructure examination. Good agreement

was obtained between the measured and predicted austenite grain sizes in the strips. In the strip with

the lowest FRT, ferrite was observed in the microstructures that could not be predicted by the model.

Task 6.5: Validation against pilot mill and industrial mill data

Comparison of measured laboratory and industrial plate mill loads with the predictions of a Tata hot

rolling model incorporating the new recrystallisation equations showed that the model was accurate

during the passes where complete or partial recrystallisation occurred, but predicted too much strain

accumulation and thus too high loads once recrystallisation had stopped due to precipitation of

Nb(C,N). The temperature range at which rolling forces start to accumulate was estimated from the

measured rolling forces and temperatures during the pilot strip rolling trials and compared with the

predictions of the StripCam model. The rolling forces started to accumulate at a later pass (lower

temperature) in the 6mm strips compared with the thinner strips.

1.3 Conclusions

The main conclusions from the project were as follows:

• Addition of Al to CMn steels led to retardation of the softening kinetics. At 1wt% Al this was

due to solute drag but at 2wt% Al, phase transformation of austenite to ferrite occurred

concurrently at temperatures below 1000°C leading to a higher retardation effect.

• The hot ductility of the 2 wt% Al steels in the hot torsion tests was low suggesting that this

level of Al may not be practically applicable.

• Strain induced precipitation of Nb was found in the AlNb steels at lower temperatures. The

kinetics of precipitation appeared to be slightly delayed in the presence of Al.

• The retarding effect of Al on static recrystallisation kinetics was quantified in terms of a Solute

Retardation Parameter and incorporated into the equation to predict the time to 50%

recrystallisation. The retardation effect of 1wt % Al was found to be equivalent to 0.027 wt%

Nb.

• The effect of Si and strain induced Nb precipitation on the austenite microstructure evolution

was studied by means of hot torsion test. Silicon retards recrystallisation, the effect being more

marked between 0% and 1%Si than between 1% and 2%Si.

• The solute retardation potential per wt% of the alloying elements investigated was found to

decrease in the order Nb>>Al>Si

• No significant grain growth during isothermal holding after recrystallisation was observed in

the CMn and CMnNb steels. The latter is consistent with previous results but the lack of

growth at high temperatures in the CMn steel was unexpected.

• The round robin tests to compare the torsion machines revealed important differences in flow

stress mainly attributed to differences in temperature measurements and the adopted

temperature control criterion, but also to differences in the strain hardening behaviour. Further

work would be required to fully resolve the discrepancies between the torsion test results.

14

• A new methodology for quantifying the recrystallised fraction has been developed based on

software for the reconstruction of austenite microstructures from EBSD maps of martensitic

structures and the use of a criterion for distinguishing recrystallised and non-recrystallised

grains based on the mean misorientation angle in the reconstructed austenite grains.

• Preliminary validation of this methodology has been made with encouraging results obtained

from the comparison of the calculated values with softening fraction data derived from double

hit torsion tests.

• The Tata model for static recrystallisation has been improved to provide better predictions of

the time to 50% recrystallization for CMnNb steels, the effect of low strain deformations and

recrystallised austenite grain size.

• The CRM model for static recrystallisation (StripCam) has been enhanced with the addition of

a Nb precipitation start criterion and a temperature dependent Nb solute drag term

• Physical models have been applied to analyse the effect of Nb and Al in solid solution on the

static softening kinetics where both recovery and recrystallisation take place. The results

suggest that Al is also retarding recovery.

• Multipass torsion tests to simulate industrial plate rolling schedules showed that only partial

recrystallisation was occurring in the initial roughing passes.

• The fractional softening in the multipass torsion schedules was well predicted by the CEIT and

Tata models.

• Processing regime maps to predict the austenite grain size, recrystallised fraction and retained

strain were constructed using the new models for plate and strip rolling schedules with

variations in final gauge, End Hold Temperature or Finish Rolling Temperature.

• Laboratory plate rolling trials designed from the processing maps were performed on an

industrial Nb microalloyed plate steel. Good predictions of the austenite grain size and

recrystallisation state were obtained.

• Pilot strip rolling trials based on the processing maps were performed on an AlNb laboratory

cast steel. Good agreement between the observed and predicted austenite grain sizes was found.

1.4 Applications

The enhanced models developed within the project will be applied by Tata Steel in their plate mill hot

rolling models to assist with the design of new products and rolling schedules. ArcelorMittal will

utilise their models for product development of hot rolled strip grades. CRM and CEIT will apply their

models both for their own research activities and in collaborations with their steel production partners.

No patents are foreseen from this project, which concentrated on fundamental metallurgical knowledge

development and modelling. A number of publications have already been presented at conferences and

in journals and more are planned after the completion of the project. This will transfer some of the

knowledge developed within the project to a wider audience within the steel and metallurgical

community.

15

2. Scientific and technical description of the results

2.1 Objectives of the project

Project MICROTOOLS will develop tools to construct processing regime maps combining

temperature-time-deformation history with enhanced knowledge of the operational metallurgical

mechanisms during hot rolling. These tools will help design improved and new rolling schedules and

steel chemistries, to exploit the increased metallurgical understanding of the underlying mechanisms

without compromising mill productivity. The compositional dependence of the austenite microstructure

evolution (recrystallisation and precipitation kinetics) for major alloying elements (Mn, Si, Al, Nb) will

be studied using thermomechanical testing and high resolution characterisation techniques, and

integrated into hot rolling models. Application to strip and plate steel production will be demonstrated.

The objectives of the project were as follows:

1. Investigation of the effects of the alloy elements Mn, Si, and Nb on the recrystallisation

behaviour of austenite in hot rolled steels by thermomechanical testing, both individually and

in combination, extending the range to levels relevant to modern high strength steels.

2. Assessment for the first time of the effects of Al additions on the static recrystallisation

kinetics via both solute drag and possible interactions with Nb precipitation kinetics.

3. Improvement of the recrystallisation equations for the effect of low strain deformations (<0.2)

4. Development of enhanced predictive equations/models for the recovery, recrystallisation and

precipitation kinetics, austenite grain size and recrystallisation critical temperatures.

5. Development of a tool for modelling austenite grain size distributions.

6. Development of more physically based models for investigation of specific mechanisms, such

as strain induced precipitation.

7. Construction of processing regime maps which combine temperature-time-deformation history

with enhanced knowledge of the operational metallurgical mechanisms.

8. Application of these maps to help design improved and new rolling schedules or alloys to take

advantage of increased metallurgical understanding of the underlying mechanisms and avoid

non-optimal rolling schedules.

9. Validation of the developed tools (equations and maps) for the production of strip and plate

steels by pilot rolling trials.

2.2 Comparison of initially planned activities and work accomplished

All the main activities of the project which were originally planned have been addressed. The

achievements against the original objectives were as follows:

1. The effects on the static and dynamic recrystallisation kinetics of austenite of Mn and Si levels

up to 2 wt% and Nb contents up to 0.07 wt% have been studied, both individually and in

combination, in a matrix of thermomechanical double hit and stress relaxation tests on

laboratory cast steels (Tasks 3.2 and 3.3).

2. The effects of Al additions up to 2 wt%, with and without Nb contents up to 0.07 wt%, have

been studied, both individually and in combination, in a matrix of torsion tests on laboratory

cast steels (Task 3.2).

3. A series of tests with deformations of 0.35 to 0.05 strain have been performed on CMn and Nb

steels at temperatures from 1150 to 950°C using stress relaxation tests on laboratory cast steels

(Task 3.2). New equations for static recrystallisation incorporating the results at low strains

have been developed (Tasks 5.2 and 5.4).

4. Improved metallurgical equations and models have been developed to include the effects of the

higher alloying additions of Mn, Si and Al (Tasks 5.2, 5.3, 5.4)

5. The planned work on austenite grain size distributions was not carried out because the grain

sizes in the steels studied were very uniform and a distribution model was not required to

successfully predict their behaviour (WP5).

16

6. A physical model was applied to analyse the effect of Al in solid solution on the static

softening kinetics where recovery and recrystallisation softening mechanisms take place (Task

5.2)

7. Processing regime maps for each of the steel types were constructed based on both

thermomechanical test results and the predictions of the models (Task 5.6).

8. Processing regime maps were calculated for different steels and processing parameters, based

on industrial strip and plate rolling schedules, and used to design the laboratory validation

rolling trials (Task 6.1)

9. Pilot rolling trials were successfully carried out on the laboratory plate mill at Tata Steel and

the pilot strip mill at CRM in collaboration with ArcelorMittal (Task 6.4).

The project Gantt chart showing the originally planned programme (black cells) and the final status

against plan (shaded cells) is given in Figure 2. All of the planned Work Packages and Tasks were

addressed, although there were some major delays in parts of the experimental work due to testing and

measurement difficulties, particularly with the torsion machine at one of the partners (AM), the round

robin tests and the need for additional tests to clarify unexpected results in Tasks 3.2 and 3.4. The

torsion machine at AM was significantly upgraded and detailed discussions were held between the

other partners operating torsion machines within the project to help resolve the difficulties. This

resulted in some of the experimental work on the Mn2Nb steels being completed towards the end of the

project, thus reducing the time available for more detailed analysis. The modelling activities of AM

within WP5 were also restricted due to the lack of reliable experimental data from the torsion machine

until near the end of the project. More effort than originally planned was invested in development of

the methodology for characterisation of recrystallised austenite fractions using the EBSD-based grain

reconstruction technique (Task 4.1). However this was due to the great promise shown by the initial

results from this work so the development was extended. As many of the tasks proceeded in parallel,

and some activities started earlier than planned, there was time within the schedule to still achieve the

main objectives of the project. A large effort was made by all of the partners working together in the

final 6 months of the project to successfully complete the validation trials in WP6.

Hours on project/

Beneficiary(s)

1st year 2nd year 3rd year 4th year Work

packages

Work packages’ title Deliverab

les

1 2 3 4 III IV I II III IV I II III IV I II III IV

WP 1 Project coordination 550 310 300 300

Task 1.1 Coordination meetings 200 120 100 150

Task 1.2 Production of reports D1.1 350 190 200 150

WP 2 Provision of materials 250 294 250 0

Task 2.1 Production of laboratory casts D2.1 100 80 150 0

Task 2.2 Laboratory rolling D2.2 100 214 100 0

Task 2.3 Provision of industrial material 50 0 0 0

WP 3 Thermomechanical testing 1000 1430 950 1400

Task 3.1 Definition of test programme D3.1 50 50 50 50

Task 3.2

Solute drag effect on static

recrystallisation kinetics D3.2 350 540 350 500

Task 3.3

Solute drag effect on dynamic

recrystallisation kinetics D3.2 0 380 200 0

Task 3.4 Grain growth kinetics D3.3 200 0 0 0

Task 3.5

Strain induced precipitation

effects D3.2 400 340 350 500

Task 3.6

Determination of critical

temperatures for recrystallisation D3.4 0 120 0 350

WP 4 Microstructure analysis 1600 910 1450 1200

Task 4.1

Quantification of recrystallised

fraction D4.1 500 0 450 350

Task 4.2

Quantification of austenite grain

structure

D4.2,

D4.3 450 400 400 350

Task 4.3 Quantification of precipitates D4.4 650 510 600 500

17

Hours on project/

Beneficiary(s)

1st year 2nd year 3rd year 4th year Work

packages

Work packages’ title Deliverab

les

1 2 3 4 III IV I II III IV I II III IV I II III IV

WP 5 Modelling and construction of

processing maps 950 400 900 1100

Task 5.1

Assessment of current model

capabilities D5.1 100 100 100 100

Task 5.2

Modelling of static

recrystallisation D5.2 300 0 250 200

Task 5.3

Modelling of dynamic

recrystallisation D5.2 0 200 150 0

Task 5.4 Modelling of austenite grain size

D5.3,

D5.4 150 0 0 300

Task 5.5

Modelling of recrystallisation-

precipitation interactions D5.5 250 0 250 300

Task 5.6

Construction of processing

regime maps D5.6 150 100 150 200

WP 6 Application and validation 850 710 600 600

Task 6.1 Design of validation tests D6.1 100 40 50 100

Task 6.2

Single and double hit validation

tests D6.2 150 0 250 0

Task 6.3 Multipass validation tests D6.3 200 300 150 500

Task 6.4 Pilot rolling trials D6.4 300 300 150 0

Task 6.5

Validation against pilot mill and

industrial mill data D6.5 100 70 0 0

Total Hours on project 5200 4054 4450 4600

Figure 2: Programme Gantt chart indicating project progress (shaded cells) against original plan (black)

2.3 Description of activities and discussion

The work programme was divided into 6 work packages which interact as shown in Error! Reference

source not found.. The main objectives of each work package (WP) are given below. The task details

are provided in the WP descriptions in the Technical Annex.

WP1 – Project Coordination: Project meetings and reporting

WP2 – Provision of Materials: To produce a matrix of laboratory cast steels for the study and to

provide industrial material for validation trials.

WP3 – Thermomechanical Testing: To determine the effect of solute elements (Mn, Si, Al) on the

kinetics of recovery, static and dynamic recrystallisation and strain induced precipitation of Nb. To

determine the effect of steel composition, temperature and interpass time on austenite grain growth

kinetics after recrystallisation. To determine the interaction between recrystallisation and precipitation

as a function of composition, temperature, strain, strain rate and interpass time to generate data for

modelling and processing maps. To determine the critical temperatures for recrystallisation.

WP4 – Microstructure Analysis: To quantify the microstructural parameters such as recrystallised

austenite fraction, mean austenite grain size and grain size distribution, amount of Nb in solution and in

precipitate form and type, volume fraction and size of microalloy precipitates.

WP5 – Modelling and Construction of Processing Maps: To extend the recovery and

recrystallisation kinetics models to more fully include the effects of Mn, Si and Al. To improve models

to predict austenite grain size after recrystallisation and the equations to predict austenite grain size

after grain growth during long interpass times. To extend the physically based models for recovery,

recrystallisation and strain induced precipitation. To construct processing regimes maps using the new

equations.

18

WP6 – Application and Validation: To validate the developed models by thermomechanical tests and

laboratory hot rolling trials and to apply the models and maps to design optimised rolling schedules.

Tata concentrated on a matrix of thermomechanical simulations tests to study the effect of Nb

additions on the static recrystallisation kinetics, particularly at lower strains and different strain rates,

and austenite grain growth kinetics at several temperatures. Improvements to the existing

microstructural models for static recrystallisation and recrystallised austenite grain size have been

carried out. Processing regime maps have been constructed for typical plate mill rolling schedules.

Validation trials were performed on a laboratory pilot plate rolling mill.

The work at CEIT has focused on the study of the combined effect of Nb and Al on the static softening

behaviour of CMn steels. Double-hit torsion tests have been carried out with the C2Mn2AlNb project

steels. Specimens have also been quenched at different deformation conditions and interpass times in

order to analyse the microstructural evolution and precipitation state by Transmission Electron

Microscopy (TEM). In addition, the effect of Nb and Al addition on the microstructural evolution of

CMn steels during multiple deformation schedules has been investigated. Multipass torsion tests have

been carried out, and from the tests, the non-recrystallisation temperature (Tnr), as well as the

recrystallisation limit and stop temperatures (RLT and RST) have been determined. Further

development of the physically-based Zurob model was carried out and the effect of Al on softening

retardation was incorporated into an empirical recrystallization model. Processing regime maps were

constructed for the validation trials of all the partners.

CRM has focussed on studying the effect of Si alone and on the coupled effect of Si with Nb on

austenite recrystallisation and precipitation. Static and dynamic recrystallisation studies have been

conducted, multipass torsion tests to determine the Tnr, RLT and RST have been performed, and the

Stripcam recrystallisation model has been improved. Quantification of precipitates was carried out

using the matrix dissolution technique. Validation trials were performed on a laboratory pilot strip

rolling mill.

ArcelorMittal have performed a series of double hit torsion tests to investigate the effect of Mn and

Nb on static and dynamic recrystallisation kinetics. An EBSD methodology for reconstruction of parent

austenite grains from quenched microstructures has been successfully applied and extended to

quantification of recrystallised austenite fraction. Quantification of precipitates was carried out using

the matrix dissolution technique. A detailed assessment of the results from the round robin comparison

exercise between the torsion machines employed in the project was performed. Validation strip rolling

trials were performed in conjunction with CRM.

2.3.1 WP1: Project coordination

2.3.1.1 Task 1.1: Coordination meetings

Eight full coordination meetings attended by all partners have been held during the project. The

progress of each work package was presented and experimental techniques and results were discussed

in detail. The meetings were hosted by each partner in turn, the final meeting being held at Tata Steel,

Swinden Technology Centre, Rotherham, UK in September 2012.

2.3.1.2 Task 1.2: Production of reports

All the required annual, mid-term and final reports were submitted on schedule to the European

Commission.

2.3.2 WP2: Provision of Materials

The objectives of this work package were:

• Production of a matrix of laboratory cast steels for study in the project

• Provision of industrial material for validation trials

19

• Distribution of material amongst the project partners

2.3.2.1 Task 2.1: Production of laboratory casts

One of the main aims of the project was to study the effects of Mn, Si, Nb and Al additions on the

recrystallisation of austenite and the precipitation of Nb(C,N). A matrix of casts based around a

reference steel containing 0.1C, 1.0Mn, 0.03Al, 0.005N 0.02P wt % was defined and agreed between

the partners at the first project meeting. The steels contained the following variations in chemistry:

• Two carbon levels: 0.1 and 0.2 wt%

• Two Mn levels: 1.0 and 2.0 wt%

• Four Si levels: 0, 0.25, 1.0 and 2.0 wt%

• Four Nb levels: 0, 0.01, 0.03 and 0.07 wt%

• Three Al levels: 0.03, 1.0 and 2.0 wt%

This has enabled the study of the effects of Mn, Si and Al individually, the interaction effect of each

element with Nb and the influence of increasing the amount of Nb on the interaction effect. The

chemistries were designed to isolate the effects of increasing the levels of the main alloy element, the

carbon and the Nb. The relatively high level of P was used to favour the identification of austenite

grain boundaries by chemical etching for the microstructural analysis of quenched samples.The steels

were divided into 4 groups to distribute the work between the partners. The allocation of these groups

is shown in Table 2 and the nominal compositions of the steels in Table 1.

Table 2: Allocation of steels studied between the project partners

Group Steel types Partners

A Mn, Mn+Nb AM, Tata

B Si, Si+Nb CRM

C Al, Al+Nb CEIT

D Nb verification Tata, AM

Table 3: Measured cast compositions of project steels (wt%)

Partner Name C Si Mn P S Cr Mo Ni Cu Al N Nb Ti

AM C1Mn2 0.099 0 1.96 0.024 0.003 0.026 0.0055 0

C1Mn1Nb7 0.099 0 0.98 0.022 0.002 0.031 0.004 0.069

C1Mn2Nb7 0.096 0 2.10 0.022 0.003 0.026 0.005 0.070

C1Mn2Nb3 0.095 0 1.95 0.023 0.002 0.025 0.0055 0.032

Tata C1Mn1 0.110 0.230 0.99 0.002 0.001 <.005 <.005 <.005 <.005 0.034 0.0060 <.001 0.001

C1Mn1Nb3 0.105 0.230 0.99 0.002 0.001 <.005 <.005 <.005 <.005 0.031 0.0060 0.028 0.001

C1Mn1Nb1 0.105 0.230 1.00 0.002 0.001 <.005 <.005 <.005 <.005 0.030 0.0060 0.009 0.001

C2Mn1Nb3 0.205 0.230 1.02 0.002 0.001 <.005 <.005 <.005 <.005 0.032 0.0049 0.029 0.001

CEIT C2Mn2Al1 0.210 0.010 2.04 0.018 0.001 <.005 <.005 <.005 <.005 1.060 0.0050 0.001 0.001

C2Mn2Al2 0.200 0.020 1.99 0.018 0.001 <.005 <.005 <.005 <.005 2.010 0.0050 0.001 0.001

C2Mn2Al2Nb3 0.205 0.010 2.03 0.018 0.001 <.005 <.005 <.005 <.005 2.020 0.0047 0.030 0.001

C2Mn2Al2Nb7 0.220 0.020 2.08 0.020 0.001 <.005 <.005 <.005 <.005 2.110 0.0070 0.071 0.001

C2Mn2 0.195 0.011 1.98 0.019 0.001 <.005 <.005 0.007 <.005 0.028 0.005 0.001 0.0047

C2Mn2Al1Nb3 0.205 0.021 1.97 0.018 0.001 0.006 <.005 <.005 0.02 0.88 0.0036 0.028 0.0013

CRM C2Mn2Si1 0.193 0.949 2.02 0.022 <0.001 0.018 0.017 0.084 0.032 0.018 0.0062 0.003 0.002

C2Mn2Si2 0.189 2.005 2.08 0.023 0.001 0.016 0.017 0.010 0.008 0.025 0.0049 0.003 0.003

C2Mn2Si2Nb3 0.202 2.134 2.13 0.024 <0.001 0.017 0.016 0.012 0.006 0.023 0.0047 0.030 0.003

C2Mn2Si2Nb7 0.189 2.00 2.07 0.021 <0.001 0.015 0.016 0.008 0.009 0.032 0.0045 0.065 0.003

C2Mn2Nb3 0.181 0.023 1.95 0.018 <0.001 0.017 <0.005 0.014 0.012 0.015 0.033 0.003

Each partner cast their own steels for study by vacuum induction melting, except CEIT whose steels

were provided by Tata. Steel C2Mn2 is an additional cast that was requested at the 2nd

project meeting

20

to provide a link between the 0.1 and 0.2 wt% C steels with 2 wt% Mn and 0.03 wt% Al. Steel

C2Mn2Al1Nb3 was produced in April 2011 after results on the 2 wt% Al steels showed that the ferrite

transformation was interacting with the effect of Nb on the recrystallisation and precipitation. This

steel contains only 1 wt% Al and therefore has a lower ferrite transformation temperature, so that the

effect of Nb on the softening can be separated from the transformation softening. Similarly, an

additional cast, C2Mn2Si1Nb3, with 1 wt% Si rather than 2 wt% Si was made by CRM to get a clearer

picture of the interaction between Si and Nb. The complete measured cast analyses are given in Table

3.

2.3.2.2 Task 2.2: Laboratory rolling

The cast ingots were further processed, to refine the as-cast microstructure and homogenise the grain

size distribution and to produce material of suitable gauge for subsequent machining of

thermomechanical test specimens for WP3.

Tata reheated and hot rolled ten ingots on their laboratory reversing plate mill from the cast thickness

of 145mm down to plates of 25mm gauge, 150mm wide and approximately 1500mm long, followed by

air cooling. 100 cylindrical uniaxial compression specimens for the Gleeble 3800 tests were machined

from the longitudinal direction in each of the 4 Tata plates, of dimension 8mm diameter and 16mm

long. Six plates were sawn into 500mm lengths and supplied to CEIT as specified above. Torsion

specimens were machined by CEIT from these plates. Material from steel C2Mn1Nb3 was supplied to

the other project partners for the round robin tests and a sample of C1Mn1Nb3 was also supplied to

CEIT for multipass torsion testing.

From the as-cast blocks of dimensions 130 x 240 x 220mm of the CRM steels, eight blocks of

dimensions 55mm (thickness) x 70mm (length) x 220mm (width) were machined. Blocks were then

reheated to 1250°C for 1 hour to assure complete dissolution of niobium in the austenite phase. After

reheating, blocks were directly hot rolled on the CRM pilot rolling line to a final thickness of 12mm in

7 rolling passes. After rolling, the plates were cooled under natural air conditions and finally machined

into torsion specimens. Around 24 torsion samples were extracted per plate.

The four 15kg ingots cast at AM, of dimensions 60x125x240mm were subsequently hot rolled to

15mm (FRT<950°C) and air cooled in order to eliminate the solidification structures and reach a

homogenous microstructure for further machining of test samples. From these laboratory rolled strips,

hot torsion test samples (φ6mm and L50mm) were machined

2.3.2.3 Task 2.3: Provision of industrial material

Tata Steel obtained a sample of a typical commercial Nb microalloyed slab from their plate mills,

which was used for validation rolling trials on the pilot plate mill in WP6. The slab was sawn into

blocks of size 140 x 140 x 400 mm in preparation for rolling. The chemistry of the steel was 0.11C,

0.36Si, 1.38Mn, 0.034Nb wt%. This is similar to the laboratory cast project steel C1Mn1Nb3 but with

slightly higher Mn and Nb content and thus provided a good test of the validity of the models

developed within the project on an industrial plate steel.

2.3.3 WP3: Thermomechanical testing

The objectives of this work package were:

• To determine the effect of solute elements (Mn, Si, Al) on the kinetics of:

o Recovery

o Static recrystallisation

o Dynamic recrystallisation

o Strain induced precipitation of Nb

21

• To determine the effect of steel composition, temperature and interpass time on austenite grain

growth kinetics after recrystallisation

• To determine the interaction between recrystallisation and precipitation as a function of

composition, temperature, strain, strain rate and interpass time to generate data for modelling

and processing maps

• To determine the critical temperatures for recrystallisation (RST and RLT)

2.3.3.1 Task 3.1: Definition of test programme

The thermomechanical test techniques applied at each of the partners comprised uniaxial compression

(Tata, AM) and hot torsion (AM, CEIT, CRM). Different types of tests were applied to try to separate

recovery, recrystallisation and precipitation effects, including single hit, double hit, multi-hit and stress

relaxation. Hot torsion allows several types of test to be performed to study both static and dynamic

recrystallisation phenomenon. The matrix of tests was designed to determine the main coefficients to

adjust the hot rolling models of the partners. Systematic variations in parameters such as strain, strain

rate, initial austenite grain size and deformation temperature were considered to study static

recrystallisation, dynamic recrystallisation and niobium precipitation.

A first series of tests was performed by all partners to make a comparison set of data between the

different steel compositions. The tests used the core parameters (in bold) from Table 4 and one

austenite grain size chosen from tests to determine the initial (reheated) grain size before the

deformation. Additional parameters that have been studied by individual partners are indicated in the

final column. More details of the tests performed are given in the sections below.

Table 4: Parameters for initial thermomechanical tests performed by all partners

parameter values comments

Strain rate (s-1) 1

0.1, 5, 10 Tata

Strain 0.1, 0.2, 0.35, 0.7 0.05, 0.1, 0.075, 0.15 Tata;

0.5, 0.7 AM, CRM, CEIT

Temperature (°C) 850, 950, 1050, 1100/1150 850 AM; 1100/1150 CEIT, Tata

Austenite grain size Small, medium, large ~60µm, ~100µm, ~200µm

Additionally, a matrix of tests was also designed to perform round robin tests between the partners in

order to compare results obtained from the different thermomechanical simulation techniques used in

the MICROTOOLS project. These are described in Task 3.2.

Test programme: static recrystallisation study

Tata carried out a large matrix of uniaxial compression tests on the Gleeble 3800 thermomechanical

simulator on the 4 Tata steels. Sheets of tantalum foil were used between the anvils and the specimen

to minimise barrelling of the cylindrical samples. The stress relaxation technique was used to follow

the progress of softening after the final deformation by keeping the position of the anvils fixed with the

load still applied, for a pre-determined time, before the sample was water quenched to room

temperature to study the austenite grain size. The load decay was monitored and used to calculate the

softening kinetics. The applied interpass and stress relaxation times were estimated by calculating the

time for 95% recrystallisation and for 5% Nb precipitation using the existing Tata Steel hot rolling

model (see WP5). The aim was to allow the austenite to fully recrystallise (where possible) and then

quench to preserve the austenite grain size after recrystallisation but prior to (significant) grain growth.

Later tests used longer stress relaxation times to capture the complete softening curve. The quenched

samples were tempered at 500°C for 5 minutes to enhance the prior austenite grain boundaries. After

cooling they were sectioned along the deformation axis and examined metallographically to measure

the (recrystallised) austenite grain size after each test condition (see WP4).

Firstly, tests were carried out to determine the initial austenite grain size after reheating at a rate of

40°C/s to 1250°C, holding for 15 minutes and then water quenching to martensite. Further tests were

22

then performed to generate different initial austenite grain sizes, using different reheating temperatures

and/or single deformations of 0.2 strain at temperatures of 1150 and 1100°C. A “medium” grain size of

approximately 100µm was achievable in all four steels. The treatments used to obtain different initial

austenite grain sizes are shown in Table 5, including the conditions for obtaining smaller (~50µm) and

larger (~200µm) grain sizes.

Table 5: Austenitising conditions and corresponding measured austenite grain sizes in Tata steels.

Grain size

Steel

Reheat

temp

(°C)

Reheat

time

(mins)

Deform

temp

(°C)

Strain

(-)

Strain

rate

(/s)

interpass

time

(s)

Average

microns

ASTM

1250 15 - - - - 190 1.5

1150 10 - - - - 48 5.5 C1Mn1

1200 15 - - - - 104 3.0-3.5

1280 30 - - - - 226-190 1.0-1.5

1280 15 1150 0.2 1 50 34-40 6.0-6.5 C1Mn1Nb3

1280 30 1150 0.2 1 50 113 3

1250 15 - - - -

160 -

134 2.0-2.5

1250 15 1150 0.2 1 50 95 3.5 C1Mn1Nb1

1250 15 1100 0.2 1 30 48 5.5

1250 15 - - - -

226 -

190 1.0-1.5

1250 15 1150 0.2 1 50 95 3.5 C2Mn1Nb3

1250 15 1100 0.2 1 15 28 7

The initial series of uniaxial compression tests, based on Table 4, was completed on steels C1Mn1,

C1Mn1Nb3, C1Mn1Nb1 and C2Mn1Nb3 in the first half of the project, to investigate the static

recrystallisation kinetics of the different chemistries at one austenite grain size (~100µm) and three

temperatures (1150, 1050, 950°C) and three strains (0.1, 0.2, 0.35), Table 6 (green cells). A strain rate

of 1s-1 was used for all the tests unless stated otherwise.

In the second half of the project, the test matrix on all 4 steels was expanded to investigate additional

conditions and to generate data for the modelling activities in WP5, as follows (Table 6):

• strains of 0.05, 0.075 and 0.15 at deformation temperatures of 1050°C and 1150°C (yellow

cells), to investigate the recrystallisation kinetics at low strains relevant to plate mill rolling

• larger and smaller austenite grain sizes, with a strain of 0.2 at 1050°C (orange cells)

• additional strain rates of 0.1, 5 and 10/s, with a strain of 0.2 at 1050°C (bold text)

• additional temperatures of 1000 and 1100°C, with a strain of 0.35 (blue cells)

• selected tests were repeated, with optimised PID settings on the Gleeble and longer stress

relaxation times to ensure complete softening had occurred where possible

• double hit tests were performed on steel C2Mn1Nb3 for the round robin exercise

Figure 3 shows a schematic of the thermomechanical treatment applied in the tests. A cooling rate of

5°C/s was used between the reheating temperature and the deformation temperature. The samples were

held for 30s at the deformation temperature to allow the temperature to stabilise in the sample before

starting the deformation test.

To study the effect of austenite grain size on static recrystallisation kinetics in the Si series of steels, a

first set of trials was performed by CRM to generate different initial austenite grain sizes using

different reheating and roughing deformation conditions. Deformation levels of 0.3 and 0.5 at 1150°C

followed by different holding times after the deformation were tested to produce small, medium and

large austenite grains. Several hot torsion tests were performed according to thermomechanical

treatments GS1, GS2 and GS3 given in Figure 4 where the dashed arrow refers to water quench cooling

conditions.

23

T

em

pera

ture

Time

1200-1280°C

900-1800s1150°C

ε=0.2

Stress relaxation

quench

Tdef= 1150, 1050, 950°C

ε = 0.1, 0.2, 0.35

Austenite Strain

grain size rate (°C/s)

Small

~50µm

0.05 1150 1050 1

0.075 1050 1

Medium 0.1 1150 1050 950 1

~100µm 0.15 1150 1050 1

0.2 1150 1050 950 1, 0.1, 5, 10

0.35 1150 1100 1050 1000 950 1

Large

~200µm

Strain Temperature (°C)

0.2 1050

0.2

1

1050 1

Figure 3: Schematic diagram of the

thermomechanical treatments applied in the

Gleeble static recrystallisation tests.

Table 6: Matrix of static recrystallisation test conditions

for Tata steels Green cells = initial tests; Yellow cells = strain variations;

Orange cells = austenite grain size variation; Blue cells =

additional temperatures; Bold text = strain rate variation

Figure 4: Initial austenite grain size tests

at CRM

Table 7: Test programme - SRX study at CRM

The SRX kinetics were studied using the interrupted hot torsion technique that allows performing

several double hit tests on one sample. For each steel grade, softening kinetics were obtained according

to the work-plan summarized in Table 7 and which was designed to minimize the number of trials. The

effect of austenite grain size, deformation temperature and strain on SRX kinetics was initially planned

to be investigated. However, due to difficulties to obtain small and medium grain size for the Si steel

grades of Table 3, the grain size effect was disregarded and only large grain size was considered, see

Task 4.2. The grain size effect was considered to be the one described by StripCam equation as default

value, see Task 5.1. Furthermore, in the initial work plan, it was scheduled to study a strain of 0.7

instead of 0.5 but the first tests revealed that applying a strain of 0.7 initiated dynamic recrystallisation

for steels containing no niobium. For that reason, a strain of 0.5 instead of 0.7 was considered.

Figure 5 shows the thermomechanical treatment applied on torsion specimens to study SRX kinetics.

Using the interrupted torsion test technique as shown, three conditions per torsion specimen can be

tested. The first deformation applied at the reheating temperature (1250°C) was used to normalize the

grain size before the reheating stage in order to produce constant reheating conditions (i.e. austenite

grain size) from sample to sample. Then, the intensity of the deformation (εgrain size) and the time

between the deformation and the next temperature plateau are used to control the size of the austenite

grain (see Task 4.2). εtest and the testing temperatures correspond respectively to values of 0.2, 0.35, 0.7

and 950°C, 1000°C, 1050°C.

The softening kinetics were obtained from stress-strain curves of the two step deformation test using

the back extrapolation method (see Task 3.2). Some of the results were also obtained with the 2%

offset method for comparison with the back extrapolation one.

24

Figure 5: Interrupted torsion test technique - Double hit tests

CEIT carried out single-hit, double-hit and multipass torsion tests with the C2Mn2, C2Mn2Al and

C2Mn2AlNb steels in order to investigate the effect that Al addition has on the static softening

behaviour of C-Mn steels. Both the solute drag exerted by Al and the effect of Al on Nb(C,N) strain-

induced precipitation were considered. Before the torsion tests, in all the cases the specimens were

soaked at a temperature of 1250ºC during 15 min in the induction furnace attached to the torsion

machine. In order to investigate the microstructure obtained before the tests, specimens were quenched

directly after the reheating treatment following the thermal cycle shown in Figure 6. The austenite

grain sizes measured in each of the cases have been included in Table 8. In the 2%Al steels

(C2Mn2Al2, C2Mn2Al2Nb3, C2Mn2Al2Nb7) a small amount of ferrite was also found present in the

quenched specimens (further analysis in WP4). This can be attributed to the high Al content of these

steels. The strong ferrite stabiliser effect of Al has also been reported in other works [1,2]. However,

the amount of ferrite present in the specimens was small, less than 5% for the C2Mn2Al2 steel and less

than 1% for the C2Mn2Al2Nb steels, and therefore, it was not expected to affect the austenite

softening evolution after deformation.

1250ºC 900s

1-10ºC/s

1ºC/s

Time (s)

Temperature(ºC)

1250ºC 900s

ε1 ε=0.1

tip1-10ºC/s

Quenching(optional for

microestructuralanalysis)1ºC/s

Time (s)

Temperature(ºC)

Figure 6: Thermal cycle for the initial

microstructure characterisation at CEIT

Figure 7: Thermomechanical cycle applied in

the double-hit torsion tests at CEIT

The softening behaviour of these materials was analysed by the double-hit torsion technique. The

thermomechanical cycle employed in the tests is shown in Figure 7. After the soaking treatment, the

specimens were cooled down to the selected deformation temperature. Once the temperature was

stabilised, the specimens were strained up to ε=0.2-0.35, immediately unloaded and held for increasing

times. Following this, a second deformation pass of ε=0.1 was applied. In all the tests a strain rate of 11 −= sε& was used. The deformation conditions employed in the tests are summarised in Table 8.

In all deformation conditions one specimen was water quenched after the soaking treatment in order to

analyse the initial microstructure. Measured initial grain sizes are also indicated in Table 8. In addition,

several specimens were water quenched just before reloading to analyse the microstructure present

after different holding times. The quenching treatments were carried out to characterise the

recrystallised microstructure, the phases present after deformation or to investigate the strain-induced

precipitation evolution. For the microstructure characterisation different microscopy techniques such as

Optical Microscopy (OM), Scanning Electron Microscopy (SEM) and Transmission Electron

Microscopy (TEM) were employed. The most relevant quenching treatments performed are listed in

25

Table 9, together with the microstructural characterisation investigations carried out in each of the

cases.

Table 8: Deformation conditions employed in the double-hit torsion tests on Al steels ( 11 −= sε& ).

Steel Soaking

Temperature (ºC) Dγ0 (µm) TDef (ºC) ε

C2Mn2 69±4 1065, 965, 925 0.35

1065 0.2 C2Mn2Al1 100±3

1065, 965, 925 0.35

1065 0.2 C2Mn2Al2 65±1

1065, 1000, 965, 925 0.35

C2Mn2Al1Nb3 102±5 1065, 1000, 925, 900 0.35

C2Mn2Al2Nb3 65±4 1065, 1000, 925, 925 0.35

C2Mn2Al2Nb7

1250

56±2 1065, 1000, 965, 925 0.35

Table 9: Quenching treatments carried out for microstructural analysis and strain-induced precipitation

study on Al steels.

Microstructural analysis

Steel Dγ0 (µm) Tdef

(ºC) tip (s) εεεε Recrystallised

microstructure Others

Nb (C,N)

precipitation

analysis

1065 56 0.2

1065 22 C2Mn2 69±4

925 77 0.35

133 0.2

2

5 1065

29

C2Mn2Al1 100±3

925 178

0.35

1065 553 0.2

1065 63

1000 58 0.35

X

C2Mn2Al2 65±1

925 270, 404, 2400, 10200 0.35 X

1065 65 X

1000 384

925 96, 288, 960, 4800 C2Mn2Al1Nb3 102±5

900 96, 960, 5760

0.35 X

1065 144 X

1000 576

965 384 C2Mn2Al2Nb3 65±4

925 672, 2016, 5760

0.35 X X

1065 240 X

1000 576

965 384, 5760 C2Mn2Al2Nb7 56±2

925 672, 5760

0.35 X X

Double-hit torsion tests and quenching treatments were also carried out with the Tata C2Mn1Nb3 steel

at the lowest temperatures investigated (925-900ºC). The aim was to compare the softening and

precipitation behaviour with the results obtained for the C2Mn2Al1Nb3 steel, in order to evaluate the

effect of Al on strain-induced precipitation. The thermomechanical cycle employed in the tests is the

same employed for the rest of the steels (Figure 7) and the conditions selected for the study are

summarised in Table 10.

26

Table 10: Double-hit torsion tests and quenching treatments carried out on C2Mn1Nb3 to study the

effect of Al on strain-induced precipitation.

Steel Dγ0 (µm) TDef (ºC) ε

925, 900 0.35

TDef (ºC) tip (s)

925 58, 4800 C2Mn1Nb3 87±4

900 96, 5760

At ArcelorMittal, isothermal Double Hit tests were performed in a torsion machine using the

technique of ‘testing in series’ by which consecutive cycles of reheating and double deformation tests

are applied on a single sample in order to optimise the use of material (also applied by CRM, Figure 5).

Table 11 presents the selected conditions for testing the materials in terms of initial grain size,

deformation temperature, applied strain and strain rate and interpass times taking as a reference the

study of static recrystallization kinetics in these steels.

Table 11: Selected Conditions for Thermomechanical Testing

Grade Temperature

(°C) Strain

Initial Grain

Size (µm)

Strain Rate

(1/s)

Interpass

Times (s)

C1Mn2 950, 1000, 1050 0,2, 0,35, 0.5 100, 200 1 0.5-100

C1Mn2Nb3 950, 1000, 1050 0,2, 0,35, 0.5 100, 200 1 0.5-100

C1Mn1Nb7 950, 1000, 1050 0,2, 0,35, 0.5 100 1 0.5-100

C1Mn2Nb7 950, 1000, 1050 0,2, 0,35, 0.5 100, 200 1 0.5-100

The tests involved initially a reheating step at a temperature of 1200°C in order to ensure the presence

of the nominal Nb content in solid solution and a high temperature deformation step introduced for

reaching the initial grain size targets by recrystallization of the coarse reheated microstructure. In order

to avoid any precipitation of Nb this deformation step was performed at 1150°C. Two levels of strain

were applied at 1150°C for grain refinement, ε=0.3 and ε=0.8. In order to verify the absence of NbC

precipitation prior to the double hit tests, quenched samples were obtained for high Nb material

C1Mn2Nb7 just after reheating at 1200°C and after deformation at 1150°C with a high strain (e=0.8)

and cooling down to 1050°C. On these quenched samples, the NbC precipitation rate was determined

by electrolytic dissolution and Inductive Coupled Plasma (ICP) spectroscopy as described in Task 4.3.

6 and 8ppm of precipitated Nb were determined for the reheated and reheated and deformed samples,

respectively, thereby validating the design proposed for the double hit tests.

In order to characterize the austenite grain size for the isothermal double hit tests and to approach the

targets of 100 and 200µm a series of hot torsion tests were performed in each of the steel grades

involving reheating, high temperature (1150°C) deformation and cooling at 5°C/s down to 1050°C

followed by water quenching. Samples for metallographic analysis were extracted from torsion samples

and this analysis was performed on a longitudinal section corresponding to the subsurface (depth

~200µm) of the torsion sample, a section in which the thermomechanical conditions applied are

representative of the target conditions of the test. The results are presented fully in WP4.

Table 12 presents the results of the quantitative analysis showing that for an applied roughing strain of

0.8 the mean grain size closely approached the target with values of 124 and 128µm for C1Mn2 and

C1Mn2Nb3 respectively. Reducing the roughing strain to 0.3 induced larger mean grain sizes in the

microstructures however they remained far from the target of 200µm with values of 161 and 138µm for

C1Mn2 and C1Mn2Nb3 respectively. The applied deformation with strain 0.8 similarly led to mean

grain size values approaching the target of 100µm as values of 128 and 108µm were determined for

C1Mn1Nb7 and C1Mn2Nb7 respectively. For 0.3 roughing strain applied to C1Mn2Nb7 the

microstructures were heterogeneous and a large dispersion of grain size values was observed with a

mean value exceeding the target and reaching 271µm. Despite these observations, the applied strain of

0.3 at high temperature was retained for the experimental programme.

27

Table 12: Initial austenite grain size measurements (Mean Linear Intercept) for MnNb steels

Grade C1Mn2 C1Mn2Nb3 C1Mn1Nb7 C1Mn2Nb7

Roughing strain 0.3 0.8 0.3 0.8 0.8 0.3 0.8

Geometric MLI (µm) 161.7 123.8 137.9 126.7 128.4 271.2 107.9

Test programme: dynamic recrystallisation study

At CRM and AM, experiments were performed by single hit hot torsion to study the effect of Si and

Mn on critical and peak strains for dynamic recrystallisation. Torsion tests were performed for several

conditions of deformation temperatures and strain rates. A total single deformation of at least 2.0 was

applied on each specimen following the thermomechanical treatment given in Figure 8. The complete

matrix of tests at CRM is given in Table 13. The testing at AM was carried out on grades C1Mn1Nb7

and C1Mn2Nb7 at testing temperatures of 1000, 1050 and 1100°C and strain rates of 0.1 and 1/s, as the

maximum strain rate achievable in the current torsion machine set up at AM does not exceed 3.6/s. The

method used to analyse flow stress curves, based on the second derivative, is presented in Task 3.3.

Table 13: Matrix of tests - DRX study at CRM Figure 8: Single hit hot torsion test for DRX

study

Test programme: niobium precipitation study

Task 3.5 aimed to study the effect of silicon on niobium precipitation kinetics. Single hit hot torsion

tests were performed on steel grade C2Mn2Nb3 and C2Mn2Si2Nb3 to evaluate the influence of 2%Si

on Nb precipitation. The precipitation kinetics were determined for one condition of deformation

temperature (Tdef = 1000°C) and deformation level (strain = 0.2). Torsion specimens were water

quenched 10s, 100s, 1000s and 10000s after the deformation. For statistical reasons, three samples per

condition were tested. Furthermore, three additional samples were quenched just before the

deformation in order to obtain the initial precipitation state. A schematic of the thermomechanical

treatment is given in Figure 9.

Figure 9: Single hit hot torsion test for Nb precipitation analysis at CRM

28

Similar single hit tests were performed on steels C1Mn1Nb7 and C1Mn2Nb7 to evaluate the effect of

Mn on the Nb precipitation behaviour at temperatures of 1050, 1000 and 950°C with an applied

strain of 0.35.

Test programme: determination of critical temperatures

Task 3.6 aimed to determine critical temperatures for recrystallisation in order to define the regimes

where recrystallisation is complete between passes, partially complete or not possible. Multi-hit hot

torsion tests were performed to determine critical recrystallisation temperatures like the no-

recrystallisation temperature (Tnr), the recrystallisation limit temperature (RLT) and the

recrystallisation stop temperature (RST). Torsion specimens were first reheated to 1250°C for 5 min to

have all Nb in solid solution. Subsequently, samples were subjected to a series of consecutive

deformations (see Figure 10) for different conditions of deformation, inter-pass time and cooling rate,

which are summarised in Table 14.

Figure 10: Multi-pass deformation test

to determine critical temperatures

Table 14: Matrix of tests - Critical recrystallisation

temperatures of Si steels

The mean flow stress analysis coupled to the anisothermal softening fraction concept was applied to

stress strain curves of the multipass deformation test to obtain the critical recrystallisation

temperatures. The method is described in Task 3.6.

Multipass torsion tests were carried out on the Al series of steels in order to investigate the

microstructural evolution of the specimens during multiple deformation schedules. The

thermomechanical treatment employed in the tests is summarised in Figure 11. After the reheating

treatment (1250ºC, 15 min) twenty deformation passes were applied at continuous cooling conditions at

temperatures ranging from 1180 to 800ºC. The strain per pass, ε=0.3, and the strain rate, 1s-1, were kept

constant in all the tests, and interpass times ranging from 5 to 100 s were employed. The deformation

conditions employed in the tests are summarised in Table 15. In some of the tests the specimens broke

during the deformation schedule, and as a result the test could not be completed. This has also been

indicated in the table.

1ºC/s

1250ºC 900s

Time (s)

Temperature(ºC)

Tdef1 =1180ºC

ε=1s-1.

ε, Npass, tip

20 deformation passes

20ºC temperature drop per pass

Steel ε tip

(s)

Vcooling

(ºC/s)

Specimen

broken during

test

5 4 C2Mn2Al2Nb3,

C2Mn2Al2Nb7

30 0.67

C2Mn2Al2,

C2Mn2Al2Nb3,

C2Mn2Al2Nb7

C2Mn2

C2Mn2Al1

C2Mn2Al2

C2Mn2Al1Nb3

C2Mn2Al2Nb3

C2Mn2Al2Nb7

0.3

100 0.2

Figure 11: Thermomechanical cycle

applied in the multipass deformation tests.

Table 15: Deformation conditions employed in the

multipass torsion tests ( 11 −= sε& ).

29

Several specimens were water quenched at different stages of the multipass torsion tests in order to

investigate the microstructural evolution mechanisms occurring in each case. The quenching treatments

were carried out at temperatures close to the non-recrystallisation (Tnr) and γ→α phase transformation

start (Ar3) temperatures. The selected conditions are summarised in Table 16.

Table 16: Quenching treatments carried out in order to investigate the microstructural evolution of the

steels investigated during the multipass torsion tests.

Steel ε Number of

passes

Tip (s) after

the last pass TQuench (ºC) Tnr (ºC) Ar3 (ºC)

8 5 1020

13 5 920 1056 920

12 30 940 1067 940 C2Mn2Al2

13 100 920 1064 920

C2Mn2Al1Nb3 9 30 1000 1029

10 100 980 C2Mn2Al2Nb3

13 100 920 1022 920

C2Mn2Al2Nb7

0.3

8 30 1020 1065 940

2.3.3.2 Task 3.2: Solute drag effect on static recrystallisation kinetics

This activity was the main focus of the work for all partners in the project. CEIT concentrated on

studying the effect of Al, CRM on the effect of Si, whilst Tata and AM investigated the effects of Nb

and Mn at different levels.

Effect of Nb

The results of the matrix of uniaxial compression tests carried out by Tata Steel using stress relaxation

to follow the progress of softening after deformation are presented in this section. The fraction softened

after the deformation was determined from the stress relaxation curves using the approach described by

Karjalainen, Figure 12 [3,4]. The softening curve (stress versus log(time)) is considered to show three

distinct regions: (i) a linear region with a slow decrease in stress, corresponding to creep and recovery,

(ii) a rapid decrease in stress, due to recrystallisation processes, and (iii) a second linear region with a

slow or zero decrease in stress, corresponding to stress relaxation of the fully softened austenite by

creep or grain growth. If it is assumed that a partially softened austenite consists of a mixture of work-

hardened and fully softened austenite, of stresses σ1 and σ2 respectively, then by applying an equi-

strain law of mixtures, the stress σ of the mixture at time t can be given by:

( )( ) ( ))log()log(1 2211 tXtX ασασσ −+−−= (1)

where X is the fraction of recrystallised austenite and α1 and α2 are the gradients of the tangents to the

start and end of the curve, respectively.

30

0

10

20

30

40

50

60

70

80

0.01 0.1 1 10 100

Time (s)

Str

ess (

MP

a)

0

0.2

0.4

0.6

0.8

1

Fraction re

crystallis

ed

σ=σ1−α1 log(t)

σ=σ2−α2 log(t)

(i) (ii) (iii)

Figure 12: Schematic illustration of method for analysing stress relaxation curves (after [3,4]).

Fraction recrystallised plotted in red on 2nd

y-axis.

The time for 50% recrystallisation, t50, was determined from the softening curves for each of the stress

relaxation tests. The recrystallisation time was measured from the start of region (ii) in Figure 12. The

sigmoidal form of the softened fraction curve can be described by an Avrami relationship of the type:

−−=

n

t

tX

50

693.0exp1

(2)

where X is the fraction recrystallised corresponding to a time t. The Avrami coefficient n can be

determined from the gradient of a plot of log[-ln(1-X)] versus log time.

Table 17 and Table 18 summarise the t50 and n values determined from the stress relaxation curves for

the C1Mn1, C1Mn1Nb1, C1Mn1Nb3 and C2Mn1Nb3 steels, investigating the effect of strain and

temperature and strain rate, respectively. Tests highlighted in grey either did not fully recrystallise in

the time allowed for relaxation, and therefore no t50 and n value could be derived, or the curves

indicated that recovery might be occurring rather than recrystallisation, with a lower gradient of the

curve and n values much less than 1. Recrystallisation did not occur or was not completed in many of

the tests at 950°C, particularly at lower strains and with increasing Nb content. The curves from the

0.05 strain tests at 1150°C in all steels, at 1050°C in C1Mn1, and the 0.1 strain tests in the 0.03 wt%

Nb steels also showed evidence that recovery was the dominant softening mechanism. The curves for

the 0.075 and 0.05 strain tests at 1050°C had similarly long t50 times but it was less clear that recovery

was occurring instead of recrystallisation. The 0.2 strain tests at 1100 and 1000°C were only performed

on steel C1Mn1.

Figure 13 shows the stress relaxation curves for the series of tests performed on the four steels with

different amounts of strain applied at 1050°C, from an initial austenite grain size of ~100µm. In all of

the steels, the initial stress and the rate of softening increased as the applied strain increased from 0.05

to 0.35. The curves at 0.35, 0.2 and to a lesser extent 0.15 strain showed a steep drop in stress with

increasing relaxation time, consistent with the occurrence of recrystallisation. However, the curves at

the lowest strains, between 0.05 and 0.1, did not always show this steep drop in stress and therefore

probably only recovery was occurring in some cases.

31

Table 17: t50 and n values determined from fitting Avrami curves to softened fraction data: effect of

strain and temperature at strain rate of 1/s and 100µm initial austenite grain size

n t50 n t50 n t50 n t50

0.35 0.86 0.09 0.92 0.13 1.06 0.30 0.97 0.18

0.2 1.11 0.22 1.01 0.39 0.97 0.45 0.99 0.32

0.15 1.29 0.49 1.09 0.70 1.28 1.00 0.91 0.90

0.1 1.11 0.63 1.10 1.37 1.10 2.64 0.71 0.72

0.05 1.10 12.86 1.07 39.98 0.70 11.29

0.35 0.88 0.09 1.04 0.38 1.14 0.50 1.20 0.54

0.2 1.03 0.32

0.35 1.06 0.22 1.22 0.75 1.14 0.96 1.30 0.96

0.2 1.22 0.61 1.25 1.32 1.25 2.22 1.27 2.74

0.15 1.28 0.97 0.99 3.01 1.03 2.93 1.07 3.59

0.1 1.29 2.29 1.39 4.79 0.77 8.21 0.59 9.51

0.075 1.31 6.59 1.01 9.16 1.08 6.53 1.46 6.57

0.05 1.19 7.20 1.15 4.45 0.92 8.39

0.35 1.36 0.47 1.05 0.98 1.32 2.91 0.59 1.17

0.2 0.95 0.95

0.35 1.16 0.89 1.10 4.97 0.56 5.99

0.2 1.40 1.73 0.72 8.60

0.1 1.60 11.63

C1Mn1Nb1

950

1000

C1Mn1Nb3 C2Mn1Nb3

1150

1050

1100

T (°C) strainC1Mn1

Table 18: t50 and n values determined from fitting Avrami curves to softened fraction data: effect of

strain rate at 0.2 strain, 1050°C and 100µm initial austenite grain size.

n t50 n t50 n t50 n t50

0.1 0.991 0.502 1.06 2.353 1.164 5.375 1.076 1.549

1 1.218 0.607 1.245 1.324 1.249 2.22 1.272 2.74

5 1.058 0.445 1.372 1.222 1.195 2.895 0.97 2.11

10 1.438 0.621 1.122 1.459 1.442 2.49 1.198 2.041

1050

T (°C)Strain

rate (/s)

C1Mn1 C1Mn1Nb1 C1Mn1Nb3 C2Mn1Nb3

Figure 14 shows the Avrami curves derived from the stress relaxation data in Figure 13. The rate of

softening increased with increasing strain, as expected, and decreased with increasing Nb content. The

curve for 0.05 strain in steel C1Mn1 could not be fitted with an Avrami curve as the gradient of the

curve was very shallow and therefore recovery rather than recrystallisation appeared to be the primary

softening mechanism. There was uncertainty over the validity of the Avrami curves for 0.05 strain in

the three Nb steels as well for the same reasons, although it was possible to fit them.

Figure 15 shows the same data but where the softened fraction has been calculated based on the initial

stress after the deformation corresponding to zero softening and a stress of zero corresponding to fully

softened. The data was then “normalised” between the maximum stress and zero. This method of

analysis enables the tests to be compared avoiding the subjectivity in deciding where the start and

finish of recrystallisation occur in the stress relaxation curve. The analysis emphasised that the

softening behaviour was very similar for all the strains up to a softened fraction of about 0.4. Above

this fraction, a small plateau in the curve can be seen, the magnitude of which increased with

decreasing strain. The rate of softening then decreased with decreasing applied strain before the curves

converged again as the softened fraction approached one. The point at which the curves diverged at the

plateau seemed to correspond to the end of recovery/start of recrystallisation in the analysis of the

stress relaxation curves.

32

(a) C1Mn1, 1050°C

0

20

40

60

80

100

120

140

0.001 0.01 0.1 1 10 100 1000

Time (s)

Str

ess (

MP

a)

0.05 strain

0.075 strain

0.1 strain

0.15 strain

0.2 strain

0.35 strain

C1Mn1Nb1 1050°C

(b) C1Mn1Nb1, 1050°C

0

20

40

60

80

100

120

140

0.001 0.01 0.1 1 10 100 1000

Time (s)

Str

ess (

MP

a)

0.05 strain

0.075 strain

0.1 strain

0.15 strain

0.2 strain

0.35 strain

C1Mn1Nb3 1050°C

(c) C1Mn1Nb3, 1050°C

0

20

40

60

80

100

120

140

0.001 0.01 0.1 1 10 100 1000

Time (s)

Str

ess (

MP

a)

0.05 strain

0.075 strain

0.1 strain

0.15 strain

0.2 strain

0.35 strain

C2Mn1Nb3 1050°C

(d) C2Mn1Nb3, 1050°C

Figure 13: Stress relaxation curves for Tata steels deformed at 1050°C showing effect of strain

0.0

0.2

0.4

0.6

0.8

1.0

0.001 0.01 0.1 1 10 100 1000

Time (s)

Recry

sta

llised fra

ctio

n

0.075 strain

0.1 strain

0.15 strain

0.2 strain

0.35 strain

C1Mn1 1050°C

(a) C1Mn1, 1050°C

0.0

0.2

0.4

0.6

0.8

1.0

0.01 0.1 1 10 100 1000

Time (s)

Recry

sta

llised fra

ctio

n

0.05 strain

0.075 strain

0.1 strain

0.15 strain

0.2 strain

0.35 strain

C1Mn1Nb1 1050°C

(b) C1Mn1Nb1, 1050°C

0

0.2

0.4

0.6

0.8

1

0.001 0.01 0.1 1 10 100 1000

Time (s)

Recry

sta

llised fra

ctio

n

0.05 strain

0.075 strain

0.1 strain

0.15 strain

0.2 strain

0.35 strain

C1Mn1Nb3 1050°C

(c) C1Mn1Nb3, 1050°C

0.0

0.2

0.4

0.6

0.8

1.0

0.001 0.01 0.1 1 10 100 1000

Time (s)

Recry

sta

llised fra

ctio

n

0.05 strain

0.075 strain

0.1 strain

0.15 strain

0.2 strain

0.35 strain

C2Mn1Nb3 1050°C

(d) C2Mn1Nb3, 1050°C

Figure 14: Avrami recrystallisation curves for Tata steels deformed at 1050°C showing effect of strain

0

20

40

60

80

100

120

140

0.001 0.01 0.1 1 10 100 1000

Time (s)

Str

ess (

MP

a)

0.05 strain

0.075 strain

0.1 strain

0.15 strain

0.2 strain

0.35 strain

C1Mn1 1050°C

33

0.0

0.2

0.4

0.6

0.8

1.0

0.001 0.01 0.1 1 10 100 1000

Time (s)

Soft

ened f

raction

0.05 strain

0.075 strain

0.1 strain

0.15 strain

0.2 strain

0.35 strain

C1Mn1 1050°C

(a) C1Mn1, 1050°C

0.0

0.2

0.4

0.6

0.8

1.0

0.001 0.01 0.1 1 10 100 1000

Time (s)

Soft

ened f

raction

0.05 strain

0.075 strain

0.1 strain

0.15 strain

0.2 strain

0.35 strain

C1Mn1Nb1 1050°C

(b) C1Mn1Nb1, 1050°C

0

0.2

0.4

0.6

0.8

1

0.001 0.01 0.1 1 10 100 1000

Time (s)

Soft

ened fra

ction

0.05 strain

0.075 strain

0.1 strain

0.15 strain

0.2 strain

0.35 strain

C1Mn1Nb3 1050°C

(c) C1Mn1Nb3, 1050°C

0

0.2

0.4

0.6

0.8

1

0.001 0.01 0.1 1 10 100 1000

Time (s)

Softe

ned f

raction

0.05 strain

0.075 strain

0.1 strain

0.15 strain

0.2 strain

0.35 strain

C2Mn1Nb3 1050°C

(d) C2Mn1Nb3, 1050°C

Figure 15: “Normalised” softening curves for Tata steels deformed at 1050°C showing effect of strain

Figure 16 to Figure 17 show the recrystallized and softened fraction graphs plotted for the stress

relaxation tests performed at 1150°C. Most of the softening curves showed a sharp decrease in stress

with increasing time, consistent with recrystallisation. Only the tests at 0.05 strain showed a more

gentle gradient in stress relaxation, indicating that recovery may be occurring. The data from the test on

C1Mn1 at 0.05 strain was corrupted and could not be analysed. The time for recrystallisation was

shorter for a given strain at 1150°C compared with the tests at 1050°C. The difference in shape at the

start of some of the curves in Figure 17 is due to the corresponding abrupt start to the measured

relaxation kinetics at 0.35 strain and the (unintentional) use of a lower data acquisition frequency for

the tests at 0.1 and 0.2 strain in steel C2Mn1Nb3.

34

0

0.2

0.4

0.6

0.8

1

0.001 0.01 0.1 1 10 100 1000

Time (s)

Recry

sta

llised

fra

ction

0.1 strain

0.15 strain

0.2 strain

0.35 strain

C1Mn1 1150°C

(a) C1Mn1, 1150°C

0

0.2

0.4

0.6

0.8

1

0.001 0.01 0.1 1 10 100 1000

Time (s)

Recry

sta

llised

fra

ction

0.05 strain

0.1 strain

0.15 strain

0.2 strain

0.35 strain

C1Mn1Nb1 1150°C

(b) C1Mn1Nb1, 1150°C

0

0.2

0.4

0.6

0.8

1

0.001 0.01 0.1 1 10 100 1000

Time (s)

Recry

sta

llised

fra

ction

0.05 strain

0.1 strain

0.15 strain

0.2 strain

0.35 strain

C1Mn1Nb3 1150°C

(c) C1Mn1Nb3, 1150°C

0

0.2

0.4

0.6

0.8

1

0.001 0.01 0.1 1 10 100 1000

Time (s)

Recry

sta

llised

fra

ction

0.05 strain

0.1 strain

0.15 strain

0.2 strain

0.35 strain

C2Mn1Nb3 1150°C

(d) C2Mn1Nb3, 1150°C

Figure 16: Avrami recrystallisation curves for Tata steels deformed at 1150°C showing effect of strain

0

0.2

0.4

0.6

0.8

1

0.001 0.01 0.1 1 10 100 1000

Time (s)

So

fte

ne

d f

raction

0.1 strain

0.15 strain

0.2 strain

0.35 strain

C1Mn1 1150°C

(a) C1Mn1, 1150°C

0

0.2

0.4

0.6

0.8

1

0.001 0.01 0.1 1 10 100 1000

Time (s)

So

fte

ne

d f

raction

0.05 strain

0.1 strain

0.15 strain

0.2 strain

0.35 strain

C1Mn1Nb1 1150°C

(b) C1Mn1Nb1, 1150°C

0

0.2

0.4

0.6

0.8

1

0.001 0.01 0.1 1 10 100 1000

Time (s)

So

fte

ne

d f

raction

0.05 strain

0.1 strain

0.15 strain

0.2 strain

0.35 strain

C1Mn1Nb3 1150°C

(c) C1Mn1Nb3, 1150°C

0

0.2

0.4

0.6

0.8

1

0.001 0.01 0.1 1 10 100 1000

Time (s)

So

fte

ne

d f

raction

0.05 strain

0.1 strain

0.15 strain

0.2 strain

0.35 strain

C2Mn1Nb3 1150°C

(d) C2Mn1Nb3, 1150°C

Figure 17: “Normalised” softening curves for Tata steels deformed at 1150°C showing effect of strain

35

Figure 18 shows the softening curves plotted for the stress relaxation tests performed at 950°C. The

steels had slower softening kinetics at 950°C compared with the tests at 1050 and 1150°C. The curves

for the C1Mn1 steel indicate that recrystallisation was still occurring at all strains. In most of the tests

on the Nb steels, softening was not completed within the 1000s time allowed for the test and therefore

the data could not be fitted to Avrami recrystallisation curves. The shape of the curves in these tests

suggested that the primary softening mechanism was recovery rather than recrystallisation in the Nb

steels below 0.35 strain.

Figure 19 shows the effect of temperature on the softening kinetics at a fixed strain of 0.35 and a strain

rate of 1/s. Temperatures of 950, 1000, 1050, 1100 and 1150°C were investigated. The graphs show the

increase in the rate of softening with increasing temperature in all steels. At 950°C in the 0.03wt% Nb

steels, the gradient of the curves was much shallower, suggesting that recovery was occurring or

precipitation had started to slow down recrystallisation.

Figure 20 shows the effect of Nb on the recrystallisation curves at different levels of applied strain at a

temperature of 1050°C. At low strains (0.075), it was difficult to distinguish consistently between the

steels, due to the variation in measured stress relaxation curves and difficulty in analysing the curves

when they are dominated by recovery effects. At strains of 0.1 and above, the effect of Nb became

clearer, with softening retarded with increasing Nb content from zero to 0.03 wt%. No precipitation

was expected at this temperature (calculated using the models in Task 5.1) and so this retardation was

attributed to solute drag of Nb on austenite recrystallisation.

0

0.2

0.4

0.6

0.8

1

0.001 0.01 0.1 1 10 100 1000

Time (s)

Softe

ned

fra

ction

0.1 strain

0.2 strain

0.35 strain

C1Mn1 950°C

(a) C1Mn1, 950°C

0

0.2

0.4

0.6

0.8

1

0.001 0.01 0.1 1 10 100 1000

Time (s)

Softe

ned

fra

ction

0.1 strain

0.2 strain

0.35 strain

C1Mn1Nb1 950°C

(b) C1Mn1Nb1, 950°C

0

0.2

0.4

0.6

0.8

1

0.001 0.01 0.1 1 10 100 1000

Time (s)

Softe

ned

fra

ction

0.1 strain

0.2 strain

0.35 strain

C1Mn1Nb3 950°C

(c) C1Mn1Nb3, 950°C

0

0.2

0.4

0.6

0.8

1

0.001 0.01 0.1 1 10 100 1000

Time (s)

Softe

ned

fra

ction

0.1 strain

0.2 strain

0.35 strain

C2Mn1Nb3 950°C

(d) C2Mn1Nb3, 950°C

Figure 18: “Normalised” softening curves for Tata steels deformed at 950°C showing effect of strain

36

0

0.2

0.4

0.6

0.8

1

0.001 0.01 0.1 1 10 100 1000

Time (s)

Recry

sta

llised

fra

ction

950°C

1000°C

1050°C

1100°C

1150°C

C1Mn1 0.35 strain

(a) C1Mn1, 0.35 strain

0

0.2

0.4

0.6

0.8

1

0.001 0.01 0.1 1 10 100 1000

Time (s)

Recry

sta

llised

fra

ction

950°C

1000°C

1050°C

1100°C

1150°C

C1Mn1Nb1 0.35 strain

(b) C1Mn1Nb1, 0.35 strain

0

0.2

0.4

0.6

0.8

1

0.001 0.01 0.1 1 10 100 1000

Time (s)

Recry

sta

llised

fra

ction

950°C

1000°C

1050°C

1100°C

1150°C

C1Mn1Nb3 0.35 strain

(c) C1Mn1Nb3, 0.35 strain

0

0.2

0.4

0.6

0.8

1

0.001 0.01 0.1 1 10 100 1000

Time (s)

Recry

sta

llised

fra

ction

1000°C

1050°C

1100°C

1150°C

C2Mn1Nb3 0.35 strain

(d) C2Mn1Nb3, 0.35 strain

Figure 19: Avrami recrystallisation curves for Tata steels deformed at fixed strain showing effect of

temperature

0

0.2

0.4

0.6

0.8

1

0.001 0.01 0.1 1 10 100 1000

Time (s)

Recrystallised fraction

C1Mn1 0.075

C1Mn1Nb1 0.075

C1Mn1Nb3 0.075

C2Mn1Nb3 0.075

C1Mn1 0.2

C1Mn1Nb1 0.2

C1Mn1Nb3 0.2

C2Mn1Nb3 0.2

(a) 0.075 and 0.2 strain, 1050°C

0

0.2

0.4

0.6

0.8

1

0.001 0.01 0.1 1 10 100 1000

Time (s)

Recrystallised fraction

C1Mn1 0.1

C1Mn1Nb1 0.1

C1Mn1Nb3 0.1

C2Mn1Nb3 0.1

C1Mn1 0.35

C1Mn1Nb1 0.35

C1Mn1Nb3 0.35

C2Mn1Nb3 0.35

(b) 0.1 and 0.35 strain, 1050°C

Figure 20: Avrami recrystallisation curves for Tata steels deformed at 1050°C showing effect of Nb

content and strain

Figure 21 compares the normalised softening curves for different Nb contents at strains of 0.35 and 0.1

and temperatures of 1150, 1050 and 950°C. At 0.35 strain, 1150°C, the softening of all the steels was

very similar with rapid recrystallisation occurring. As the temperature decreased to 1050°C, the initial

softening was retarded by increasing Nb content, but above about 0.4 softened fraction the curves

became parallel as the rate of softening increased again as recrystallisation occurred. At 950°C, the

softening of all the Nb steels was significantly delayed compared with the C1Mn1 steel. The curves for

the Nb steels were coincident up to 0.45 softened fraction, where the C1Mn1Nb1 steel then started to

recrystallise. The C2Mn1Nb3 steel maintained the same shallow gradient of softening, suggesting that

it may only be recovering not recrystallising. The behaviour of the C1Mn1Nb3 steel lay between the

other two steels.

37

When the strain was lowered to 0.1, the softened fraction at which the curves diverged increased

compared with 0.35 strain, from 0.4 at 1150°C to around 0.6 at 950°C suggesting that recovery

continued for a longer proportion of the softening. All the steels showed an increase in softening rate

again at 1150°C above 0.5 softened fraction which was indicative of recrystallisation, but the time at

which this occurred increased with Nb content. (The C2Mn1Nb3 curve shows different behaviour at

short times due to a different acquisition frequency for the test data). As the temperature decreased to

950°C, only the C1Mn1 steel continued to recrystallise after the initial recovery period. The rate of

softening of the Nb steels slowed down above 0.6 softened fraction and then increased again slightly to

follow the same curve as the initial recovery stage. No consistent difference between the behaviour of

the C1Mn1Nb3 and C2Mn1Nb3 steels was observed and so the effect of increasing from 0.1 to 0.2

wt% carbon on the softening kinetics is negligible in these steels, although it will affect the Nb(C,N)

precipitation kinetics and thus the temperature at which precipitation inhibits recrystallisation.

0

0.2

0.4

0.6

0.8

1

0.001 0.01 0.1 1 10 100 1000

Time (s)

Softened fra

ction

C1Mn1

C1Mn1Nb1

C1Mn1Nb3

C2Mn1Nb3

0.35 strain 1150°C

(a) 0.35 strain, 1150°C

0

0.2

0.4

0.6

0.8

1

0.001 0.01 0.1 1 10 100 1000

Time (s)

Softened fra

ction

C1Mn1

C1Mn1Nb1

C1Mn1Nb3

C2Mn1Nb3

0.1 strain 1150°C

(b) 0.1 strain, 1150°C

0

0.2

0.4

0.6

0.8

1

0.001 0.01 0.1 1 10 100 1000

Time (s)

Softened fra

ction

C1Mn1

C1Mn1Nb1

C1Mn1Nb3

C2Mn1Nb3

0.35 strain 1050°C

(c) 0.35 strain, 1050°C

0

0.2

0.4

0.6

0.8

1

0.001 0.01 0.1 1 10 100 1000

Time (s)

Softened

fra

ction

C1Mn1

C1Mn1Nb1

C1Mn1Nb3

C2Mn1Nb3

0.1 strain 1050°C

(d) 0.1 strain, 1050°C

0

0.2

0.4

0.6

0.8

1

0.001 0.01 0.1 1 10 100 1000

Time (s)

Softened fra

ction

C1Mn1

C1Mn1Nb1

C1Mn1Nb3

C2Mn1Nb3

0.35 strain 950°C

(e) 0.35 strain, 950°C

0

0.2

0.4

0.6

0.8

1

0.001 0.01 0.1 1 10 100 1000

Time (s)

Softened

fra

ction

C1Mn1

C1Mn1Nb1

C1Mn1Nb3

C2Mn1Nb3

0.1 strain 950°C

(f) 0.1 strain, 950°C

Figure 21: “Normalised” softening curves for Tata steels deformed by 0.35 and 0.1 strain at three

temperatures, strain rate 1/s, 100µm initial austenite grain size.

38

Figure 22 compares the curves for softening at 1050°C and 950°C at strains of 0.35 and 0.1 for the

C1Mn1 steel and two of the Nb steels. Assuming that no precipitation of Nb has occurred at 1050°C,

then the retardation of the softening in the Nb steels is solely due to the Nb solute drag effect. The

effect of reducing the temperature on the C1Mn1 softening kinetics is to offset the curves parallel to

each other. The solubility equations for Nb(C,N) predict that Nb should be able to precipitate at 950°C.

However, if no precipitation had occurred, the softening at 950°C would only be due to a solute drag

effect. This has been estimated by offsetting a 950°C curve from the 1050°C curves in the same way as

for the CMn steel, as shown by the lines marked with triangles in each graph. The deviation in actual

softening kinetics (lines marked with open squares) from the estimated solute-controlled behaviour

could then be attributed to precipitation occurring during the delay in softening between about 0.3 – 0.4

softened fraction in the 0.35 strain curves and 0.6 – 0.7 softened fraction in the 0.1 strain curves.

0.2

0.4

0.6

0.8

1

0.01 0.1 1 10 100

Time (s)

Softened

fra

ction

C1Mn1 1050°C

C1Mn1Nb1 1050°C

C1Mn1 950°C

C1Mn1Nb1 950°C

C1Mn1Nb1 950°C solute drag

0.35 strain

precipitation?

temperature

solute drag

(a) 0.35 strain, C1Mn1 and C1Mn1Nb1

0.2

0.4

0.6

0.8

1

0.01 0.1 1 10 100

Time (s)

Soft

ened

fra

ction

C1Mn1 1050°C

C1Mn1Nb3 1050°C

C1Mn1 950°C

C1Mn1Nb3 950°C

C1Mn1Nb3 950°C solute drag

0.35 strain

precipitation?

temperature

solute drag

(b) 0.35 strain, C1Mn1 and C1Mn1Nb3

0.4

0.6

0.8

1

0.1 1 10 100 1000

Time (s)

Softened

fra

ction

C1Mn1 1050°C

C1Mn1Nb1 1050°C

C1Mn1 950°C

C1Mn1Nb1 950°C

C1Mn1Nb1 950°C solute drag

0.1 strain

precipitation?

temperature

solute drag

(c) 0.1 strain, C1Mn1 and C1Mn1Nb1

0.3

0.5

0.7

0.9

0.1 1 10 100 1000

Time (s)

Soft

ened

fra

ction

C1Mn1 1050°C

C1Mn1Nb3 1050°C

C1Mn1 950°C

C1Mn1Nb3 950°C

C1Mn1Nb3 950°C solute drag

0.1 strain

precipitation?temperature

solute drag

(d) 0.1 strain, C1Mn1 and C1Mn1Nb3

Figure 22: “Normalised” softening curves for Tata steels deformed by 0.35 and 0.1 strain at 1050°C

and 950°C, indicating effect of solute drag and precipitation.

Figure 23 shows the effect of different initial austenite grain sizes, obtained using the conditions in

Table 5, on the softening kinetics at 1050°C after a deformation of 0.2 strain at a strain rate of 1/s.

There was not a clear and consistent difference between the results, with all the samples fully softening

within approximately 10 seconds. This was unexpected, as increasing the grain size has been shown to

slow down the softening kinetics [5]. Further tests were performed starting from a very large austenite

grain size, obtained by reheating at 1300°C for 15 mins, but these also showed little difference. One

possible explanation could be that the recrystallisation kinetics were so rapid at this temperature and

strain that any grain size effect was masked. Tests on a steel that recrystallised more slowly might show

a stronger effect of grain size.

39

Figure 24 shows the effect of strain rates of 0.1, 1, 5 and 10/s on the softening kinetics at 1050°C after

a deformation of 0.2, initial austenite grain size ~100µm. The difference between the softening kinetics

at different strain rates was quite small, the clearest effect being the slower kinetics at a strain rate of

0.1/s in steels C1Mn1Nb1 and C1Mn1Nb3. The rate of softening at a specific strain rate decreased as

the amount of Nb in the steel increased from zero to 0.03 wt% (Figure 25), but no significant effect of

increasing the C content from 0.1 to 0.2 wt% was observed (compare steel C1Mn1Nb3 and

C2Mn1Nb3). Examples of the corresponding flow curves are given in Figure 26. Increasing the strain

rate from 0.1 to 10/s led to an increase in flow stress in all the steels. No strong effect of Nb content on

the flow stress was observed at a particular strain rate.

0

0.2

0.4

0.6

0.8

1

0.001 0.01 0.1 1 10 100 1000

Time (s)

Re

cry

sta

llise

d fra

ctio

n

small C1Mn1

medium C1Mn1

large C1Mn1

v large C1Mn1

small C1Mn1Nb3

medium C1Mn1Nb3

v large C1Mn1Nb3

(a) C1Mn1 (solid) and C1Mn1Nb3 (dashed)

0

0.2

0.4

0.6

0.8

1

0.001 0.01 0.1 1 10 100 1000

Time (s)

Recry

sta

llised fra

ction

small C1Mn1Nb1

medium C1Mn1Nb1

large C1Mn1Nb1

v large C1Mn1Nb1

small C2Mn1Nb3

medium C2Mn1Nb3

large C2Mn1Nb3

v large C2Mn1Nb3

(b) C1Mn1Nb1 (solid) and C2Mn1Nb3 (dashed)

Figure 23: Avrami recrystallisation curves for Tata steels deformed 0.2 strain at 1050°C, strain rate 1/s,

effect of different initial austenite grain sizes.

0

0.2

0.4

0.6

0.8

1

0.001 0.01 0.1 1 10 100

Time (s)

Recrystallised fraction

10/s

5/s

1/s

0.1/s

(a) C1Mn1, 1050°C

0

0.2

0.4

0.6

0.8

1

0.001 0.01 0.1 1 10 100

Time (s)

Recrystallised fraction

10/s

5/s

1/s

0.1/s

(b) C1Mn1Nb1, 1050°C

0

0.2

0.4

0.6

0.8

1

0.001 0.01 0.1 1 10 100

Time (s)

Recrystallised fraction

10/s

5/s

1/s

0.1/s

(c) C1Mn1Nb3, 1050°C

0

0.2

0.4

0.6

0.8

1

0.001 0.01 0.1 1 10 100

Time (s)

Recrystallised fraction

10/s

5/s

1/s

0.1/s

(d) C2Mn1Nb3, 1050°C

Figure 24: Avrami recrystallisation curves for Tata steels deformed 0.2 strain at 1050°C, effect of

strain rate

40

0

0.2

0.4

0.6

0.8

1

0.001 0.01 0.1 1 10 100

Time (s)

Recrystallised fraction

C1Mn1 10/s

C1Mn1Nb1 10/s

C1Mn1Nb3 10/s

C2Mn1Nb3 10/s

(a) strain rate 10/s

0

0.2

0.4

0.6

0.8

1

0.001 0.01 0.1 1 10 100

Time (s)

Recrystallised fraction

C1Mn1 1/s

C1Mn1Nb1 1/s

C1Mn1Nb3 1/s

C2Mn1Nb3 1/s

(b) strain rate 1/s

Figure 25: Avrami recrystallisation curves for Tata steels deformed 0.2 strain at 1050°C, showing

effect of Nb content at different strain rates

0

20

40

60

80

100

120

140

0 0.05 0.1 0.15 0.2 0.25

Strain (-)

Stress (MPa)

10/s

5/s

1/s

0.1/s

(a) C1Mn1, 1050°C

0

20

40

60

80

100

120

140

0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45

Strain (-)

Stress (MPa)

10/s

5/s

1/s

0.1/s

(b) C2Mn1Nb3, 1050°C

Figure 26: Flow curves for Tata steels deformed 0.2 strain at 1050°C, effect of strain rate

In addition to the stress relaxation test performed on steel C2Mn1Nb3 for the round robin exercise (see

below) a series of double hit (DH) compression tests were also carried out to provide an additional

comparison between test techniques. The first deformation of 0.35 strain was applied at 1050°C, the

load was removed, and then a second hit of 0.35 strain was applied after a specified interpass time. The

fractional softening (FS) was measured using the “2% offset method” from the stress-strain curves [6].

The method relies on the following equation to calculate the FS:

0σσσσ−−

=m

rmFS (3)

where mσ is the value of the stress before unloading, and 0σ and rσ are the stresses corresponding to

2% strain values of the first and second curves, as shown in Figure 27.

41

0

10

20

30

40

50

60

70

80

90

0 0.1 0.2 0.3 0.4

Strain

Stress (MPa)

σσσσ0000

σσσσm

σσσσr

εεεε=0.02 εεεε=0.02

Figure 27: Definition of the stresses used in the 2% offset method for the determination of the

fractional softening.

Eight different interpass times from 0.1 to 100s were used to define the softening curve. The stress-

strain curves are shown in Figure 28(a) and clearly show that the degree of softening increased from

almost zero after 0.1s interpass time up to complete softening after 100s. Figure 28(b) compares the

DH test softening values with the stress relaxation (SR) result from Figure 14(d). The Avrami curve

fitted to the DH data is also shown. There was reasonable agreement between the results, with the DH

tests giving slightly slower softening kinetics than stress relaxation, which is consistent with previous

Gleeble results [7].

0

40

80

120

0.1 0.3 0.5 0.7 0.9 1.1

Strain (-)

Str

ess (

MP

a)

ip time 0.1s ip time 0.5s

ip time 1s ip time 2s

ip time 3s ip time 5s

ip time 10s ip time 100s

(a) Stress-strain curves for double hit round robin tests

0.0

0.2

0.4

0.6

0.8

1.0

0.01 0.1 1 10 100 1000

Time (s)

Softened fraction

Tata uniaxial SR

Tata uniaxial DH 2%offset

Tata uniaxial DHAvrami fit

(b) Softened fraction curves

Figure 28: Round robin test results on steel C2Mn1Nb3 deformed to 0.35 strain at 1050°C using Tata

Gleeble in uniaxial compression.

Effect of Si

According to the matrix of tests defined in Task 3.1 (see Table 7), softening kinetics of C2Mn2Si1,

C2Mn2Si2, C2Mn2Si2Nb3 and C2Mn2Si2Nb7 steel grades were obtained from stress-strain curves of

the double hit test using the back extrapolation method. Some of the tests were also performed using

the 2% offset method to compare results between both methods. Figure 29 shows an example of stress-

strain curves of the C2Mn2Si1 grade obtained for several inter-pass times at a temperature of 1050°C

with a deformation of 0.2 for the first hit. From the stress-strain curves, softening kinetics were then

obtained by plotting the softening fraction as a function of inter-pass time, Figure 30. The results show

an average difference of around 8% between the two methods.

42

Figure 29: C2Mn2Si1 steel grade - Stress-Strain

curves - variation of inter-pass time (IPT)

Figure 30: Comparison of fractional softening

between back extrapolation and 2% offset method

The influence of deformation temperature, deformation intensity and silicon/niobium content on

softening kinetics are given in Figure 31 to Figure 33, which were determined for large austenite grain

size (around 230µm, see task 4.2). Markers on the charts are experimental values. Continuous curves

represent KJMA model functions (see equation (2)) for which the time for 50% recrystallisation, t50,

and Avrami exponent, n, were adapted to best fit experimental values. These values are summarised in

Table 19.

Table 19: Avrami exponent and t50 - Fitting of KJMA model to Si steels

The effect of the deformation temperature on SRX kinetics was more pronounced with the presence of

Nb as alloying element. Indeed, decreasing the deformation temperature from 1050°C to 950°C

increased t50 by 6 sec for the C2Mn2Si2 grade (Figure 31b) while the increase was 247 sec for the

C2Mn2Si2Nb3 grade (Figure 31c). This is due to the effect of niobium in solid solution on recovery.

Concerning the effect of the deformation intensity, Figure 33 reveals as expected that the higher the

deformation, the faster the kinetics. Concerning the C2Mn2Si2Nb7 curve of Figure 32a, experimental

values revealed that the recrystallisation was stopped roughly 100sec after the deformation. It seems

that for this case, precipitation started just after the deformation. Figure 32 shows that no clear effect of

silicon in solid solution on SRX kinetics was observed and only niobium affects the kinetics. However,

steel grades containing a high level of silicon content of 1% and 2% were used to determine the silicon

effect. A possible saturation effect could explain that no effect of silicon on SRX kinetics was

observed. Suikkanen found that the effect of Si on the activation energy for recrystallisation tended to

saturate towards 1.5 wt% [14]. Maebara found that Si retarded recrystallisation linearly up to 1wt% but

then not at all [15].

43

Figure 31: Deformation temperature effect on measured SRX kinetics in Si steels

According to reference [12], in the absence of niobium, the silicon effect on austenite recrystallisation

for steel grades containing 0.1%C – 0% to 1.1%Si – no Nb was observed to retard SRX kinetics.

Furthermore according to reference [13], in the presence of niobium for steel grade containing 0.1%C -

0% to 0.5%Si, the increase of Tnr with silicon content is explained by its effect in accelerating Nb(CN)

precipitation. In both studies, the silicon effect was determined from steel grades containing not more

than 1%Si. In the MICROTOOLS project, by comparing SRX kinetics obtained from 1%Si and 2%Si

steel grade, no effect of silicon content on SRX kinetics was observed in the absence of Nb. The

saturation effect could be verified by comparing SRX kinetics results of 1%Si and 2%Si with an

additional steel grade containing no silicon. Project steel C2Mn2 was not studied by CRM, but hot

torsion tests were performed by CEIT on this steel grade to determine the effect of aluminium (Figure

37). The test condition with a deformation of 0.35 at a temperature of 1000°C was considered by both

CRM and CEIT and was used to make a first estimation of the silicon effect on the SRX kinetics. From

the round robin tests for the C1Mn1Nb7 and C2Mn1Nb3 steel grades (Table 26), the SRX kinetics

determined by CRM using double hit torsion tests were in both cases 5 times faster than those

determined by CEIT. A time corrective coefficient of 5 can be considered to compare SRX results

between the results of the two partners. Figure 34 compares the SRX kinetics of the C2Mn2,

C2Mn2Si1 and C2Mn2Si2 steel grades obtained at a deformation of 0.35 at 1000°C to make a

qualitative estimation of the effect of silicon. Figure 35 shows the evolution of the time to reach 50%

recrystallisation obtained from the Avrami plots of Figure 34 as a function of the silicon content.

Furthermore, to remove the grain size effect, the t0.5SRX was normalized according to equation (24).

This reveals that silicon retards recrystallisation, the effect being more marked from 0% to 1% Si than

from 1% to 2%Si.

44

Figure 32: Effect of silicon/niobium on measured SRX kinetics

45

Figure 33: Deformation intensity effect on measured SRX kinetics

Figure 34: Effect of Si on static recrystallisation

kinetics

Figure 35: Effect of Si on t50 and normalised t50

Effect of Al

In order to investigate the solute drag effect exerted by Al addition, the softening data corresponding to

the C2Mn2 and C2Mn2Al steels were first considered. The data corresponding to the Nb microalloyed

heats (C2Mn2Al1Nb3, C2Mn2Al2Nb3 and C2Mn2Al2Nb7) will be analysed separately in Task 3.5.

Figure 36 shows an example of the stress-strain curves obtained in double-hit torsion tests carried out

with the C2Mn2Al1 steel for a deformation temperature of 925ºC and varying interpass times. As can

be observed from the figure, the stress level of the second curve decreased as the interpass time

increased. This can be attributed to the operation of microstructural softening mechanisms between the

46

two deformation passes. From the strain-stress curves, the fractional softening (FS) was calculated

using the 2% offset method, equation (3) [6].

0

20

40

60

80

100

120

140

160

180

0 0.1 0.2 0.3 0.4 0.5

Stress (MPa)

Strain

tip=8s

tip=13s

tip=20s

tip=35s

tip=39s

tip=77s

tip=107s

tip=280s

C2Mn2Al1 925ºC

Figure 36: Stress-strain curves obtained for the C2Mn2Al1 steel deformed at 925ºC at

different interpass times.

The fractional softening calculated for the C2Mn2, C2Mn2Al1 and C2Mn2Al2 steels at the different

deformation conditions investigated is plotted in Figure 37 and Figure 38. The softening data obtained

display in all the cases a sigmoidal shape and can be well-fitted to an Avrami type equation (equation

(2)). The data in Figure 37 and Figure 38 show that, as usually reported, the softening is retarded with

decreasing the deformation temperature or strain. However, it is also evident that the retardation effect

due to temperature decrease is larger for the C2Mn2Al2 than for the C2Mn2 and C2Mn2Al1 steels.

0

0.2

0.4

0.6

0.8

1

0.1 1 10 100 1000 10000

Fractional Softening

t (s)

T=1065ºC

T=1000ºC

T=925ºC

C2Mn2

ε=0.35

(a) C2Mn2

0

0.2

0.4

0.6

0.8

1

0.1 1 10 100 1000 10000

Fractional Softening

t (s)

T=1065ºC

T=1000ºC

T=925ºC

C2Mn2Al1

ε=0.35

(b) C2Mn2Al1

0

0.2

0.4

0.6

0.8

1

0.1 1 10 100 1000 10000

Fractional Softening

t (s)

T=1065ºC

T=1000ºC

T=965ºC

T=925ºC

C2Mn2Al2

ε=0.35

(c) C2Mn2Al2

Figure 37: Fractional softening obtained for the Al steels at different deformation temperatures.

47

0

0.2

0.4

0.6

0.8

1

0.1 1 10 100 1000 10000

Fractional Softening

t (s)C2Mn2Al1

ε=0.2

ε=0.35

(a) C2Mn2Al1

0

0.2

0.4

0.6

0.8

1

0.1 1 10 100 1000 10000

Fractional Softening

t (s)C2Mn2Al2

ε=0.2

ε=0.35

(b) C2Mn2Al2

Figure 38: Fractional softening obtained for the Al steels after applying different strains.

Figure 39 shows the softening obtained for the different steels at the same deformation conditions.

Although the austenite grain size can also affect the softening kinetics [6], in the present case the

curves corresponding to the C2Mn2 and C2Mn2Al2 can be directly compared due to the similar initial

grain sizes (D0∼65-69 µm) obtained for the two steels. The figure shows that Al exerts a significant

retardation effect on the softening kinetics. However, the effect is enhanced for the highest Al content

(2%), and the lowest deformation temperature (925ºC). In order to investigate the mechanisms leading

to this retardation, specimens were quenched at different conditions and their microstructure analysed.

The results obtained will be detailed in WP4.

0

0.2

0.4

0.6

0.8

1

0.1 1 10 100 1000 10000

Fractional Softening

t (s)

C2Mn2

C2Mn2Al1

C2Mn2Al2

ε=0.35T=1065ºC

(65 µm)

(100 µm)

(69 µm)

(a) T=1065°C

0

0.2

0.4

0.6

0.8

1

0.1 1 10 100 1000 10000

Fractional Softening

t (s)

C2Mn2

C2Mn2Al1

C2Mn2Al2

ε=0.35T=1000ºC

(69 µm)

(100 µm)

(65 µm)

(b) T=1000°C

0

0.2

0.4

0.6

0.8

1

0.1 1 10 100 1000 10000

Fractional Softening

t (s)

C2Mn2

C2Mn2Al1

C2Mn2Al2

ε=0.35T=925ºC

(69 µm)

(100 µm)

(65 µm)

(c) T=925°C

Figure 39: Fractional softening obtained for the C2Mn2, C2Mn2Al1 and C2Mn2Al2 steels at different

temperatures

48

Effect of Mn and Nb

Figure 40 to Figure 43 show the softening curves obtained by double hit tests in torsion on C1Mn2,

C1Mn2Nb3, C1Mn1Nb7 and C1Mn2Nb7 respectively under the conditions selected in the

experimental programme. The softening curves are presented showing the experimental values and the

best fit assuming a JMAK or Avrami behaviour. The figures show the results highlighting the effect of

test temperature, applied strain and initial grain size on softening kinetics. The softening was retarded

as temperature or strain decreased, as expected. There was a minimal effect of initial austenite grain

size, however, which was consistent with the results on the Tata Mn1Nb steels reported earlier in this

Task. Table 20 to Table 23 summarise the results in terms of softening parameters from the Avrami

curves derived for these steels: t50 (s) and n. In addition, in the case of microalloyed steels the values of

precipitation start time (Ps (s)) and precipitation end time (Pf (s)) were derived corresponding to the

estimated time for the initiation of the plateau indicating the inhibition of softening and that

corresponding to the end of the inhibition triggering further progress of softening as proposed by

Medina et al [16]. The levels of softening achieved before the inhibition are also reported. In those

cases in which the inhibition occurred at softening levels below 50%, the values of t50 and n reported

correspond to the Avrami curve derived from the experimental values before the inhibition. In these

cases the parameters should be considered with care.

Table 20: Softening parameters for C1Mn2

Grade Temperature

(°C) Strain

Initial Grain

Size (µm) t50 (s) n

C1Mn2 1050 0,35 124 1,3 0,9

C1Mn2 1000 0,35 124 2,2 0,9

C1Mn2 950 0,35 124 4 0,8

C1Mn2 1050 0,5 124 0,8 0,9

C1Mn2 1050 0,2 124 2,1 0,9

C1Mn2 950 0,2 124 12 0,5

C1Mn2 1050 0,35 162 1,3 0,7

C1Mn2 950 0,35 162 4,5 0,8

Table 21: Softening parameters for C1Mn2Nb3

Grade Temp

(°C) Strain

Initial

Grain

Size

(µm)

t50 (s) n Ps (s) Pf (s) Rplateau

C1Mn2Nb3 1050 0,35 127 5,5 0,85

C1Mn2Nb3 1000 0,35 127 13 0,75

C1Mn2Nb3 950 0,35 127 8 0,65 2 >1000 0.24

C1Mn2Nb3 1050 0,5 127 2,4 0,85

C1Mn2Nb3 1050 0,2 127 14 0,8

C1Mn2Nb3 950 0,2 127 10 0,65 3 >400 0.27

C1Mn2Nb3 1050 0,35 138 6 0,85

C1Mn2Nb3 950 0,35 138 8 0,65 2 >1000 0,26

49

Table 22: Softening parameters for C1Mn1Nb7

Grade Temp

(°C) Strain

Initial

Grain

Size

(µm)

t50 (s) n Ps(s) Pf (s) Rplateau

C1Mn1Nb7 1050 0,35 128 12,5 0,65

C1Mn1Nb7 1000 0,35 128 14 0,65 3,5 84 0,25

C1Mn1Nb7 950 0,35 128 16 0,65 3 >100 0,21

C1Mn1Nb7 1050 0,5 128 9 0,65 27,5 >100 0,75

C1Mn1Nb7 1050 0,2 128 15 0,65 1,75 >10 0,16

C1Mn1Nb7 950 0,2 128 12 0,65 4,25 >5 0,30

Table 23: Softening parameters for C1Mn2Nb7

Grade Temp

(°C) Strain

Initial

Grain

Size

(µm)

t50 (s) n Ps(s) Pf (s) Rplateau

C1Mn2Nb7 1050 0,35 106 7 0,65

C1Mn2Nb7 1000 0,35 106 11 0,65 4,65 >10 0,30

C1Mn2Nb7 950 0,35 106 17 0,65 4 >10 0,23

C1Mn2Nb7 1050 0,5 106 5 0,65 19,5 >100 0,80

C1Mn2Nb7 1050 0,2 106 7,5 0,65 2,25 >100 0,27

C1Mn2Nb7 950 0,2 106 16 0,65 3,25 >100 0,22

C1Mn2Nb7 1050 0.35 271 6 0,65 22 >100 0,79

C1Mn2Nb7 950 0,35 271 14 0,65 3 >100 0,23

50

C1Mn2 - εεεε 0.35 - D°124µm

0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

0,8

0,9

1

0,1 1 10 100 1000

Time, s

Soft

en

ing

Fra

ctio

n

1050°C - Exp.

1050°C - JMAK fit

1000°C - Exp

1000°C - JMAK fit

950°C - Exp.

950°C - JMAK fit

(a) effect of temperature

C1Mn2Nb3 - e 0.35 - D°127µm

0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

0,8

0,9

1

0,1 1 10 100 1000

Time, s

So

fte

nin

g F

rac

tio

n

950°C - Exp

950°C - JMAK fit

1000°C - Exp

1000°C - JMAK fit

1050°C - Exp.

1050°C - JMAK fit

(a) effect of temperature

C1Mn2 - D°124µm

0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

0,8

0,9

1

0,1 1 10 100 1000

Time, s

Soft

en

ing

Fra

ctio

n

950°C - e 0.2 - Exp

950°C - e 0.2 - JMAK fit

950°C - e 0.35 - Exp

950°C - e 0.35 - JMAK fit

1050°C - e 0.2 - Exp.

1050°C - e 0.2 - JMAK fit

1050°C - e 0.35 - Exp.

1050°C - e 0.35 - JMAK fit

1050°C - e 0.5 - Exp.

1050°C - e 0.5 - JMAK fit

(b) effect of strain

C1Mn2Nb3 - 1050°C - D°127µm

0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

0,8

0,9

1

0,1 1 10 100 1000

Time, s

Soft

en

ing

Fra

ctio

n

e 0.2 - Exp

e 0.2 - JMAK fit

e 0.35 - Exp

e 0.35 - JMAK fit

e 0.5 - Exp

e 0.5 - JMAK fit

(b) effect of strain

C1Mn2 - εεεε 0.35

0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

0,8

0,9

1

0,1 1 10 100 1000

Time, s

Soft

en

ing

Fra

ctio

n

950°C - D°124µm - Exp

950°C - D°124µm - JMAK fit

950°C - D°162µm - Exp

950°C - D°162µm - JMAK fit

1050°C - D°124µm - Exp

1050°C - D°124µm - JMAK fit

1050°C - D°162µm - Exp

1050°C - D°162µm - JMAK fit

(c) effect of austenite grain size

C1Mn2Nb3 - ε 0.35

0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

0,8

0,9

1

0,1 1 10 100 1000

Time, s

Soft

en

ing

Fra

ctio

n

950°C - D°125µm - Exp

950°C - D°127µm - JMAK fit

950°C - D°138µm - Exp

950°C - D+138µm - JMAK fit

1050°C - D°127µm - Exp

1050°C - D°127µm - JMAK fit

1050°C - D°138µm - Exp

1050°C - D°138µm - JMAK fit

(c) effect of austenite grain size

Figure 40: Softening curves for C1Mn2 Figure 41: Softening curves for C1Mn2Nb3

51

C1Mn1Nb7 - ε 0.35 - D°125µm

0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

0,8

0,9

1

0,1 1 10 100 1000

Time, s

So

fte

nin

g F

ract

ion

950°C - Exp

950°C - JMAK fit

1000°C - Exp

1000°C - JMAK fit

1050°C - Exp

1050°C - JMAK fit

(a) effect of temperature

C1Mn2Nb7 - e 0.35 - D°107µm

0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

0,8

0,9

1

0,1 1 10 100 1000

Time, s

Soft

en

ing

Fra

ctio

n

950°C - Exp

950°C - JMAK fit

1000°C - Exp

1000°C - JMAK fit

1050°C - Exp

1050°C - JMAK fit

(a) effect of temperature

C1Mn1Nb7 - 1050°C - D°125µm

0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

0,8

0,9

1

0,1 1 10 100 1000

Time, s

So

fte

nin

g F

ract

ion

e 0.2 - Exp

e 0.2 - JMAK fit

e 0.35 - Exp

e 0.35 - JMAK fit

e 0.5 - Exp

e 0.5 - JMAK fit

(b) effect of strain

C1Mn2Nb7 - 1050°C - D°107µm

0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

0,8

0,9

1

0,1 1 10 100 1000

Time, s

Soft

en

ing

Fra

ctio

n

e 0.2 - Exp

e 0.2 - JMAK fit

e 0.35 - Exp

e 0.35 - JMAK fit

e 0.5 - Exp

e 0.5 - JMAK fit

(b) effect of strain

Figure 42: Softening curves for C1Mn1Nb7 C1Mn2Nb7 - ε 0.35

0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

0,8

0,9

1

0,1 1 10 100 1000

Time, s

Soft

en

ing

Fra

ctio

n

950°C - D°106µm - Exp

950°C - D°106µm - JMAK fit

950°C - D°271µm - Exp

950°C - D°271µm - JMAK fit

1050°C - D°106µm - Exp

1050°C - D°106µm - JMAK fit

1050°C - D°271µm - Exp

1050°C - D°271µm - JMAK fit

(c) effect of austenite grain size

Figure 43: Softening curves for C1Mn2Nb7

52

A large number of experimental values have been collected showing a limited dispersion and allowing

a rather adequate description of the softening behaviour for the selected steels and testing conditions.

Nevertheless in certain cases further tests should be performed to obtain a more accurate description of

the softening behaviour. Notably for C1Mn1Nb7 and C1Mn2Nb7, the tests performed at 1050°C

(ε=0.35 and ε=0.5) did not reach a fully softened state with values of softening fraction reported

between 0.75 and 0.90. From these results it is not possible to clearly distinguish between softening

following Avrami behaviour and the event of softening inhibition in this softening range. Further

testing at interpass times exceeding 100s are required. In order to clarify this issue the quantification of

precipitates has been performed for these conditions for times up to 400s, as reported in Task 4.3.

Similarly, for C1Mn1Nb7 at 1000°C, tests extending the interpass times up to 1000s were performed

identifying in the range 100-1000s the end of the inhibition of softening triggered at short interpass

times. However, this was not verified in C1Mn2Nb7 which presented a similar softening behaviour at

1000°C for interpass times up to 100s.

2.3.3.3 Task 3.2: Round robin exercise

A round robin exercise has been carried out between the project partners, to compare the results from

the different thermomechanical test techniques and machines, to verify the uniformity of the softening

database to be created. One set of trials, to compare the torsion test machines of the partners, was

carried out on the C1Mn1Nb7 grade which was supplied by ArcelorMittal. The second set of tests, to

compare double hit and stress relaxation tests for static recrystallisation measurement, was performed

on the C2Mn1Nb3 steel grade, supplied by Tata Steel. A comparison of the results in terms of flow

stress and softening kinetics has been made highlighting the similarities and differences.

1. Comparison of torsion test machines on steel C1Mn1Nb7 (AM, CEIT, CRM)

Double hit torsion test conditions:

• reheat 1250°C for 15 mins

• cool at 1°C/s to 1150°C

• roughing deformation of 0.8 strain at 1150°C, strain rate 1s-1

• cool at 5°C/s to 1050°C

• Test deformation 0.35 strain at 1050°C, interpass time 5-100s, strain rate 1s-1.

The comparison was made in terms of the evolution of flow stress with strain and in softening using the

method of 2% Offset for the calculation of the softening parameter R. Torsion testing amongst the

project partners differs both in terms of sample geometry and dimensions and in terms of temperature

control methodology or strategy. Figure 44 presents a schematic illustration of these differences, most

important are the different approaches for measuring test temperature and to control the temperature of

the test with the inductor.

At CEIT a thermocouple is inserted in the axis of the sample and into the working length of the sample

(total length of 16.5mm) to a depth of approximately 5mm. The measurement of this thermocouple is

considered the test temperature and controls the power generator for the induction heating keeping the

isothermal conditions.

At AM, and after several adjustments during the progress of the project, the chosen methodology

consisted of a temperature measurement made by a thermocouple welded on the surface of the sample

head (not subjected to deformation). Preliminary tests were performed with an inserted thermocouple

in the axis of the sample and into the working length (total length of 50mm) to a depth of 10mm and

these tests performed with no deformation showed a temperature difference between the inserted and

the welded one of -70°C in the range 900-1100°C. The temperature measurement of the inserted

thermocouple was considered the test temperature and a constant difference of 70°C was assumed with

the welded one under all testing conditions in the study. The tests were therefore performed with a

welded thermocouple at the sample head aiming at a temperature 70°C below the target, this

thermocouple controlled the induction heating device.

53

At CRM the temperature was measured by a bichromatic pyrometer aimed at the mid-point of the

working length (total length of 25mm), this measurement on the surface was considered the test

temperature and it controlled the induction heating device. As can be noted the differences are

significant and in addition each of the machines presents different designs of induction heating devices

(coil diameter and total inductor length), factors known to have an influence on temperature

homogeneity in the samples.

1

2

50mm

6mm

1

2

50mm

6mm

AM – Thermocouple Control

1: TCP Position for reference temperature (inserted thermocouple) 2: TCP

Position for controlling temperature (welded thermocouple)

1

16.5mm

7.5mm 7,5mm1

16.5mm

7.5mm1

16.5mm

7.5mm 7,5mm

CEIT – Thermocouple Control

1: TCP Position for reference temperature and controlling temperature

(inserted thermocouple)

25mm

6mm

1

25mm

6mm

11

CRM – Pyrometer Control

1: Position for reference temperature and controlling temperature (incident

beam from bichromatic pyrometer)

Figure 44: Sample Dimensions and Temperature control

for torsion tests at AM, CEIT and CRM

Figure 45 presents a comparison of the flow stress curves obtained under the selected conditions by

AM and CEIT for which the test temperature corresponded to that at the axis of the sample in its

working length. Differences were identified in the flow stress evolution both in the level of strength

achieved and in the shape of the curves that characterises the strain hardening of the material. The flow

stress at AM was approximately 10% higher than at CEIT under identical test conditions. The cause of

such differences in flow stress level is yet to be clarified, nevertheless it could be argued that the actual

test temperatures at CEIT were higher than that at AM and issues of sample geometry and the selected

approaches for temperature measurement and control need to be further investigated. Regarding the

shape of the flow stress-strain curve, it was noted that the strain hardening rate was somewhat higher at

the initial stages of deformation in AM test but lower at the last stages of deformation compared to

CEIT curves. In order to analyse the deviations in the evolution of strain hardening rates, the evolution

of strain rate during the test at AM was verified and the results are presented in Figure 46 in terms of

angular rate evolution during deformation. This angular rate is directly related to the strain rate and for

the sample geometry and conditions at AM a strain rate of 1/s corresponds to 287rev/min. This rate is

reached almost immediately in the test and similarly the deceleration at the end of deformation is

performed in a very small fraction of time and therefore of strain. This verification eliminates strain

rate deviations as a source of error in the curves at AM.

Finally, a comparison has been made between the experimental results and a physically based model

under development at AM which considers the flow stress behaviour as composed by the following

terms: lattice friction stress (σ0 ), the effective stress (σeff ) required to overcome local obstacles with

54

the help of thermal fluctuations and enables dislocation movements, the Internal stress (σi) considering

long range stress due to dislocation forest accumulation; this term plays a major role during

deformation and the back stress (σb ) created due to the effect of dislocation pile-up at the grain

boundaries. This model has been internally validated at AM and its application on the Round Robin

steel and test conditions is shown in Figure 47 showing that predicted values closely corresponded to

those obtained experimentally on the torsion machine in AM. According to these verifications the

stress strain curves derived from torsion tests at AM were considered adequate for the proposed

experimental programme. As mentioned before, further work is required to identify the cause of

discrepancies between the curves derived at CEIT and AM.

0

20

40

60

80

100

120

0 0,1 0,2 0,3 0,4 0,5

Strain

Stre

ss (

MP

a)

CEIT tip=1s

AM tip=1s

0

20

40

60

80

100

120

0 0,1 0,2 0,3 0,4 0,5

Strain

Stre

ss (

MP

a)

CEIT tip=5s

AM tip=3s

0

20

40

60

80

100

120

0 0,1 0,2 0,3 0,4 0,5

Strain

Stre

ss (

MP

a)

CEIT tip=10s

AM tip=10s

0

20

40

60

80

100

120

0 0,1 0,2 0,3 0,4 0,5

Strain

Stre

ss (

MP

a)

CEIT tip=80s

AM tip=100s

Figure 45: Comparative Flow curves AM and CEIT for C1Mn1Nb7 – 1050°C – ε=0.35 – ε=1/s

0

20

40

60

80

100

120

0 0,05 0,1 0,15 0,2 0,25 0,3 0,35 0,4 0,45 0,5

Strain

Stre

ss (

MP

a)

0

50

100

150

200

250

300

350

400

450

An

gu

lar

Ra

te (

rev

/min

)

AM Stress (MPa)AM Strain Rate (rev/min)AM Strain rate equivalent to 1/s

0

20

40

60

80

100

120

140

0 0,1 0,2 0,3 0,4 0,5

Strain

Stre

ss (

MP

a)

Predicted value

AM tip=1s

Figure 46: Evolution of stress and strain rate with

strain for AM tests (tip=1s)

Figure 47: Stress evolution comparison of

experimental and model predicted results

55

Figure 48 compares the stress strain curves obtained by AM and CEIT with those obtained under

identical conditions by CRM. It can be noted that the flow stress levels are significantly lower in CRM

curves. This difference is mainly attributed to the different approach taken by CRM regarding the

reference temperature of the test located at the surface of the sample at the mid-point of the working

length. In tests performed at AM a temperature difference has been consistently measured between the

axis of the sample and the surface of the sample exceeding 50°C. This is an important consideration to

be made for the analysis of the global database of project MICROTOOLS.

0

20

40

60

80

100

120

0 0,1 0,2 0,3 0,4 0,5

Strain

Stre

ss (

MP

a)

CRM tip=1s

AM tip=1s

CEIT tip=1s

0

20

40

60

80

100

120

0 0,1 0,2 0,3 0,4 0,5

Strain

Stre

ss (

MP

a)

CRM tip=3s

AM tip=3s

CEIT tip=5s

Figure 48: Comparative Flow curves AM/CEIT and CRM for C1Mn1Nb7 – 1050°C – ε=0.35 – ε=1/s

From the stress strain curves the softening curves have been determined using the method of 2%

Offset. Table 24 presents the comparison of softening fraction calculations for the differences in the

flow stress curves, a rather good agreement in terms was found in the calculated R values. Differences

in the maximum flow stress σmax exceeded 10% as mentioned above, even considering certain

deviations in the total applied strain (lower than target 0.35 for CEIT curves). These differences

increased for σyi+1

and σyi; however these differences compensate to bring only small deviations in the

calculated R values leading to a similar description of the static softening behaviour. Figure 49 presents

the resulting softening curves showing rather similar kinetics.

0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

0,8

0,9

1

0,1 1 10 100 1000

Time, s

Softening Fraction

AM Experimental

AM Avrami

CEIT Experimental

CEIT Avrami

0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

0,8

0,9

1

0,1 1 10 100 1000

Time, s

Softening Fraction

CRM Experimental

CRM Avrami

AM Experimental

AM Avrami

CEIT Experimental

CEIT Avrami

C1Mn1Nb7

Figure 49: Softening curves for C1Mn1Nb7 –

1050°C – ε=0.35 – ε=1/s – Comparative Results

by Torsion AM and Torsion CEIT

Figure 50: Softening curves for C1Mn1Nb7 –

1050°C – ε=0.35 – ε=1/s – Comparative Results

by Torsion AM, Torsion CEIT, Torsion CRM

The comparative analysis of softening was extended to include CRM results and Table 25 compares the

softening fraction calculations with those from CEIT and AM. In this case the softening values from

CRM were significantly higher under identical conditions. Figure 50 presents the resulting softening

curves showing accelerated softening kinetics derived from CRM experiments. It can be argued that

this is a consequence of the different approach on considering testing temperatures as discussed above.

56

Higher relative temperatures in CRM testing would explain the accelerated kinetics observed in static

softening.

Table 24: Calculation of softening fraction using 2% offset Method – Comparison AM/CEIT

1s 3/5s 10s 50/30s 100/80s

AM CEIT AM CEIT AM CEIT AM CEIT AM CEIT

σσσσyi (MPa) (offs2%) 58 44 57 44 55 38 53 43 53 39

σσσσyi+1 (MPa) (offs2%) 108 87 102 89 84 70 65 55 59 52

σσσσmax (MPa) 116 97 115 100 109 100 110 100 107 98

R Factor 0,13 0,18 0,22 0,20 0,47 0,48 0,80 0,79 0,88 0,78

Table 25: Calculation of softening fraction using 2% Offset Method – Comparison CRM

1s 3/5s

AM CEIT CRM AM CEIT CRM

σσσσ0i (MPa) (offs2%) 58 44 45 57 44 44

σσσσ0i+1 (MPa) (offs2%) 108 87 72 102 89 60

σσσσmax (MPa) 116 97 84 115 100 85

R Fractor 0,13 0,18 0,305 0,22 0,20 0,610

Table 26 summarises the static softening parameters for C1Mn1Nb7 under the selected conditions for

the Round Robin as derived from torsion tests at each partner as a fit assuming JMAK or Avrami

behavior together with the measured initial austenite grain size before the deformation. The differences

in terms of t50 are significant between CRM and both CEIT and AM whilst regarding n similarities

were obtained between CRM and CEIT with lower values reported by AM. This reveals the complexity

for a proper and safe interpretation of data and this may impose significant limitations for the

application of softening databases of different origins for the construction of one single robust model.

Table 26: Softening parameters for C1Mn1Nb7 as obtained by AM, CEIT and CRM

CEIT AM CRM

t50 (s) 11,7 12,5 2,3

Avrami exponent n 0.97 0.65 0.97

Mean Dg (µm) 168 128.4 187

In order to further examine the validity of experimental results, a final comparison was made at AM

with an external database of double hit torsion testing made available by NSC (Nippon Steel

Corporation) as a consequence of technical exchanges between companies. In this database the

softening behaviour of 0.15%C-2%Mn steel was determined after reheating at 1150°C and deformation

at 850°C with applied strain of 0.5 and strain rate of 10/s. This data was compared with that obtained in

C1Mn2 steel following the same testing conditions but a strain rate of 1/s, as 10/s is not achievable

using the current torsion testing procedure at AM. No significant differences are nevertheless expected

in the softening parameters as a consequence of the lower applied strain rate, only a very limited

increase in softening kinetics under high strain rate conditions. Figure 51 presents the comparison of

softening curves and Table 27 the results in terms of softening parameters. Close similarities were

found between these curves, notably in the softening parameters t50 with only small differences

observed as expected. However, the values of n obtained from the experiments at AM were lower. This

was also the case in the comparative tests with CEIT and CRM on microalloyed steel at high

temperature.

57

0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

0,8

0,9

1

0,1 1 10 100 1000

Time, s

Softening Fraction

NSC C15Mn2 - strain rate:10/s

Avrami

AM C1Mn2 - strain rate:1/s

Avrami

t50 (s) n

NSC C15Mn2

(850°C/0.5/10s-1)

5 1.1

AM C1Mn2

(850°C/0.5/1s-1)

6.1 0.65

Figure 51: Comparison of softening curves for CMn

steels C15Mn2 and C1Mn2 from NSC and AM

(T=850°C, ε=0.5)

Table 27: Softening parameters for CMn

steels by AM and NSC derived from

torsion testing

The Round Robin tests have revealed important differences in flow stress mainly attributed to

differences in temperature measurements and the adopted temperature control criterion but also to

differences in the strain hardening behaviour revealed by the shape of the flow stress curves. At AM a

long series of tests have led to an optimised operation by adopting the temperature at the axis of the

sample as the test temperature. At the same time, the strain hardening behaviour has been validated

using a physical model for predicting flow stress. The differences in flow stress between the partners

have led to differences in softening kinetics both in terms of t50 and n parameters. An additional

exercise was performed by comparing softening data from torsion tests using a database external (NSC)

to the partners involved in the project. This has shown only small differences in softening with AM

results in terms of t50 but important ones in terms of n value. The low values of n consistently obtained

at AM are currently the subject of further investigation. Nevertheless, from these results AM have

pursued the experimental programme using the methodologies adopted in these Round Robin tests.

However, further work would be required to resolve the discrepancies between the torsion test results.

On the other hand, it could be argued that the building of a common database with contributions from

different torsion machines may not be a reliable approach for constructing or fitting a single predictive

model.

2. Comparison between double hit torsion, double hit compression and stress relaxation tests on steel

C2Mn1Nb3 (all partners)

Test conditions:

• reheat 1250°C for 15 mins

• cool at 5°C/s to 1150°C

• roughing deformation of 0.2 strain at 1150°C, strain rate 1s-1 + holding time 50s

• cool at 5°C/s to 1050°C

• test deformation 0.35 strain at 1050°C, strain rate 1s-1 + interpass time 10s

• quench to room temperature

Tata – stress relaxation and double hit compression tests; CEIT – double hit torsion tests

AM – double hit compression tests and stress relaxation; CRM – double hit torsion tests

The first step was to define the conditions required on each test machine to obtain a ~100µm austenite

grain size before the deformation (Table 28). The tests were then performed at each partner as

described in Task 3.1. The softened fraction determined from each of the tests is shown in Figure 52.

The techniques applied at the partners include uniaxial compression tests (Gleeble machines at Tata

and AM) and torsion tests (CEIT, CRM). Both double hit (DH) and stress relaxation (SR) tests were

performed in uniaxial compression so that these two methods could be compared. Figure 52 shows that

58

in all of the tests the steel softened completely within 10s, apart from in the torsion tests at CEIT where

the kinetics were an order of magnitude slower. The results from the two Gleeble machines at Tata and

AM were in good agreement. Comparison of the results from the torsion double hit tests at CEIT and

CRM revealed similar differences between the machines as described for the round robin test on steel

C1Mn1Nb7. The CRM torsion DH results are in line with the uniaxial compression data, although the

C1Mn1Nb7 round robin test suggested that the temperatures in the CRM torsion test may be higher

than the target temperature so the kinetics will be faster than might be expected at 1050°C. The t50

values and Avrami n-values derived from the softening data from all the round robin tests are

summarised in Table 29.

Partner

Measured

austenite grain

size (µm)

Tata 95

CEIT 96

CRM 107

AM -

0.0

0.2

0.4

0.6

0.8

1.0

0.01 0.1 1 10 100 1000

Time (s)

Softened fraction

Tata uniaxial DH

AM uniaxial DH

Tata uniaxial SR

AM uniaxial SR

CRM torsion DH

CEIT torsion DH

Table 28: Initial austenite grain size in

steel C2Mn1Nb3 measured at each

partner

Figure 52: Overall results of softening kinetics from round

robin exercise on steel C2Mn1Nb3

Table 29: Avrami n-values and t50 times derived from all round robin tests at each partner

1. C1Mn1Nb7 2. C2Mn1Nb3

Partner t50 (s) n t50 (s) n

CEIT DH: 11.69 DH: 0.97 DH: 5.83 DH: 1.0

CRM DH: 2.3 DH: 0.97 DH: 1.26 DH: 0.69

AM DH: 12.5 DH: 0.65 SR: 1.8 ; DH: 1.0 SR: 1.35 ; DH: 1.0

Tata - - SR: 0.96; DH: 1.25 SR: 1.30; DH: 0.78

2.3.3.4 Task 3.3: Solute drag effect on dynamic recrystallisation kinetics

Effect of Si

In the course of a hot deformation process, when the total dislocation density is high enough, dynamic

recrystallisation can appear. This metallurgical mechanism contributes to the steel softening during the

deformation. This softening proceeds by the development of new grains, with a lower dislocation

density than the deformed grains. Dynamic recrystallisation appears when the energy accumulated in

the steel during deformation is high enough, or in other words when the stress is higher than a critical

value. According to the literature, this critical energy level depends on deformation temperature, grain

size and strain rate. It is also considered to be dependent on steel chemical analysis. Practically, the

critical strain for the initiation of dynamic recrystallisation is determined from the peak stress or the

maximum stress level. This value and its corresponding peak strain are two characteristics of a stress-

strain curve when dynamic recrystallisation occurs and is function of the so called Zener-Hollomon

parameter.

CRM experiments were performed by single hit hot torsion to study the effect of silicon on the critical

strain for dynamic recrystallisation. Torsion tests were performed for several conditions of deformation

temperatures and strain rates according to the work programme defined in Task 3.1 (see Table 13).

From experimental stress strain curves, main coefficients describing dynamic recrystallisation like peak

59

strain and critical strain were determined following the second derivative method fully described in

reference [17]. The overall methodology followed to analyse experimental curves can be summarised

according to the charts given in Figure 53.

Figure 53: DRX study - analysis of flow stress experimental curves

From the experimental stress-strain curve, the elastic part of the curves was firstly removed considering

the yield strain as 2% of the total strain. The plastic part of the curve was fitted using a 9th order

polynomial function to smooth the curve which allows performing differentiation analysis required to

determine coefficients of DRX. By plotting the strain hardening rate (Theta) as function of strain or

stress (Figure 53b), peak strain and peak stress can be determined. The estimation of the critical stress

is obtained by plotting the second derivative of the strain hardening rate with regard to stress (d²Theta

/d²stress) as a function of stress. The critical stress is determined for a zero value of the second

derivative of the strain hardening rate (i.e. for d²Theta /d²stress = 0). It corresponds also to the

minimum of first derivative of the strain hardening rate plotted as function of stress (Figure 53d).

Finally, saturation stress was determined from a linear regression analysis of the function (Theta x

stress)=F(stress²), which can be described by the equation in Figure 53c. The knowledge of the slope

and the Y-intercept allows the saturation stress to be determined. Results obtained following this

methodology are summarized in Table 30. The effect of the deformation temperature and the strain rate

on the peak stress value is plotted in Figure 54. Peak stress increases with an increase of the strain rate

and a decrease of the deformation temperature. The results are analysed in Task 5.3.

Figure 54: Effect of temperature and strain rate on peak stress for DRX in Si steels

60

Table 30: Results - DRX study on Si steels

Effect of Mn

The testing for DRX studies at AM were carried out on grades C1Mn1Nb7 and C1Mn2Nb7. The

conditions for the hot torsion tests were testing temperatures of 1000, 1050 and 1100°C and strain rates

0.1 and 1/s. From the flow curves, the characteristic parameters related to DRX were obtained: peak

stress σp and peak strain εp and εss representing the strain at the onset of the steady state and σss the

stress achieved in that state. The critical strain εc for DRX was calculated from the downward inflexion

point in the dσ/dε-σ experimental curve as described by Davenport [18].

Figure 55 shows the flow curves obtained under the selected testing conditions for C1Mn1Nb7 and

C1Mn2Nb7. The DRX parameters derived from these curves are shown in Table 31. The flow curves

obtained under condition of strain rate 1/s led to a rather clear determination of all DRX parameters

although no steady state was reached at lower temperatures. As shown in Figure 56, the experimental

data under these conditions led to rather simple curves of dσ/dε-σ from which the critical stress and

therefore the critical strain was determined. The tests performed at 0.1/s led to a significantly increased

level of noise in the reported values of equivalent stress making the determination of critical strain

nearly impossible. The origin of this level of noise is yet to be clarified. Further tests would be needed

with a reduced data acquisition frequency to properly identify the source of variations.

Table 31: Critical Parameters for Dynamic Recrystallisation for C1Mn1Nb7 and C1Mn2Nb7

Grade D°

(µm)

T

(°C)

εεεε (1/s)

Z σσσσc

(MPa) εεεεc

σσσσp

(MPa) εεεεp

σσσσss

(MPa) εεεεss

C1Mn1Nb7 128 1100 0,1 2,32E+11 82 0,60 64 1,51

C1Mn1Nb7 128 1050 0,1 6,79E+11 93 0,62 77 1,61

C1Mn1Nb7 128 1000 0,1 2,17E+12 119 1,51

C1Mn1Nb7 128 1100 1 2,32E+12 116 0,47 117 0,55 102 1,36

C1Mn1Nb7 128 1050 1 6,79E+12 139,3 0,73 140 0,92

C1Mn1Nb7 128 1000 1 2,17E+13 160 1,07 163 1,26

C1Mn2Nb7 108 1100 0,1 2,32E+11 72 0,60 56 1,14

C1Mn2Nb7 108 1050 0,1 6,79E+11 93 0,68 79 1,13

C1Mn2Nb7 108 1100 1 2,32E+12 107 0,43 108 0,52 95 1,11

C1Mn2Nb7 108 1050 1 6,79E+12 124 0,55 125 0,68 112 1,35

C1Mn2Nb7 108 1000 1 2,17E+13 168 1,06 169 1,25

61

0

20

40

60

80

100

120

140

160

180

0 0,2 0,4 0,6 0,8 1 1,2 1,4 1,6 1,8 2

Strain

Str

ess

, M

Pa

C1Mn1Nb7 1050°C 0.1/s C1Mn1Nb7 1050°C 1/s

C1Mn1Nb7 1000°C 1/s C1Mn1Nb7 1100°C 1/s

C1Mn1Nb7 - 1100°C - 0.1/s C1Mn1Nb7 - 1000°C - 0.1/s

0

20

40

60

80

100

120

140

160

180

0 0,2 0,4 0,6 0,8 1 1,2 1,4 1,6 1,8 2

Strain

Str

ess

, M

Pa

C1Mn2Nb7 1100°C 1/s C1mN2Nb7 1050°C 1/s

C1Mn2Nb7 1000°C 1/s C1Mn2Nb7 - 1050°C - 0.1/s

C1Mn2Nb7 - 1100°C - 0.1/s

(a) C1Mn1Nb7 (b) C1Mn2Nb7

Figure 55: Flow curves describing DRX behavior for Nb7 steels

It is known that the onset of DRX during hot deformation occurs when the critical strain εc is reached

and this is related to the peak strain εp following relationships of the type εc =A εp. Values ranging

between 0.65 and 0.85 have been reported for the coefficient A in different materials [19]. From the

stress strain curves at 1/s the values of critical and peak strains have been derived and Figure 57 shows

the relationship between this parameters from which a coefficient A=0.856 was derived.

---- C1Mn1Nb7 - 1100°C - 1/s

-20

0

20

40

60

80

100

120

100 101 102 103 104 105 106 107 108 109 110

Stress, MPa

d/d

e

σc

0

0,2

0,4

0,6

0,8

1

1,2

1,4

0 0,2 0,4 0,6 0,8 1 1,2

εc

p

C1Mn1Nb7 - 1/s

C1Mn2Nb7 - 1/s

Figure 56: Determination of critical stress and

strain for DRX

Figure 57: Relationship between critical and peak

strain (n=0.856)

These characteristic strains depend on strain rate and temperature, both variables combined in the

Zener-Hollomon parameter Z, and on the prior austenite grain size D0. Usually the peak strain is related

to these parameters by relationships of the type εp=AD0mZ

p where m and p are coefficients taking

different values for different materials. Figure 58 shows the relationship between εp and Z values for

the tested conditions leading to values of p between 0.13 and 0.16, in agreement with values reported in

the literature for CMn and microalloyed steels ranging between 0.137 and 0.23 [21].

62

0,1

1

10

1,00E+11 1,00E+12 1,00E+13 1,00E+14

Z (s-1)

p

C1Mn1Nb7 - D°128µm

C1Mn2Nb7 - D°108µm

Figure 58: Evolution of εp values with Zener-Hollomon

parameter for C1Mn1Nb7 and C1Mn2Nb7

2.3.3.5 Task 3.4: Grain growth kinetics

This task aimed to investigate the austenite grain growth kinetics during hold times in the deformation

schedule during thermomechanically controlled rolling. Plates are often held for times of up to 15

minutes in some rolling schedules to lower the plate temperature before entry into the finishing mill.

This enables better mechanical properties to be achieved by control of the microstructure. Current

equations [8] predict a large amount of grain growth at hold temperatures in Nb microalloyed steels,

leading to large austenite grain sizes at the start of finish rolling. Previous Gleeble tests within Tata

Steel on a limited number of steels indicated that very little growth was actually occurring and the

equations needed refining. A series of tests was therefore carried out on steels C1Mn1, C1Mn1Nb1 and

C1Mn1Nb3 to obtain extra data to confirm these results. The reheating conditions were selected to

obtain an initial austenite grain size of ~100µm as in Task 3.2, and then deformation tests were

performed at temperatures of 1150, 1050 and 950°C and strains of 0.2 and 0.1, with hold times as

detailed in Table 32. Samples were held after deformation for times of up to 900s before quenching

with water to martensite so that the prior austenite grain size could be determined. At least three

different holding times were chosen per deformation condition, so that any change in austenite grain

size could be observed. The measured time for 95% recrystallisation was determined from the stress

relaxation tests in Task 3.2. The actual time available for grain growth during the hold time was then

calculated. The grain size results are presented in Task 4.2.

Multi-hit tests were also performed on steel C1Mn1 to see if refinement of the austenite grain size by

pre-deformation affected the subsequent grain growth. Tests were performed with 3 hits of 0.2 strain at

1200, 1175 and 1150°C, or 1150, 1100 and 1050°C before holding at a constant temperature for up to

900s after the final deformation.

Table 32: Grain growth tests performed on steels C1Mn1, C1Mn1Nb1 and C1Mn1Nb3

Hold times (s) Deformation

temperature (°C) Strain (-)

C1Mn1 C1Mn1Nb1 C1Mn1Nb3

1150 0.2 5, 30, 100, 300, 900 3.5, 30, 300 3, 100, 300

1050 0.2 1, 7, 100, 300, 900 5, 30, 300 16, 100, 300

1050 0.1 5, 23, 100, 300, 900 2, 22, 300 5, 88, 300

950 0.2 5, 44, 100, 300, 900 3, 33, 300 30,100,900

1200, 1175, 1150 0.2 100, 900 - -

1150, 1100, 1050 0.2 100, 900 - -

63

2.3.3.6 Task 3.5: Strain induced precipitation effects

Effect of Si

Multipass hot torsion tests coupled with single hit hot torsion tests were performed according to the

work programme defined in task 3.1, see Figure 9 and Table 14. Single hit hot torsion tests were

performed on steel grade C2Mn2Si0Nb3 and C2Mn2Si2Nb3 to evaluate the influence of 2%Si on Nb

precipitation. Trials were performed considering on one hand a single deformation temperature

(Tdef=1000°C) and on the other hand a single deformation level (strain=0.2). Holding times of 10s,

100s, 1000s and 10000s after the deformation were tested. Furthermore, some samples were quenched

before applying the deformation in order to define the initial precipitation state of niobium.

Quantification of Nb(C,N) precipitates was performed in Task 4.3.

Multi hit hot torsion tests were performed on steel grades C2Mn2Si1, C2Mn2Si2, C2Mn2Si2Nb3 and

C2Mn2Si2Nb7. The effect of the interpass time, the deformation level and the Si/Nb content was

investigated (see Table 14). The mean flow stress analysis coupled to the anisothermal softening

fraction concept was applied to stress strain curves of the multipass deformation test to obtain critical

recrystallisation temperatures and to study interactions between recrystallisation and niobium

precipitation. Figure 59 shows an example of stress strain curve evolution during multipass hot torsion

test for the C2Mn2Si2Nb3 steel grade. The curve given in Figure 59 was obtained for a nominal strain

of 0.3 per pass, an interpass time (IPT) of 50s and a strain rate of 1s-1. The first deformation was

applied at 1200°C. Other deformations were applied at 20°C intervals. Mean flow stress analysis

results are given in Task 3.6. The Von Mises effective stress and strain were calculated from the

measured torque and torsion angles.

Figure 59: Stress strain curves - Multipass hot torsion test on C2Mn2Si2Nb3 steel

The increase of stress as temperature drops is clearly obvious. A higher tendency towards hardening

was observed between pass number 9 and 10 meaning that another hardening effect than temperature

appears. This change in material flow behaviour is attributed to the end of the full austenite

recrystallisation.

Effect of Al

Figure 60 shows the softening curves obtained for the C2Mn2Al1Nb3, C2Mn2Al2Nb3 and

C2Mn2Al2Nb7 steels at the different deformation temperatures investigated, while Figure 61 displays

the softening curves obtained for these steels at the same deformation conditions. The figures show that

although for all the Nb microalloyed steels the fractional softening data obtained after deformation at

1065ºC can also be fitted by an Avrami type curve, at lowest temperatures the softening is largely

retarded and does not complete in the range of interpass times investigated. In the case of Nb

microalloyed steels, this strong retardation effect is usually attributed to the strain induced-

precipitation of Nb(C,N) particles [28]. It has been reported that when this takes place, these

64

precipitates exert a pinning effect on grain boundaries retarding or even completely stopping softening

processes. In these cases a temporary stop in the softening curves called "plateau" occurs. Sometimes,

after a given period of time precipitate growth and/or coarsening can take place leading to a loss of

their retarding effect and allowing softening to increase again. Figure 60 shows that the softening

corresponding to all the Nb steels below 1000ºC can be fitted to this type of behaviour. However, in

order to investigate the microstructural mechanisms leading to this behaviour C2Mn2Al1Nb3,

C2Mn2Al2Nb3 and C2Mn2Al2Nb7 specimens were quenched at different conditions and their

microstructure and precipitation state analysed. The results will be discussed in WP4.

0

0.2

0.4

0.6

0.8

1

0.1 1 10 100 1000 10000

Fractional Softening

t (s)

T=1065ºC

T=1000ºC

T=925ºC

T=900ºC

C2Mn2Al1Nb3

ε=0.35

(a) C2Mn2Al1Nb3

0

0.2

0.4

0.6

0.8

1

0.1 1 10 100 1000 10000

Fractional Softening

t(s)

T=1065ºC

T=1000ºC

T=965ºC

T=925ºC

C2Mn2Al2Nb3

ε=0.35

(b) C2Mn2Al2Nb3

0

0.2

0.4

0.6

0.8

1

0.1 1 10 100 1000 10000

Fractional Softening

t (s)

T=1065ºC

T=1000ºC

T=965ºC

T=925ºC

C2Mn2Al2Nb7

ε=0.35

(c) C2Mn2Al2Nb7

Figure 60: Fractional softening experimental data obtained for the Al steels at different deformation

temperatures.

65

0

0.2

0.4

0.6

0.8

1

0.1 1 10 100 1000 10000

Fractional Softening

t (s)

C2Mn2Al1Nb3

C2Mn2Al2Nb3

C2Mn2Al2Nb7

ε=0.35T=1065ºC

(56 µm)

(65 µm)

(102 µm)

(a) 1065ºC

0

0.2

0.4

0.6

0.8

1

0.1 1 10 100 1000 10000

Fractional Softening

t (s)

C2Mn2Al1Nb3

C2Mn2Al2Nb3

C2Mn2Al2Nb7

ε=0.35T=1000ºC

(102 µm)

(65 µm)

(56 µm)

(b) 1000ºC

0

0.2

0.4

0.6

0.8

1

0.1 1 10 100 1000 10000

Fractional Softening

t (s)

C2Mn2Al2Nb3

C2Mn2Al2Nb7

ε=0.35

T=965ºC

(65 µm)

(56 µm)

(c) 965ºC

0

0.2

0.4

0.6

0.8

1

0.1 1 10 100 1000 10000

Fractional Softening

t (s)

C2Mn2Al1Nb3

C2Mn2Al2Nb3

C2Mn2Al2Nb7

ε=0.35T=925ºC

(102 µm)

(65 µm)

(56 µm)

(d) 925ºC

Figure 61: Fractional softening obtained for the AlNb steels at different temperatures.

Effect of Mn

Single hit isothermal torsion tests followed by water quenching after different holding times were

performed in order to characterize the strain induced precipitation in Mn-Nb microalloyed steels under

the conditions tested in the study of static softening (Task 3.2). From the water quenched samples a

cylinder 40mm long was extracted from the working length of the sample (total length of 50mm) and

pickled in HCl solution at 80°C to remove the thin film of scale formed during quenching and storing.

The cylinders were subjected to electrolytic dissolution and ICP spectroscopy. The length of the

cylinders of 40mm leads to the dissolution of a critical amount of 1.5gr needed for accurate ICP

measurements corresponding to a depth of dissolution not exceeding 250µm therefore focusing the ICP

measurement in the subsurface, i.e. the area of interest in torsion testing.

The testing was carried out on grades C1Mn1Nb7 and C1Mn2Nb7 and the conditions for the hot

torsion tests corresponded to those performed in double hit tests at testing temperatures of 1050, 1000

and 950°C, applied strain ε=0.35 and strain rate 1/s. The initial grain size was fixed by the application

of the roughing step at 1150°C with ε=0.8. The initial state of precipitates was characterised for the

Nb7 steel by analysis of a quenched sample just after reheating and after roughing deformation and

cooling down to the deformation temperature. The holding times after deformation and before water

quenching were defined according to conditions derived from the softening curves in Task 3.2. Table

33 presents the single hit test conditions. The results of the precipitate quantification are presented in

Task 4.3.

66

Table 33: Torsion Single Hit tests performed for precipitation studies on MnNb steels

Quench Time (s)

Grade Temp

(°C)

Initial

Grain

Size

(µm)

Strain Ps(s) Pf (s) Rplateau

t1 t2 t3 t4

C1Mn2Nb7 1250 1*

C1Mn2Nb7 1050 106 0 1*

C1Mn2Nb7 1050 106 0,35 2 10 40 100

C1Mn2Nb7 950 106 0,35 4 >10 0,23 1 2 5 10

C1Mn1Nb7 1050 128 0,35 2 10 40 100

C1Mn1Nb7 1000 128 0.35 3,5 84 0,25 1 10

C1Mn1Nb7 950 128 0,35 3 >100 0,21 1 5 10

2.3.3.7 Task 3.6: Determination of critical temperatures for recrystallisation

There is no single temperature at which recrystallisation suddenly ceases, but rather a temperature

range between the lowest temperature above which recrystallisation between passes is complete (85 or

95% recrystallisation criteria are used), the recrystallisation limit temperature (RLT), and the highest

temperature at which recrystallisation is completely absent (usually taken as 5% recrystallised

fraction), the recrystallisation stop temperature (RST). Between these limits, there is a temperature

regime within which partial recrystallisation occurs. Multi-hit hot torsion tests were performed to

determine the critical recrystallisation temperatures for the project steels: the no-recrystallisation

temperature (Tnr), RLT and the RST. Figure 62(a) shows an example of the stress-strain curves

obtained in a multipass torsion test on steel C2Mn2Al2Nb3 with a strain per pass of ε=0.3 and an

interpass time of tip=100 s.

From the figure, the Mean Flow Stress (MFS, the area under strain-stress curve divided by the pass

strain) corresponding to each pass was calculated for each deformation pass by numerical integration

and is plotted against the temperature in Figure 62(b). Four different regions can be clearly

distinguished in both figures: Region I, where complete recrystallisation between passes takes place

and the stress increase from pass to pass is only due to the temperature drop; Region II, where

recrystallisation between passes is inhibited and as a result the hardening level is increased; Region III

where ferrite transformation starts and consequently there is some degree of softening, and finally

Region IV, where austenite to ferrite transformation is completed and ferrite hardening starts [22].

Following the standard procedure [11,22], the non-recrystallisation temperature (Tnr) was determined

as the intersection between the regression lines of the points corresponding to regions I and II in Figure

62(b). The austenite to ferrite phase transformation start (Ar3) and finish (Ar1) temperatures were also

determined from the plots.

0

50

100

150

200

0 1 2 3 4 5 6

Strain

Stress (MPa)

Region I Region IIRegion III

(a) Stress-strain curves

0

50

100

150

200

75085095010501150

T (ºC)

Mean Flow Stress (MPa) Ar3=920ºC

Ar1=840ºC

Tnr=1022ºC

(b) Mean flow stress versus deformation temperature

Figure 62: Multipass torsion test results on C2Mn2Al2Nb3 steel, tip=100 s, ε per pass=0.3.

67

For each of the multipass tests carried out, the fractional softening level between deformation passes

was also calculated. As the interpass fractional softening must be determined under anisothermal

conditions, the following equation proposed by Liu et al. [23] was used:

100io

im

1io

io1i

yim

⋅−

−

=+

+

σσ

σ

σσσ

(%)FS (4)

where i

mσ is the maximum flow stress for pass ‘i’ at temperature Ti and 1i

y

+σ is the yield stress of pass

‘i+1’. Also, i

oσ and 1i

o

+σ are the yield stresses of the fully recrystallised material for passes ‘i’ and

‘i+1’. The stresses i

mσ and 1i

y

+σ are derived from the pass-to-pass flow curves, while i

oσ and 1i

o

+σ are

derived from the relationship between the yield stresses measured in the fully recrystallised initial

passes. The yield stresses are determined by the 2% offset method.

Effect of Nb

Torsion tests were performed by CEIT to determine the critical temperatures for recrystallisation (RLT,

RST and Tnr) in some of the Tata steels using the same conditions as the tests performed on the CEIT

series of Al treated steels. Plate material from steel C1Mn1Nb3 and C2Mn1Nb3 was supplied to CEIT

from which torsion samples were machined. Three tests were performed on each steel: at a strain of 0.3

with interpass times of 10s and 30s, and a strain of 0.1 with an interpass time of 30s. In this way, the

effect of both strain and interpass time on the critical temperatures could be investigated. Samples were

reheated to 1300°C to produce the required austenite grain size, followed by 24 deformations at 20°C

intervals between 1180 and 720°C. The mean flow stress (MFS) was calculated for each deformation

and plotted against temperature (Figure 63). Increasing the carbon content from 0.1 to 0.2 wt% did not

have a major effect on the MFS of the austenite, but affected the temperature at which the

transformation from austenite to ferrite occurred and thus the MFS in the 0.2C steel remained higher

for longer. Reducing the interpass time from 30s to 10s decreased the amount of time available for

recrystallisation, leading to more rapid strain accumulation in the austenite and a higher flow stress, in

both steels. The Tnr, Ar3 and Ar1 temperatures could be clearly identified from the changes in slope of

the plot.

Analysis of the softening between each pass, using equation (4), enabled the fractional softening plots

shown in Figure 64 to be constructed, from which the RST and RLT can be identified. Table 34

provides a summary of the critical temperatures for steels C1Mn1Nb3 and C2Mn1Nb3. The Tnr and

RLT increased with decreasing interpass time, and were slightly increased by increasing the carbon

content from 0.1 to 0.2 wt% for the same interpass time. The Ar3 was lower in the higher carbon steel

as would be expected. Figure 64 also shows that incomplete softening was determined for every pass in

both steels when a strain of 0.1 was applied and unlike the behaviour at 0.3 strain, the fraction softened

did not decrease steadily with temperature. Instead it increased and decreased in consecutive passes.

This could be due to the applied strain being too small to initiate recrystallisation in one pass, so that

strain is accumulated and the fraction softened decreases. In the next pass, the total applied plus

accumulated strain becomes large enough for some recrystallisation to occur, so the fraction softened

increases again, and so on for subsequent passes.

Table 34: Critical temperatures from multipass torsion tests on steels C1Mn1Nb3 and C2Mn1Nb3

Steel Tsoak

(°C)

Total

passes

Tinitial

(°C)

Tfinal

(°C) ε tip

(s)

Cooling

rate

(°C/s)

Tnr

(°C)

Ar3

(°C)

Ar1

(°C)

RLT

(°C)

RST

(°C) 10 2 1048 800 740 1113 953

0.3 30 0.67 1035 820 740 1063 958 C2Mn1Nb3

0.1 30 0.67 800 740

10 2 1042 860 760 1085 946 0.3

30 0.67 1025 860 740 1063 932 C1Mn1Nb3

1300 24 1180 720

0.1 30 0.67 840 760

68

0

50

100

150

200

700800900100011001200

T (ºC)

Mean Flow Stress (MPa)

C1Mn1Nb3 def=0.3 tip=10s

C1Mn1Nb3 def=0.3 tip=30s

C1Mn1Nb3 def=0.1 tip=30s

Tnr=1025ºC

Tnr=1042ºC

Ar3=860ºC

Ar1=760ºC

Ar1=740ºC

Ar3=860ºC

Ar3=840ºC

Ar1=760ºC

(a) steel C1Mn1Nb3, effect of strain and interpass

time

0

50

100

150

200

700800900100011001200

T (ºC)

Mean Flow Stress (MPa)

C2Mn1Nb3 def=0.3 tip=10s

C2Mn1Nb3 def=0.3 tip=30s

C2Mn1Nb3 def=0.1 tip=30s

Tnr=1035ºC

Tnr=1048ºC

Ar3=800ºC Ar1=740ºC

Ar3=820ºC

Ar1=740ºCAr3=800ºC

(b) steel C2Mn1Nb3, effect of strain and interpass

time

Figure 63: Mean flow stress plots from multipass torsion tests on steels C1Mn1Nb3 and C2Mn1Nb3

0

20

40

60

80

100

120

800900100011001200

T (ºC)

FS (

%)

C1Mn1Nb3 def=0.3 tip=30s

C1Mn1Nb3 def=0.3 tip=10s

C1Mn1Nb3 def=0.1 tip=30s

Tnr=1025ºC

RLT=1063ºC

RST=932ºC

RLT=1105ºC

RST=946ºC

Tnr=1042ºC

(a) steel C1Mn1Nb3, effect of strain and interpass

time

0

20

40

60

80

100

120

800900100011001200

T (ºC)

FS

(%

)

C2Mn1Nb3 def=0.3 tip=30s

C2Mn1Nb3 def=0.3 tip=10s

C2Mn1Nb3 def=0.1 tip=30s

Tnr=1035ºC

Tnr=1048ºCRLT=1113ºC

RST=953ºC

RLT=1063ºC

RST=958ºC

(b) steel C2Mn1Nb3, effect of strain and interpass

time

Figure 64: Fractional softening plots from multipass torsion tests on steels C1Mn1Nb3 and C2Mn1Nb3

Effect of Si

Torsion specimens of the Si series of steels were first reheated to 1250°C for 5 min to have all Nb in

solid solution. Subsequently, samples were subjected to a series of consecutive deformations for

different conditions of deformations, inter-pass time and cooling rates, see Task 3.5 and Table 14. The

fraction softened plots indicating the RLT, RST and Tnr temperatures are shown in Figure 65 and the

critical temperatures are tabulated in Table 35.

69

(a) 0.3 strain, 10s interpass time

(b) 0.3 strain, 30s interpass time

(c) 0.3 strain, 50s interpass time

(d) 0.2 strain, 30s interpass time

(e) 0.5 strain, 30s interpass time

Figure 65: Fractional softening plots from multipass torsion tests on CRM Si steels .

Double arrow refers to the Tnr temperature

Table 35: Critical recrystallisation temperatures determined from multipass torsion tests on Si steels

70

Effect of Al

The MFS versus temperature graphs obtained for the Al steels investigated at varying interpass times

are displayed in Figure 66, while Figure 67 shows the influence of steel composition on the MFS plots.

Figure 66 denotes that for all the steels analysed decreasing interpass time leads to higher hardening

levels and also to a Tnr increase. This is in good agreement with the results reported in the literature

[22,27] and is related to the fact that increasing interpass time allows higher softening levels between

deformation passes to be reached.

0

50

100

150

200

250

300

75085095010501150

Mean Flow Stress(MPa)

T (ºC)

tip=5s

tip=30s

tip=100s

C2Mn2

Tnr=890ºC

Tnr=862ºC

Tnr=930ºC

(a)

0

50

100

150

200

250

300

75085095010501150Mean Flow Stress (MPa)

T (ºC)

tip=5s

tip=30s

tip=100s

Tnr=949ºC

Tnr=923ºC Tnr=887ºC

Ar3<800ºC

C2Mn2Al1 (b)

0

50

100

150

200

250

300

75085095010501150

Mean Flow Stress(MPa)

T (ºC)

tip=5s

tip=30s

tip=100s

Tnr=1056ºC

Tnr=1067ºCTnr=1064ºC

Ar3=920ºCAr1=820ºC

Ar3=940ºCAr3=920ºC

C2Mn2Al2

(c)

0

50

100

150

200

250

300

75085095010501150

Mean Flow Stress (MPa)

T (ºC)

tip=5s

tip=30s

tip=100s

Tnr=1029ºC

Tnr=1055ºC

Tnr=1010ºC

Ar3=820ºC

C2Mn2Al1Nb3 (d)

0

50

100

150

200

250

300

75085095010501150

Mean Flow Stress (MPa)

T (ºC)

tip=5s

tip=30s

tip=100s

Tnr=1061ºC

Tnr=1066ºC

Tnr=1022ºC

Ar3=920ºC

Ar3=940ºC

Ar1=820ºC

C2Mn2Al2Nb3

(e)

0

50

100

150

200

250

300

75085095010501150

Mean Flow Stress (MPa)

T (ºC)

tip=5s

tip=30s

tip=100s

Tnr=1066ºC

Tnr=1065ºC

Tnr=1028ºC

Ar3=920ºC

Ar3=940ºC

Ar1=820ºC

C2Mn2Al2Nb7

(f)

Figure 66: Mean Flow Stress (MFS) plotted against temperature at different interpass times for the

C2Mn2, C2Mn2Al and C2Mn2AlNb steels.

Figure 67 shows that the MFS and Tnr values were also affected by steel composition. However, the

effect is complex and depends on the microalloying addition type and level. At any interpass time the

flow stress was significantly increased by 1 and 2wt%Al addition. Similarly, 0.03%Nb addition to the

C2Mn2Al1 steel also resulted in a stress increase. However, Nb addition to the 2%Al steels produced a

71

lower effect. The figure also shows that 1%Al addition to the C2Mn2 steel resulted in a noticeable Tnr

increase. However, it is interesting to note that the effect was significantly enhanced by 2%Al addition.

The effect of Nb is also complex; 0.03%Nb addition to the 1%Al steel raised significantly the Tnr;

however, Nb addition to the 2%Al steels resulted in almost no effect.

0

50

100

150

200

250

300

7509501150

Mean Flow Stress (MPa)

T (ºC)

C2Mn2

C2Mn2Al1

C2Mn2Al2

C2Mn2Al1Nb3

C2Mn2Al2Nb3

C2Mn2Al2Nb7

Ar3=820ºC

Tnr=930ºC

Tnr=949ºC

Tnr=1066-1055ºC

Ar3=920ºC

Ar1=820ºC

tip=5s (a)

0

50

100

150

200

250

300

75085095010501150

Mean Flow Stress (MPa)

T (ºC)

C2Mn2

C2Mn2Al1

C2Mn2Al2

C2Mn2Al1Nb3

C2Mn2Al2Nb3

C2Mn2Al2Nb7

Tnr=923ºC

Tnr=1029ºC

Ar3=820ºC

Tnr=890ºC

Tnr=1067-1065ºC

Ar3=940ºC

tip=30s (b)

0

50

100

150

200

250

300

75085095010501150

Mean Flow Stress (MPa)

T (ºC)

C2Mn2

C2Mn2Al1

C2Mn2Al2

C2Mn2Al1Nb3

C2Mn2Al2Nb3

C2Mn2Al2Nb7

Tnr=1028-1022ºC

Ar3=920ºC

Ar1=820ºC

Tnr=1010ºC

Ar3=820ºC

Tnr=862ºC

Tnr=887ºC

Tnr=1064ºC

tip=100s (c)

Figure 67: Mean Flow Stress (MFS) plotted against temperature at the same

deformation conditions for the different Al steels.

The softening results obtained using equation (4) for the steels investigated are represented in Figure

68. From the figure, it can be observed that the softening data can be well-fitted to three linear

segments which intersect at the temperatures denoted as RLT and RST. The values of the Tnr are also

indicated. It should be noted that the Tnr temperature was always an intermediate value between these

two temperatures, although the longer the interpass time, the closer was the Tnr to the RLT value. In

good agreement with the results shown in Figure 66, longer interpass times led to an increase in the

softening levels and to a decrease in the RLT and RST temperatures.

Figure 69 illustrates the influence of steel composition on the anisothermal softening behaviour for an

interpass time of 30 s. It is evident that both increasing Al and/or Nb content led to a significant

increase in the RLT and RST. However, in good agreement with the results shown above, 2%Al

resulted in a larger increase than 1%Al, and 0.03%Nb addition to the 1%Al steel resulted in a higher

effect than Nb addition to the 2%Al steel.

Finally, the critical temperatures determined for all the multipass torsion tests on the Al steels have

been summarised in Table 36 and the Tnr and Ar3 temperatures plotted in Figure 70. The effect of steel

composition on the Tnr has already been mentioned. From Figure 70(a) it is also interesting to note

from that for the C2Mn2, C2Mn2Al1 and C2Mn2Al1Nb3 steels the Tnr tended to decrease with

interpass time, whereas for the C2Mn2Al2 steel it remained approximately constant. For the

72

C2Mn2Al2Nb steels, only for the longest interpass time (100s) a decrease was observed. Finally,

Figure 70(b) shows that increasing Al addition from 1 to 2% had a strong effect on the Ar3 temperature,

whereas the addition of Nb or the change in tests conditions did not really affect its value.

0

20

40

60

80

100

120

800900100011001200

FS (%)

T (ºC)

tip=5s

tip=30s

tip=100s

Tnr=930ºC

RLT=958ºC

RST=870ºC

Tnr=890ºC

RLT=901ºC

Tnr=862ºCRLT=873ºC

C2Mn2 (a)

0

20

40

60

80

100

120

800900100011001200

FS (%)

T (ºC)

tip=5s

tip=30s

tip=100s

Tnr=949ºC

RLT=1046ºC

RLT=939ºC

Tnr=923ºC

Tnr=887ºC

RLT=917ºC

C2Mn2Al1 (b)

0

20

40

60

80

100

120

800900100011001200

FS (%)

T (ºC)

tip=5s

tip=30s

tip=100s

Tnr=1056ºC

RST=946ºC

Tnr∼∼∼∼RLT=1067ºC

Tnr∼∼∼∼RLT=1064ºC

C2Mn2Al2 (c)

0

20

40

60

80

100

120

800900100011001200

FS (%)

T (ºC)

tip=5s

tip=30s

tip=100s RST=976ºC

Tnr=1055ºC

RLT=1060ºC

Tnr=1029ºC

RLT=1016ºC Tnr=1010ºC

RST=951ºC

C2Mn2Al1Nb3 (d)

0

20

40

60

80

100

120

800900100011001200

FS (%)

T (ºC)

tip=5s

tip=30s

tip=100s

RST=997ºC

Tnr=1061ºC

RLT=1107ºC

RST=980ºC

Tnr=1066ºC

RLT=1030ºC

Tnr=1022ºC

C2Mn2Al2Nb3 (e)

0

20

40

60

80

100

120

800900100011001200

FS (%)

T (ºC)

tip=5s

tip=30s

tip=100s

RST=1019ºC

Tnr=1066ºC

RLT=1101ºC

RST=997ºC

Tnr=1065ºC

RLT=1041ºC

Tnr=1028ºC

C2Mn2Al2Nb7 (f)

Figure 68: Anisothermal fractional softening plotted against temperature for the C2Mn2, C2Mn2Al and

C2Mn2AlNb steels at different interpass times.

73

0

20

40

60

80

100

120

800900100011001200

FS (%)

T (ºC)

C2Mn2

C2Mn2Al1

C2Mn2Al2

C2Mn2Al1Nb3

RLT=1060ºC

RLT=939ºC

Tnr=923ºC

Tnr=1029ºC

RST=951ºC

Tnr∼∼∼∼RLT=1067ºC

Tnr=890ºC

RLT=901ºC

tip=30s (a)

0

20

40

60

80

100

120

800900100011001200

FS (%)

T (ºC)

C2Mn2

C2Mn2Al2

C2Mn2Al2Nb3

C2Mn2Al2Nb7

RLT≈1100ºC

RST=997ºC-980ºC

Tnr≈1065ºC

Tnr≈RLT=1067ºC

Tnr=890ºC

RLT=901ºC

tip=30s (b)

Figure 69: Anisothermal fractional softening plotted against temperature for the different Al steels at

the same deformation conditions.

Table 36: Critical temperatures determined from the multipass torsion tests carried out on Al steels

Steel ε tip (s) Vcooling

(ºC/s)

Tnr

(ºC)

Ar3

(ºC)

Ar1

(ºC) RLT (ºC)

RST

(ºC)

Specimen

broken in

test

5 4 930 958 870 -

30 0.67 890 901 - - C2Mn2

100 0.2 862

<800 <800

873 - -

5 4 949 1046 - -

30 0.67 923 939 - - C2Mn2Al1

100 0.2 887

<800 <800

917 - -

5 4 1056 920 820 - 946 -

30 0.67 1067 940 - 1067 - X C2Mn2Al2

100 0.2 1064 920 820 1064 - -

5 4 1055 820 - 976 -

30 0.67 1029 820 1060 951 - C2Mn2Al1Nb3

100 0.2 1010 800

<800

1016 951 -

5 4 1061 920 - - 997 X

30 0.67 1066 940 - 1107 980 X C2Mn2Al2Nb3

100 0.2 1022 920 820 1030 - -

5 4 1066 920 - - 1019 X

30 0.67 1065 940 - 1101 980 X C2Mn2Al2Nb7

0.3

100 0.2 1028 920 820 1041 -

74

850

900

950

1000

1050

1100

0 50 100

TNR (ºC)

Interpass time (s)

C2Mn2

C2Mn2Al1

C2Mn2Al2

C2Mn2Al1Nb3

C2Mn2Al2Nb3

C2Mn2Al2Nb7

(a) Tnr temperatures

700

750

800

850

900

950

1000

0 50 100

Ar3

Interpass time (s)

C2Mn2Al2

C2Mn2Al2Nb3

C2Mn2Al2Nb7

C2Mn2Al1Nb3

(b) Ar3 temperatures

Figure 70: Tnr and Ar3 temperatures obtained for the different steels.

2.3.4 WP4: Microstructure analysis

The objectives of this work package were:

• Quantification of the following microstructural parameters after different thermomechanical

treatments in WP3 and WP6:

o Recrystallised austenite fraction

o Mean austenite grain size and grain size distribution

o Amount of Nb in solution/precipitate form

o Type, volume fraction and size of microalloy precipitates

The microstructure of torsion specimens of the Al steels quenched at different conditions was

examined by Optical Microscopy and Transmission Electron Microscopy. The torsion specimens were

examined at a section corresponding to 0.9 of the outside radius of the specimen, known as the sub-

surface plane (Figure 71). Because of the proximity of this plane to the surface of the sample, the strain

and strain rate can be considered similar to those calculated for the surface. For conventional Optical

Microscopy analysis, the specimens were prepared by the classical techniques of polishing and etching.

The austenite grain boundaries were revealed using an aqueous solution of picric acid while 2% Nital

was employed in the cases in which ferrite was present. The microstructure analysis included the

determination of average grain sizes and grain size distributions as well as the quantification of ferrite

volume fractions from the optical micrographs. In order to determine the austenite grain sizes, the mean

equivalent diameter parameter was measured with the help of the Leica QWin v.2.3 image analysis

software. Micrographs were taken from the etched specimens and the grain boundaries were traced

onto acetates so that the software was able to detect them. The software calculates the area

corresponding to each grain and then it assigns to each grain an equivalent diameter, which is the

diameter of the circle with equal area. The average of all the diameters measured is known as the mean

equivalent diameter. The software also provides the grain size distribution measured in each of the

cases.

MicrographSub-Surface Section0.9R

(Direction of plastic flow)

Figure 71: Section of torsion specimen for metallographic study. Sub-surface section (0.9R),

where R is the radius of the specimen.

75

2.3.4.1 Task 4.1: Quantification of recrystallised fraction

Effect of Al

In order to analyse the recrystallised fraction evolution in the Al steels, several specimens of the

C2Mn2Al1 steel were quenched at different softening levels after deformation at 1065ºC with a pass

strain of ε=0.35. Figure 72 displays the mechanical softening curve corresponding to these conditions

and the holding times at which quenching treatments were performed.

0

0.2

0.4

0.6

0.8

1

0.1 1 10 100 1000

t (s)

Fractional Softening

2 s

5 s

30 s

Figure 72: Softening curve determined for the C2Mn2Al1 steel deformed at TDEF=1065ºC, ε=0.35. The

times at which quenching treatments were performed are also indicated.

Figure 73 displays micrographs corresponding to the initial austenite grain size (Figure 73(a)) and to

the quenched specimens (Figure 73(b-d)). Although other parameters, such as the elongation in the

deformation direction or the grain boundary curvature, can help to differentiate recrystallised grains

from those which remain unrecrystallised, in this case the similar size of the initial and recrystallised

grains led to considerable ambiguity in the detection of the recrystallised grains. The recrystallised

fraction estimated by quantitative metallography in each of the cases is indicated in the figure. At the

first softening stages after deformation (t=2 s, Figure 73(b)) a significant amount of small nuclei were

present in the microstructure, which indicates static recrystallisation onset. As recrystallisation

progressed (Figure 73(c)) these new grains grew until a completely recrystallised microstructure was

attained (Figure 73(d)). It can also be noted that the average grain size obtained after complete

recrystallisation, 61.7±2.7 µm, was slightly refined compared to the initial austenite grain size, 100±4

µm.

Figure 74 shows the mechanical softening data together with the metallographic measurements of

recrystallised fraction. It is evident that the metallographic measurements tend to be below the data

determined from the double hit torsion tests, especially for the shortest interpass times. The reasons for

this discrepancy are not clear. Although this can be attributed to the difficulty of the quantitative

recrystallisation measurements, some authors suggest that recovery processes can also have a

contribution on the softening data determined from the double hit torsion tests, being this especially

significant at the first softening stages [29].

76

(a) Initial microstructure, D0=98.5±5 µm.

(b) t=2 s, XREX∼2.4±0.6%

(c) t=5 s, XREX∼34.8±1.5%

(d) t=30 s, XREX∼100%, DSRX=61.7±2.7 µm

Figure 73: Microstructures obtained for the C2Mn2Al1 steel in the soaked condition (a) and after

deformation at 1065ºC and holding for different times. The recrystallised fraction determined by

quantitative metallography is also indicated.

0

0.2

0.4

0.6

0.8

1

0.1 1 10 100 1000

t (s)

Fractional Softening

Torsion Data

Metallographic measurements

Figure 74: Mechanical fractional softening data together with the metallographic measurements of

recrystallised fraction. C2Mn2Al1, TDEF=1065ºC, ε=0.35.

77

Effect of Mn and Nb

Metallographic technique involving chemical etching with Bechet-Beaujard agent (Picric acid solution

+ Teepol) has been applied on a series of torsion samples subjected to water quench after isothermal

single hit deformation and holding times representing different softening states with R values between

0 and 0.6 as derived from double hit torsion tests. Figure 75 shows representative micrographs for

C1Mn2 and C1Mn2Nb3 after deformation at 1000°C with an applied strain of 0.35. It can be noted that

the applied etchant has succeeded in revealing prior austenite grain boundaries. Nevertheless a large

number of limitations were identified for application of this approach for quantitative analysis of

recrystallised fractions: i) the quality of the contrast achieved by this etching was in general rather poor

and varied significantly from grade to grade, ii) the relatively large initial grain sizes limited the

magnification applied in the optical analysis in order to cover a large number of grains therefore

limiting the capacity to properly identify small recrystallised grains, iii) the efficiency of the etching

was quite random rendering the metallographic analysis time intensive, iv) the estimation of the

recrystallised fraction relied strongly on the operator criteria and interpretation rending the estimation

significantly prone to errors. As a consequence of these limitations, a reliable quantitative analysis and

an accurate estimation of the recrystallised fraction was considered not possible using this

methodology. The decision was taken at AM to develop a quantitative methodology for XRex

determination based on the application of software for the reconstruction of prior austenite structures

from EBSD maps characterising the martensitic structure of water quenched samples.

C1Mn2 – 1000°C – ε 0.35 – D°124µm – t=1s ( RDH=0.35) C1Mn2 – 1000°C – ε 0.35 – D°124µm - t=3s ( RDH=0.55)

C1Mn2Nb3 – 1000°C – ε 0.35 – D°127µm - t=1s ( RDH=0.02)

C1Mn2Nb3 – 1000°C – ε 0.35 – D°127µm – t=10s ( RDH=0.42)

Figure 75: Chemical Etching revealing austenite grain boundaries from quenched torsion samples

78

Preliminary Tests: Application of EBSD Reconstruction Software for revealing austenite structures

EBSD reconstruction software have been developed by several research institutes in recent times [20],

however their application for quantitative analysis of recrystallised fractions has not yet been reported.

The reconstruction technique is based on the fact that the martensitic transformation occurs following

preferred orientation relationship (OR) with the parent austenite of the type Kurdjumov-Sachs (KS),

Nishishama-Wasserman (N-W) or Greninger-Troiano (GT). From the orientation of the variants

identified in the maps of martensitic structures the orientation of potential parent austenite grains can

be determined. The reconstruction is therefore proposed by finding in the martensitic microstructures

groups of at least four variants having the same parent in common. From this group of variants the

nuclei of potential parents are identified and the software induces the propagation of these nuclei to

complete the reconstruction. The application of this software available at AM has been tried on

quenched samples from single hit tests in this project The conditions selected for running the software

were i) GT orientation relationship and ii) angle tolerance of +/-5° with respect to theoretical OR. An

approach was adopted for the analysis of results considering the mean grain misorientation rather than

the actual dispersion of misorientation within grains.

For a first application of this technique, a series of single hit tests followed by water quench were

performed in torsion on grade C1Mn2Nb3. The conditions of the tests were a deformation temperature

of 1100°C, an applied strain of 0.35, strain rate of 1/s and initial grain size of 128µm. The holding

times were 1s, 3s and 10s. Previous double hit tests under these conditions were performed leading to a

range of softening from 0.3 to 0.9. Chemical etching was performed on the water quenched sample in

order to reveal the prior austenite structure and adopting these micrographs as references for assessing

the validity of the EBSD reconstruction. EBSD maps were obtained adopting a step size of 0.4µm, the

size of the maps corresponded to a magnification of 200X.

Figure 76 shows the reconstructed EBSD maps in comparison with representative micrographs

obtained by chemical etching although not in the same zone. The original EBSD maps were

characterized by a rather low indexation rate in the range 55-70%, the software extended the

reconstruction leading to indexation rates well above 85%. It can be seen that the reconstructed maps

presented strong similarities with the corresponding optical micrographs both in terms of grain size and

grain shape. This was considered a first validation of the application of EBSD reconstruction technique

for revealing the prior austenite structure. This first analysis, however, was limited to a qualitative

assessment since it involved a limited amount of optical micrographs and maps. Nevertheless the

application of this technique was pursued for exploring the possibility of quantifying the recrystallised

fraction.

79

Chemical Etching EBSD Reconstruction

t=1s

t=3s (R 0.63)

t=10s (R 0.88)

Figure 76: Comparison of Optical Micrographs and EBSD reconstructed maps for C1Mn2Nb3 – 1100°C –

ε 0.35

=200 µm; Copy of BC; Step=0.4 µm; Grid1561x1171

=200 µm; Copy of BC; Step=0.4 µm; Grid1561x1171

=200 µm; Copy of BC; Step=1.6 µm; Grid386x314

80

Mean Grain Local Misorientation Φ≤3° Mean Grain Local Misorientation Φ>3°

t=1s

ΣAi(Φ≤3)/ΣAi = 0,32

t=3s

ΣAi(Φ≤3)/ΣAi = 0,64 (R=0.63)

t=10s

ΣAi(Φ≤3)/ΣAi = 0,90 (R=0,88)

Figure 77: Application of Mean Local Misorientation Criterion for estimating recrystallised fraction in

C1Mn2Nb3 – 1100°C – ε 0.35

Preliminary Tests: Development of a criterion for XReX determination from EBSD reconstructed maps

In order to distinguish between recrystallised and non recrystallised grains three main microstructural

parameters were analysed: i) mean misorientation angle in the reconstructed grain as it is assumed that

new recrystallised grain will be characterised by a low mean misorientation angle while deformed non-

recrystallised grains would present higher mean misorientations; ii) grain size in terms of circle

equivalent diameter (dceq) as large grains comparable with the initial grain sizes could be considered

=200 µm; MeanMis; Step=0.4 µm; Grid1561x1171=200 µm; MeanMis; Step=0.4 µm; Grid1561x1171

=200 µm; MeanMis; Step=0.4 µm; Grid1561x1171=200 µm; MeanMis; Step=0.4 µm; Grid1561x1171

=200 µm; MeanMis; Step=1.6 µm; Grid386x314=200 µm; Copy of MeanMis; Step=1.6 µm; Grid386x314

81

non- recrystallised while small grains could be associated to recrystallised grains. A limitation of this

hypothesis is that the initial grain size distributions presented in Task 4.2 were significantly wide

covering the range of small grain sizes typical of recrystallised structures, iii) grain shape as lower

shape factors were expected for recrystallised grains. Analysis of the maps obtained in the preliminary

tests showed that the first parameter, mean misorientation angle, was the most sensitive to variations in

the level of softening of the microstructures.

Therefore, a first attempt for establishing a criterion was made simply based on the mean

misorientation angle. This criterion proposes that all identified grains with a mean misorientation angle

equal to or lower than 3° (φ≤3°) are considered recrystallised grains while those with mean

misorientation angle higher than 3° (φ≥3°) are considered non-recrystallised. The recrystallised fraction

is estimated as the ratio between the area corresponding to recrystallised grains to the total area

considered in the map (XReX=ΣAi(Φ≤3)/ΣAi). Figure 77 shows the reconstructed maps already

presented in Figure 76 but distinguishing with a colour code between those grains considered

recrystallised in tones of yellow to red from those in blue tones considered non-recrystallised. Values

of XReX=0.32, XReX=0.64 and XReX=0.90 were obtained for 1s, 3s and 10s respectively. Figure 78

compares the estimated recrystallised fraction from EBSD reconstruction with the softening values

determined for the test conditions by double hit torsion tests. A remarkably good agreement was found

between the softening and recrystallised fractions. It has been previously reported by Fernandez et al.

[6] working on a similar grade (0.1%C1.4%Mn0.03%Nb) under conditions closely approaching torsion

testing (Tdef=1100°C, ε=0.3 and ε=1/s) that the softening fraction determined by 2% offset gives a

reasonable approach to the recrystallised fraction XReX as revealed metallographically by analysis of

grain sizes and shapes leading to a linear relationship between them. This is in agreement with the

experimental values. These results were considered very important encouraging the extended

application of the methodology for determining XReX.

C1Mn2Nb3 - ε 0.35 - D°127µm

0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

0,8

0,9

1

0,1 1 10 100 1000

Time, s

Soft

en

ing

Fra

ctio

n

1100°C - X EBSD

1100°C - Exp.

1100°C - JMAK fit

1000°C - JMAK fit

1050°C - JMAK fit

Figure 78: Comparison of Softening results by DH test with Recrystallization results derived from

EBSD Reconstruction using mean misorientation angle criterion for C1Mn2Nb3 – 1100°C – ε 0.35

Despite the quite satisfactory results obtained by its first application, a series of issues have been

identified in the application of the proposed methodology and criterion that require further study for

clarification:

• The consequences of the low indexation rate in the original EBSD cartography have not been

evaluated. The indexation rate does not exceed 70% and the average value approaches 60%. It can

be argued that the optimum conditions regarding step size, map size or magnification and sample

preparation have not yet been found.

• The consequences of the limited number of maps analysed per sample and the limited number of

reconstructed grains under analysis per map as a consequence of the large initial grain size and the

need for relatively high magnification for improving indexation rate. Similarly, the critical number

of maps to be made per sample to minimise uncertainties has to be determined.

82

• The consequences of considering the grains at the edge of the maps, since the grain area at edges is

double that determined in the map and that of the grains at the corners is multiplied by 4. This

could lead to important deviations particularly where the maps are characterised by a limited

number of large grains.

• Finally, the formulation of the criterion distinguishing recrystallised and non-recrystallised grains

needs further work as it is in principle considered too simple as it does not include any analysis of

grain sizes and shapes.

The decision was taken at AM to focus on the development and application of this methodology for the

quantification of recrystallised fractions XReX. However, slight modifications in the criterion were

introduced according to the issues detailed above: i) the elimination of edge grains and ii) the removal

from the population of recrystallised grains derived from the mean misorientation criterion, those

grains presenting dceq values with small deviations from the mean grain size of non-recrystallised

grains.

Results: Determination of XRex

The methodology developed for determination of XReX has been applied only on grade C1Mn2Nb3

under testing conditions of ε=0.35, ε=1/s, D°=128µm and two deformation temperatures: 1050 and

950°C. Three holding times were set for each condition: 1, 5 and 100s for 1050°C and 1, 5 and 10s for

950°C. Two maps have been obtained for each microstructure under conditions of increased step size

0.8µm and increased magnification to 350X. These modifications were introduced in order to analyse

the effect on indexation rate. Figure 79 shows the resulting reconstructed maps for Tdef=1050°C and

those considered for XReX determination in which edges grains has been discarded. It can be noted that

the area of analysis is strongly reduced. Despite the changes introduced in the EBSD analysis the

indexation rate did not increase remaining in the range 50-70%. Figure 80 presents the maps resulting

from the application of the adjusted criterion for distinguishing recrystallised and non-recrystallised

grains and the XReX values determined. The analysis of these maps remained rather complex as the

criterion of grain size and shape, typically used for metallographic determination of XReX and that of

mean misorientation angle dominating the calculation of XReX by EBSD seemed not to be closely

linked. Figure 81 shows the maps obtained from samples tested at 950°C, in this case the values of

XReX were calculated as 0.29, 0.27 and 0.33 for t=1s, t=5s and t=10s respectively.

Figure 82 presents a comparison between the values of XReX determined from EBSD and the softening

fraction determined by double hit torsion tests. The agreement remains remarkable despite a

discrepancy for the sample tested at 1050°C and quenched after 100s; in this case the calculated value

of XReX (0.72) was lower than R (0.98). It could be argued that such deviation points at a limitation of

the proposed methodology under its current application procedure. Further tests are required to clarify

this issue.

83

Reconstructed Map Map with no edges considered

t=1s

t=5s

t=100s

Figure 79: Maps for determining XReX on C1Mn2Nb3 – 1050°C – ε 0.35 – D°127µm

84

Mean Grain Local Misorientation Φ≤3° Mean Grain Local Misorientation Φ>3°

t=1s

ΣAi(Φ≤3)/ΣAi = 0,16

t=5s

ΣAi(Φ≤3)/ΣAi = 0,35

t=100s

ΣAi(Φ≤3)/ΣAi = 0,72

Figure 80: Application of Mean Local Misorientation Criterion for estimating recrystallised fraction in

C1Mn2Nb3 – 1050°C – ε 0.35

85

t=1s t=10s t=100s

ΣAi(Φ≤3)/ΣAi = 0,29 ΣAi(Φ≤3)/ΣAi = 0,27 ΣAi(Φ≤3)/ΣAi = 0,33

Figure 81: Reconstructed maps for C1Mn2Nb3– 950°C – ε 0.35 – D°128µm and calculated XReX

C1Mn2Nb3 - ε 0.35 - D°127µm

0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

0,8

0,9

1

0,1 1 10 100 1000

Time, s

Soft

en

ing

Fra

ctio

n

1050°C - Exp.

1050°C - JMAK fit

X EBSD

C1Mn2Nb3 - ε 0.35 - D°127µm

0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

0,8

0,9

1

0,1 1 10 100 1000

Time, s

Soft

en

ing

Fra

ctio

n

950°C - Exp

950°C - JMAK fit

X EBSD

Figure 82: Comparison of softening results by DH test with XReX results derived from EBSD

Reconstruction using adjusted mean misorientation angle criterion for C1Mn2Nb3 – ε 0.35 deformed at

1050 and 950°C

In conclusion, a new methodology for quantifying the recrystallised fraction has been developed and

applied at AM in this project based on the application of software developed for the reconstruction of

austenite microstructures from EBSD maps of martensitic structures resulting from water quenched

tests and the use of a criterion for distinguishing recrystallised and non-recrystallised grains based on

the mean misorientation angle in the reconstructed austenite grains. The first step toward a validation

of this methodology for XReX determination have been made with encouraging results revealed by the

comparison of the calculated values with those of softening fraction derived from double hit torsion

tests. Further work is required to consolidate the application of this methodology: increasing indexation

rates in original maps, increasing the number of maps and/or reconstructed grains for statistical

validation and further evolving the proposed criterion for identyfing recrystallised grains will be the

actions required.

2.3.4.2 Task 4.2: Quantification of austenite grain structure and distribution

Effect of Nb

The quenched samples of the Nb steels from WP3 were examined using optical metallography to

measure the austenite grain size after each test condition. The Gleeble samples were sectioned along

the deformation axis and hot mounted in Bakelite. After grinding, the sample was lightly polished on a

1µm diamond pad and then immersed in an etchant of aqueous picric + Teepol for 30-60 minutes. The

grain boundaries were very difficult to etch clearly in these steels and measurement by linear intercept

86

techniques or image analysis of boundaries drawn onto micrographs was not practical in many samples.

The prior austenite grain size was therefore measured using the ASTM chart comparison method at a

magnification of x100, as in standard ASTM E112. Three different measurements were made across

the central region of the sample. Optical examination of the microstructures showed that the austenite

grain size was reasonably uniform across the bulk of the sample, once away from the surface and the

“dead zones” under the anvils, varying by no more than 0.5 ASTM points. The average ASTM number

was converted into a mean linear intercept grain size using Table 2 in ASTM E112.

The strain distribution within the cylindrical uniaxial compression samples was modelled using Finite

Element (FE) analysis, for different applied deformations, temperatures at the core of the specimen and

friction conditions (lubrication) between the anvils and the sample. Measured hot flow stress data from

the Gleeble tests for the appropriate temperature were used in the model. The coefficient of friction

affects the degree of barrelling of the sample. The lubrication between the anvils and sample (tantalum

foil at the high temperatures used in these tests) was chosen to minimise barrelling, although some is

inevitable. Figure 83 shows the calculated strain distributions in the upper right quarter section of the

cylindrical samples for 6 applied deformations at a core temperature of 1050°C and a friction

coefficient of 0.1. The “dead zone” of low strain under the anvils (top) can be seen and regions where

the local strain is higher than the applied strain are observed. The areas of the sample where the grain

size was measured were chosen to correspond to the regions where the strain was closest to the nominal

applied strain (indicated by the arrows).

1050 °C (core), friction coefficient = 0.1

Strain of 0.05

(0.78 mm reduction)

Strain of 0.075

(1.16 mm reduction)

Strain of 0.10

(1.53 mm reduction)

Strain of 0.15

(2.22 mm reduction)

Strain of 0.20

(2.90 mm reduction)

Strain of 0.35

(4.74 mm reduction)

0.05-0.06

0.10-0.11

0.35-0.400.20-0.22

0.07-0.08

0.14-0.16

Figure 83: Calculated plastic equivalent strain distributions in Gleeble uniaxial compression samples

for 6 different applied strains, using Finite Element modelling

The results from the tests carried out on the Nb steels to study the effect of strain at different

deformation temperatures and a strain rate of 1/s on the statically recrystallised grain size are

summarised in Table 37. There was a general trend for the grain size to decrease with increasing strain

and decreasing temperature, Figure 84, although there was some scatter in the results. No strong effect

of the Nb content on the recrystallised grain size was observed. The results at 1050°C possibly show a

refinement with increasing Nb content, although this is within the scatter of the measured data. The

tests highlighted in grey correspond to those in Table 17 where the stress relaxation curves indicated

that recovery may be the dominant softening mechanism or recrystallisation had not completed, and

therefore these values should not necessarily be considered as recrystallised grain sizes. It is more

likely they are an average from a mixture of recrystallised and unrecrystallised grains. Figure 84(d)

shows that increasing the strain rate led to a decrease in the recrystallised grain size at 1050°C after a

87

deformation of 0.2 strain. The effect of strain rate was stronger in the C1Mn1 steel than the Nb steels

where the change in grain size was less than 10µm. Example micrographs from selected tests are

presented in Figure 85 and Figure 86. The grain sizes are analysed in more detail in Task 5.2.

Table 37: Measured austenite grain sizes after static recrystallisation tests from an initial austenite

grain size of ~100µm. Grey cells indicate tests where recovery/partial recrystallisation occurred.

Test Test Measured

recrystallised

austenite grain size

Measured

recrystallised

austenite grain size Steel

T

deform

(°C)

Strain

ASTM µm

Steel T

deform

(°C)

Strain

ASTM µm

0.1 4.0-4.5 74 0.1 3.0-4.0 95

0.2 6.0-6.5 37 0.2 5.5-6.5 40 1150

0.35 4.0-4.5 74

1150

0.35 6.5-7.0 30

0.05 3.0-4.0 95 0.05 4.5-5.5 57

0.075 4.0 80 0.075 4.5-5.5 57

0.1 3.5-4.0 87 0.1 5.0-6.0 48

0.15 5.5-6.0 43 0.15 7.0-7.5 26

0.2 6.5 34 0.2 6.5-7.0 31

1050

0.35 6.0-6.5 36

1050

0.35 8.0 20

0.1 4.5-5.0 61 0.1 3.0 113

0.2 5.5-6.0 44 0.2 4.0-5.0 67

C1Mn1

950

0.35 5.0-6.0 48

C1Mn1Nb3

950

0.35 5.0-5.5 44

0.1 5.0-5.5 52 0.1 4.5-5.0 61

0.2 6.5-7.0 31 0.2 5.0-5.5 51 1150

0.35 6.5-7.5 28

1150

0.35 4.5-5.5 57

0.05 3.5 95 0.05 6.5 34

0.075 4.5 67 0.075 6.5 34

0.1 4.5-5.5 57 0.1 4.5-5.0 61

0.15 6.5 34 0.15 7.0 28

0.2 7.0-7.5 25 0.2 7.0-7.5 26

1050

0.35 7.5-8.0 22

1050

0.35 7.5 24

0.1 5.5-7.0 37 0.1 6.0-6.5 37

0.2 6.5-7.0 31 0.2 6.5-7.0 31

C1Mn1Nb1

950

0.35 7.0-7.5 26

C2Mn1Nb3

950

0.35 7.5-8.0 22

88

0

20

40

60

80

100

120

0 0.1 0.2 0.3 0.4

Strain (-)

Recrystallised austenite grain size

(µm)

C1Mn1

C1Mn1Nb1

C1Mn1Nb3

C2Mn1Nb3

1150°C

(a) strain, 1150°C, 1/s

0

20

40

60

80

100

120

0 0.1 0.2 0.3 0.4

Strain (-)

Recrystallised austenite grain size

(µm)

C1Mn1

C1Mn1Nb1

C1Mn1Nb3

C2Mn1Nb3

1050°C

(b) strain, 1050°C, 1/s

0

20

40

60

80

100

120

0 0.1 0.2 0.3 0.4

Strain (-)

Recrystallised austenite grain size

(µm)

C1Mn1

C1Mn1Nb1

C1Mn1Nb3

C2Mn1Nb3

950°C

(c) strain, 950°C, 1/s

0

10

20

30

40

50

60

0 2 4 6 8 10 12

Strain rate (/s)

Measured recrystallised grain size (µm)

C1Mn1

C1Mn1Nb1

C1Mn1Nb3

C2Mn1Nb3

(d) strain rate, 1050°C, 0.2 strain

Figure 84: Effect of strain and strain rate on statically recrystallised austenite grain size at three

deformation temperatures

(a) C1Mn1: 1200°C, 15 mins; 104µm

(b) C1Mn1Nb1: 1250°C, 15mins + 1150°C,

0.2 strain, 50s; 95µm

(c) C1Mn1Nb3: 1280°C, 30mins + 1150°C,

0.2 strain, 50s; 113µm

(d) C2Mn1Nb3: 1250°C, 15mins + 1150°C,

0.2 strain, 50s; 95µm

Figure 85: Example micrographs of Nb steel samples quenched to measure initial austenite grain size

89

(a) C1Mn1: 1050°C, 0.2 strain, 10s; 34µm

(b) C1Mn1: 1050°C, 0.1 strain, 30s; 87µm

(c) C1Mn1Nb1: 1150°C, 0.1 strain, 10s; 52µm

(d) C1Mn1Nb3: 1150°C, 0.1 strain, 20s, 95µm

Figure 86: Example micrographs of Nb steel samples quenched to measure recrystallised austenite

grain size

Effect of grain growth on austenite grain size

The results of the measured austenite grain sizes in steels C1Mn1, C1Mn1Nb1 and C1Mn1Nb3 after

the grain growth tests are plotted against hold time in Figure 87. There was very little increase in grain

size with holding time in steel C1Mn1, even after holding for up to 900s at 1150°C. The results at

1150°C were mixed, showing very little growth in C1Mn1 and C1Mn1Nb3 and a larger grain size in

C1Mn1Nb1 after 100s than after 300s. Some repeat tests were performed to investigate these

unexpected results but similar grain sizes were obtained. Some grain growth was measured at 1050°C

in the C1Mn1Nb1 and C1Mn1Nb3 steels. At 950°C there was no grain growth in any of the steels.

The results of the multi-hit deformation tests on steel C1Mn1 are shown in Figure 87(d) as dashed

lines. Two additional deformations were performed at higher temperatures to refine the austenite grain

size prior to the deformation at 1150 or 1050°C followed by a holding time of 100 or 900s (see Table

32). Larger austenite grain sizes were measured in these tests compared with the corresponding tests

with only one deformation before the hold, particularly at 1150°C. However, the grain size decreased

with longer holding time at 1150°C, similar to the single hit test. Grain growth was measured at

1050°C between hold times of 100 and 900s, at a similar rate to that observed in the single deformation

tests. The lack of grain growth in the Nb steels was consistent with that observed in previous Tata work

but the absence of growth in the C1Mn1 steel was not.

90

0

20

40

60

80

100

0 200 400 600 800 1000

Hold time (s)

Ave

rage

auste

nite g

rain

siz

e (

µm

)

C1Mn1 1050 0.2

C1Mn1 1050 0.1

C1Mn1 1150 0.2

C1Mn1 950 0.2

(a) steel C1Mn1

0

20

40

60

80

100

0 100 200 300

Hold time (s)

Ave

rage

auste

nite g

rain

siz

e (

µm

)

C1Mn1Nb1 1050 0.2

C1Mn1Nb1 1050 0.1

C1Mn1Nb1 1150 0.2

C1Mn1Nb1 950 0.2

(b) steel C1Mn1Nb1

0

20

40

60

80

100

0 100 200 300

Hold time (s)

Ave

rage

auste

nite

gra

in s

ize

(µ

m)

C1Mn1Nb3 1050 0.2

C1Mn1Nb3 1050 0.1

C1Mn1Nb3 1150 0.2

C1Mn1Nb3 950 0.2

(c) steel C1Mn1Nb3

0

20

40

60

80

100

0 200 400 600 800 1000

Hold time (s)

Ave

rage

auste

nite g

rain

siz

e (

µm

)

C1Mn1 1050 0.2 C1Mn1 1050 0.1

C1Mn1 1150 0.2 C1Mn1 950 0.2

C1Mn1 1150 0.2 3 hits C1Mn1 1050 0.2 3 hits

(d) steel C1Mn1 with 3 deformations before hold time

Figure 87: Measured austenite grain size as a function of holding time, temperature and strain

Comparison of grain size measurement techniques

A comparison has also been made between grain sizes measured with mean linear intercept and image

analysis techniques for selected samples, for consistency with the measurements of the other partners.

Four of the samples quenched out to measure the initial austenite grain size (from Table 5) and four

samples quenched after deformation at 1050°C to determine the statically recrystallised grain size have

been quantified using image analysis. In each sample, austenite grain boundaries were traced onto 4-6

digital micrographs (x100 magnification), which were then converted to black and white images and

analysed using the KS400 Image Analysis System to get an Equivalent Circle Diameter (ECD) grain

size (± 1 standard error). Figure 88 shows an example for steel C1Mn1 reheated at 1200°C for 15

minutes. The results from each micrograph were combined to get an overall grain size distribution and

statistics for each sample. The average grain size decreased in all cases after the deformation and

recrystallisation and the grain size distribution was also narrower than in the initial microstructure after

reheating and roughing (Figure 89).

The ECD grain size results were compared with the ASTM grain size estimated from the sample under

the microscope, using the standard chart comparison method, Table 38. The typical error quoted on

ASTM grain sizes is ±1 ASTM grain size number. There is reasonable agreement between the two

methods in most of the samples. The largest error was in the C1Mn1Nb1 and C2Mn1Nb3 recrystallised

samples with the smallest grain sizes. It should be noted that it was difficult to clearly reveal the

austenite grain boundaries in most of the Tata steel samples, despite careful etching and trying

variations in the etch composition. It was impossible to quantify some of the samples directly by a

linear intercept grain size technique.

As an alternative, selected samples were prepared for examination using EBSD to see if this method

could provide a measure of the grain size. The samples were analysed using the TSL EBSD software

on a FEI Quanta 600 FEG-SEM. Prior to analysis, the samples were polished and etched six times

91

followed by a colloidal silica polish for 10 minutes. Three scans were performed per sample, each of

area 500 x 500µm at a step size of 1µm. Figure 88(c) shows an example image with the 15-52°

misorientation angle boundaries highlighted, which give an indication of the prior austenite grain

structure. The grain boundaries were drawn onto the EBSD images by hand, and image analysed in the

same way as for the optical images. The results for the two samples analysed by this method are also

given in Table 38. There was good agreement between the EBSD measurement and the other

techniques for the reheated sample but the grain size of the recrystallised sample was significantly

over-estimated by the EBSD measurement.

(a) Original micrograph

(b) corresponding traced austenite

grain boundary image

(c) EBSD image, 15-52°

misorientation angle

boundaries

Figure 88: Steel C1Mn1, reheated at 1200°C for 15 minutes

9ZP1_cv1 all images

ECD grain size

0

10

20

30

40

50

60

70

80

90

100

0 20 40 60 80 100

120

140

160

180

200

220

240

260

280

300

320

34036

038

0

Bin

Fre

quency

0.00%

20.00%

40.00%

60.00%

80.00%

100.00%

120.00%

Frequency

Cumulative %

n=457 grains

mean g.s = 89µm

(a) C1Mn1, 1200°C, 15 mins

9ZP1_test1 all images

ECD grain size

0

10

20

30

40

50

60

70

80

90

100

0 20 40 60 80 100

120

140

160

180

Mor

e

Bin

Fre

quency

0.00%

20.00%

40.00%

60.00%

80.00%

100.00%

120.00%

Frequency

Cumulative %

n=413 grains

mean g.s = 47µm

(b) C1Mn1, 1200°C, 15 mins + 0.2ε 1050°C + 20s

Figure 89: Histograms of ECD initial austenite grain size distribution and cumulative frequency for

C1Mn1 steel (a) before and (b) after deformation tests.

Table 38: Comparison of grain size measurement techniques

Image analysis Microscopy EBSD + image analysis

Sample No. of

grains

ECD grain

size (µm)

ASTM

grain

number

Equivalent

linear

intercept

(µm)

No. of

grains

ECD

grain size

(µm)

C1Mn1 457 88.9 ± 2.0 3.0 – 3.5 95 – 113 106 92

C1Mn1Nb3 347 108 ± 2.7 3.0 113

C1Mn1Nb1 322 116 ± 2.6 3.5 95

Initial grain

size

C2Mn1Nb3 326 122 ± 3.3 3.5 95

C1Mn1 413 47.5 ± 1.0 6.5 34 123 84

C1Mn1Nb3 357 98.0 ± 2.4 3.5-4.5 67-95

C1Mn1Nb1 383 53.6 ± 1.2 7.0-7.5 24-28

Recrystallised

grain size

0.2 strain,

1050°C C2Mn1Nb3 335 52.9 ± 1.2 6.0-6.5 34-40

92

Effect of Si

In Task 3.2, it was aimed to study the effect of austenite grain size on SRX kinetics in the Si series of

steels. Several reheating and deformation conditions were tested to produce small, medium and large

grain size according to the test programme defined in Task 3.1. The thermomechanical treatment in

Figure 4 was applied to obtain different grain sizes. Torsion specimens were then water quenched

according to thermal treatment GS1, GS2 and GS3 in order to produce a fully martensitic structure.

Torsion specimens were then polished down to ¾ of the radius and etched using a Bechet-Beaujard

etchant in order to reveal the prior austenite grain size. Measurement of austenite grain sizes was

performed using the mean linear intercept method. Following thermal path GS1, grain sizes as large as

380µm were obtained, see Figure 90. Following thermal path GS2, recrystallised and unrecrystallised

austenite region were observed, Figure 91. For that reason, thermal path GS2 was not considered even

though smaller grain sizes were observed.

Figure 90: Thermal path GS1 - Large austenite grain size

Figure 91: Thermal path GS2

The results obtained for thermal treatment GS3 with a deformation of 0.5 at 1150°C are given in Figure

92. More than 100 grains were considered to determine the equivalent grain diameter. The results

revealed that no smaller average austenite grain size than ~230µm could be obtained. For that reason,

the effect of the grain size was not considered in the present study. Initial austenite grain sizes

considered for the Si steels were all in the same range of 230µm, see Table 39.

Table 39: Initial austenite grain sizes in Si steels

93

(a) C2Mn2Si1Nb0

(b) C2Mn2Si2Nb0

(c) C2Mn2Si2Nb3

(d) C2Mn2Si2Nb7

Figure 92: Initial austenite grain size – Si steel grades

Effect of Al

In order to study the effect of Al on the microstructure under equilibrium conditions, thermodynamic

calculations were performed with the Thermo-Calc software (TCFE6 database). In addition, the

microstructure of torsion specimens tested at different conditions was analysed. First, the initial

microstructures obtained after the soaking treatment were investigated. Specimens quenched after

deformation and different holding times were also analysed in order to investigate the microstructures

developed during softening. Finally, quenching treatments were carried out at different stages of the

multipass torsion tests in order to investigate the mechanisms contributing to strain accumulation.

Figure 93 shows the ferrite and austenite equilibrium mole phases calculated for the C2Mn2,

C2Mn2Al1 and C2Mn2Al2 steels as a function of temperature while in Figure 94 the phase diagrams

obtained for the steels with 1%Al and 2%Al contents are displayed. From the figures it can be observed

that Al addition leads to a significant increase in the ferrite phase equilibrium stability and in the Ae3

temperature, which is in good agreement with the trends reported in other works [1,2]. According to the

software results, 1%Al addition (C2Mn2Al1 steel) raises the Ae3 temperature from 780ºC to 900ºC,

while 2%Al addition results in a further increase up to 1030ºC. It must be noted that the deformation

temperature employed during some of the torsion tests for the C2Mn2Al2 steel was below the predicted

Ae3 temperature.

94

0

0.2

0.4

0.6

0.8

1

750 850 950 1050 1150 1250

T (ºC)

Mole Fraction

C2Mn2, FerriteC2Mn2, AusteniteC2Mn2Al1, FerriteC2Mn2Al1, AusteniteC2Mn2Al2, FerriteC2Mn2Al2, Austenite

Figure 93: Equilibrium ferrite and austenite mole fraction calculated by Thermo-Calc for the C2Mn2,

C2Mn2Al1 and C2Mn2Al2 steels as a function of temperature (TCFE6 database).

500

700

900

1100

1300

1500

0 0.2 0.4 0.6 0.8 1

C (wt%)

T (ºC)

1%Al

ferrite+cementite

austenite

liquid+austeniteferrite+austenite

liquid

ferrite+austenite

(a) C2Mn2Al1

500

700

900

1100

1300

1500

0 0.2 0.4 0.6 0.8 1

C (wt%)

T (ºC)

2%Al

ferrite+cementite

austenite

liquid+austeniteferrite+austenite

liquid

ferrite+austenite

ferrite

(b) C2Mn2Al2

Figure 94: Phase diagrams calculated by the Thermo-Calc software for the Al steels (TCFE6 database).

The AlN phase is not plotted for simplicity.

The Thermo-Calc software also predicted the presence of AlN in the range of temperatures

investigated. This could be of interest regarding the softening behaviour of the steels, firstly because

AlN precipitation could lead to a decrease in the amount of Al in solid solution, and secondly because

second phase particles are known to influence the softening behaviour of microalloyed steels. However

it must be taken into account that the maximum AlN mole fraction which can be formed is limited by

the N content and as a result the Al amount which can be tied up in the form of AlN is the same and

very low (<0.01wt%) for the three steels studied. The calculations also indicated that nearly all the AlN

present in the microstructure remains undissolved during the reheating treatment. The analysis of the

C2Mn2Al1 and C2Mn2Al2 steel specimens quenched after the soaking treatment by means of

Scanning Electron Microscopy (SEM) confirmed the presence of very coarse (>1 µm) Al and N bearing

particles, which were not expected to affect the softening behaviour. Therefore, for these steels only an

effect of Al in solid solution can be expected after deformation. Finally, according to the calculations,

for the 1% and 2%Al steels all the N is tied up in the form of AlN after the reheating treatment.

Therefore, all the Nb strain-induced precipitates formed after deformation are expected to be mainly

carbides.

Figure 95 shows the initial microstructures obtained for the different materials quenched directly after

the reheating treatment (1250ºC, 15min) etched in an aqueous solution of picric acid. In all cases the

microstructure was mainly formed by austenite phase, although in the 2%Al steels (C2Mn2Al2,

C2Mn2Al2Nb3 and C2Mn2Al2Nb7) after etching with 2% nital the presence of a small amount of

ferrite was revealed. The presence of ferrite grains can be attributed to the high Al content of these

95

steels [1,2]. Although these findings are in contrast with the thermodynamic results shown above which

predict an Ae3 temperature of 1030ºC for the 2%Al steels, the amount of ferrite present in the

specimens was small, less than 5% for the C2Mn2Al2 steel and less than 1% for the C2Mn2Al2Nb

steels. The results suggest that the time employed in the soaking treatment may not be long enough to

attain thermodynamic equilibrium. As already mentioned due to the small ferrite fraction its effect on

the softening behaviour of the steels was assumed to be negligible and only austenite grain size

distributions were measured.

C2Mn2

(a)

C2Mn2Al1

(b)

C2Mn2Al2

Ferrite

FerriteFerrite

(c)

C2Mn2Al1Nb3

(d)

C2Mn2Al2Nb3

Ferrite

(e)

C2Mn2Al2Nb7

Ferrite

(f)

Figure 95: Microstructure of the different Al steels after soaking at 1250ºC.

The initial austenite grain size (mean equivalent diameter) distribution was measured in all the steels.

In Table 40, the mean austenite grain size values, along with the ferrite volume fractions measured in

the 2%Al steels, are summarised. In the C2Mn2Al1 and C2Mn2Al1Nb3 steels similar grain sizes of

100 and 102 µm were obtained, while the 2%Al steels showed finer microstructures, of 65 µm for the

C2Mn2Al2 and C2Mn2Al2Nb3 of 56 µm for the C2Mn2Al2Nb7 steel. This indicates that Al and Nb

addition resulted in a grain refinement effect. However, the C2Mn2 steel also exhibited a fine

microstructure with an average grain size of 69 µm. This is probably related to the slightly higher

residual Ti level present in the steel, ∼50 ppm, compared to the other steels, ∼10 ppm.

Table 40: Mean equivalent diameters and ferrite volume fractions determined for

the studied steels at different conditions.

Steel Tsoak (ºC) Tquench (ºC) Dγmean (µm) fα

(%)

C2Mn2 1065 69±4 -

C2Mn2Al1 1065 98±5 -

1000 104±5 - 925 98±4 -

1065 65±4 3.1

1000 68±2 1.3 C2Mn2Al2

925 63±2 1.3

C2Mn2Al1Nb3 925 102±4 -

C2Mn2Al2Nb3 925 65±2 <1

C2Mn2Al2Nb7

1250

925 56±2 <1

The results obtained in Task 3.2 showed that Al addition resulted in a significant retardation of the

softening kinetics. However, this effect was significantly enhanced for the 2%Al steels and for the

96

lowest deformation temperature investigated, 925ºC. In order to investigate the mechanism leading to

this retardation several specimens were quenched at different temperatures and holding times. Figure

96 shows the microstructures obtained for C2Mn2Al2 at 925ºC, just after deformation (a), and at

holding times corresponding to 50% (b) and 90% (c) fractional softening. The micrographs were

obtained after etching the specimens with 2% Nital. The figure shows that the ferrite fraction present in

the microstructure just after deformation, 1.3%, was similar to that present after the reheating

treatment, ∼2%. However, as the holding time increased the ferrite fraction increased to 17% for a 50%

softening fraction and after large holding times, 10200s, a fully ferritic microstructure was achieved.

Therefore, the results indicate that at these conditions, γ→α phase transformation was concurrent with

softening increase.

C2Mn2Al2

(a)

(a) Tdef=925ºC, tip=0s, fα=1.3%, FS=0

(b)

C2Mn2Al2

(b) Tdef=925ºC, tip=270s, fα=17%, FS=50%

(c)

C2Mn2Al2

(c) Tdef=925ºC, tip=10200s, fα=100%, FS=90%

C2Mn2Al2

(d) Tdef=965ºC, tip=60s, fα=19%, FS=50%

Figure 96: Micrographs obtained for the C2Mn2Al2 steel at different temperatures and holding times.

In order to investigate if the microstructural evolution followed similar trends at other conditions, some

specimens were quenched at different temperatures and holding times. As shown in Figure 96 (d), for

the C2Mn2Al2 steel at 965ºC the specimen quenched at 50% fractional softening showed a ferrite

volume fraction of 19%, which indicates that at these conditions austenite to ferrite phase

transformation also takes place after deformation. However, no evidence of phase transformation was

found in the rest of the C2Mn2Al2 specimens quenched after deformation at temperatures above 965ºC

or for the C2Mn2 and C2Mn2Al1 specimens at any of the conditions investigated. This indicates that

in these cases the microstructural evolution mechanisms leading to softening were recovery and

recrystallisation. This is in good agreement with the trends predicted by the Thermo-Calc software,

although the final ferrite fraction measured at 925ºC (∼100%, see Figure 96(c)), was higher than that

predicted.

Similar trends were observed for the other 2%Al steels microalloyed with Nb (C2Mn2Al2Nb3 and

C2Mn2Al2Nb7); at temperatures above 1000ºC after deformation fully austenitic microstructures were

obtained, while at lower temperatures austenite to ferrite phase transformation was concurrent with

softening increase. Figure 97 shows an example corresponding to the C2Mn2Al2Nb3 steel deformed at

925ºC and quenched after 672 s holding time (40% fractional softening), in which a ferrite volume

fraction of ∼29% was measured. In addition, for the C2Mn2Al2Nb steels, at temperatures below

97

965ºC, strain-induced precipitation was also found to take place leading to a more complex behaviour.

This will be analysed in Task 4.3.

The results indicate that for the Al1 steel at all the conditions investigated and for the Al2 and Al2Nb

steels at temperatures above 1000ºC the softening retardation due to Al addition was caused by Al

solute drag effect. However, for the 2%Al steels at lower temperatures γ�α phase transformation takes

place together with softening increase, leading to a significantly higher degree of retardation. The

reasons for the softening delay for the 2%Al steels when γ�α phase transformation takes place are not

clear. From Figure 97 it can be observed that when phase transformation takes place ferrite grains

nucleate along the austenite grain boundaries. The austenite grain boundaries are also the preferred

nucleation sites for recrystallisation; therefore, when phase transformation takes place, recrystallisation

could be prevented. At these conditions, softening increase could only be due to recovery and/or phase

transformation, which may progress at a slower rate than recrystallisation. Finally, the ferrite fractions

measured for the 2%Al steels at all the conditions investigated have been summarised in Table 41.

(a) Etched with picric acid solution

(b) Etched with 2%Nital

Figure 97: Micrographs obtained for the C2Mn2Al2Nb3 steel deformed at 925ºC and water

quenched after a holding time of 672 s.

The recrystallised microstructures obtained were analysed at 95% fractional softening conditions

excluding the cases in which γ →α phase transformation took place after deformation. Figure 98 shows

as an example the recrystallised microstructures obtained after deformation at 1065ºC and ε=0.35 for

the different steels. All these micrographs exhibit homogeneous microstructures denoting

recrystallisation completion.

Figure 98: Recrystallised microstructures obtained for the different steels after deformation at

1065ºC, ε=0.35.

98

Table 41: Ferrite fraction (fα) and fractional softening measured at different conditions for the

C2Mn2Al2 steels.

Steel Dγ0 (µm) Tdef (ºC) tip (s) fα (%) FS (%)

Initial microstructure 1.3 -

965 60 19 50

0 1.3 0

270 17 50

404 24 55

2400 90 76

C2Mn2Al2 ~65

925

10200 100 90

Initial microstructure <1 -

1000 576 17 78

965 384 32 43

672 29 39

2016 24 39

C2Mn2Al2Nb3 ~102

925

5760 100 50

Initial microstructure <1 -

1000 576 17 78

384 15 39 965

5760 100 70

672 30 36

C2Mn2Al2Nb7 ~56

925 5760 100 76

In all cases the recrystallised grain size distributions were measured in terms of the mean equivalent

diameter. The mean values measured at the different deformation conditions are listed in

Table 42. From the data no significant effect of temperature on the recrystallised grain size was

observed. However, decreasing the applied strain leads in all cases to an increase in the austenite grain

size. This behaviour is in good agreement with that reported by other authors who only have found an

effect of the initial grain size and strain, but none for temperature [24,42].

Additionally, in order to investigate the mechanisms leading to strain accumulation during the

multipass tests, quenching treatments were performed at temperatures close to the Tnr for some of the

steels investigated. In the case of the C2Mn2Al2 steel, quenching treatments were also carried out near

the Ar3.

Table 42: Recrystallised grain sizes measured for the different Al steels.

Steel Tsoak (ºC) Dγγγγ0 (µm) Tdef (ºC) ε Dγrex (µm)

C2Mn2 1250 ~69 1065 0.35 56±2

1065 0.2 67±2 ~69

925 0.35 63±3

1065 0.35 62±3

1065 0.2 96±5 C2Mn2Al1 ~100

925 0.35 53±2

1065 0.35 60±2

1065 0.2 68±2 C2Mn2Al2 ~65

1000 0.35 52±2

C2Mn2Al1Nb3 ~102 1065 0.35 70±3

C2Mn2Al2Nb3 ~65 1065 0.35 48±1

C2Mn2Al2Nb7

1250

~56 1065 0.35 36±1

99

As previously mentioned it was found that Al addition leads to an increase of the recrystallisation

critical temperatures and this increase was significantly enhanced for the 2%Al steels. To investigate

this, C2Mn2Al2 and C2Mn2Al2Nb specimens were quenched two passes below the Tnr for tests carried

out at different interpass times. Micrographs corresponding to some of these specimens etched with 2%

Nital are shown in Figure 99. It was evident that for the three conditions the amount of ferrite present

in the specimens was higher than in the initial microstructure, therefore for the 2%Al steels γ�α phase

transformation was initiated at temperatures close to the Tnr. In the static softening analysis it was

found that γ�α phase transformation led to a high retardation of the softening kinetics. Therefore, the

results indicate that the high Tnr increase observed for the 2%Al steels was not related to Al solute drag

or strain-induced precipitation, but to the onset of γ�α phase transformation during the multipass

tests. This also agrees well with the small effect observed on the recrystallisation temperatures when

Nb was added to the 2%Al steels.

C2Mn2Al2

C2Mn2Al2 (a) C2Mn2Al2, Tquench=1020ºC (8 passes + 5 s), tip=5 s (Tnr=1056ºC)

C2Mn2Al2Nb3

C2Mn2Al2Nb3

(b) C2Mn2Al2Nb3, Tquench=980ºC (10 passes + 100 s), tip=100 s (Tnr=1022ºC)

C2Mn2Al2Nb7

C2Mn2Al2Nb7 (c) C2Mn2Al2Nb7, Tquench=1020ºC (10 passes + 30 s), tip=30 s (Tnr=1065ºC)

Figure 99: Micrographs obtained for the C2Mn2Al2Nb steels quenched two passes below the Tnr.

Although the microstructural investigations showed that for the 2%Al steels γ�α phase transformation

was already initiated at temperatures close to the Tnr, the Ar3 temperatures determined mechanically

were significantly lower. In recent works, it has been suggested that a minimum ferrite fraction, ∼35%,

must be developed in order to observe a decrease in the stress during multipass torsion tests [24]. In

order to investigate this, a C2Mn2Al2Nb3 specimen (tip=100 s) and several C2Mn2Al2 specimens

(tip=5, 30, 100s) were quenched at temperatures close to the Ar3. Results of the microstructures

obtained at the different conditions are shown in Figure 100. Although the ferrite fraction present in the

specimens was not measured, from the micrographs it is evident that at temperatures close to the Ar3

100

the ferrite fraction was in the range of that suggested by Jonas et al [24]. However, the ferrite fraction

formed at the Ar3 also depends on the multipass deformation conditions and tends to be larger for the

longest interpass time investigated, 100s.

C2Mn2Al2 (a) Tquench=Ar3=920ºC, tip=5 s

C2Mn2Al2 (b) Tquench=Ar3=940ºC, tip=30 s

C2Mn2Al2 (c) Tquench=Ar3=920ºC, tip=100 s

C2Mn2Al2Nb3 (d) Tquench=Ar3=920ºC, tip=100 s

Figure 100: Micrographs obtained for the C2Mn2Al2 and C2Mn2Al2Nb3 steels quenched at the Ar3 .

Effect of Mn and Nb

In order to characterize the austenite grain size for the isothermal double hit tests at AM (Table 11) and

to approach the target grain sizes of 100 and 200µm a series of hot torsion tests were performed in each

of the MnNb steel grades involving reheating, high temperature (1150°C) deformation and cooling at

5°C/s down to 1050°C followed by water quenching. Samples for metallographic analysis were

extracted from torsion samples and this analysis was performed on a longitudinal section corresponding

to the subsurface (depth ~200µm) of the torsion sample, a section in which the thermomechanical

conditions applied are representative of the target conditions of the test. Chemical etching was applied

using Picric Acid and 2% Teepol (Bechet-Beaujard agent) revealing prior austenite grains. Image

analysis was applied for determination of the mean grain size and grain size distribution in terms of

mean linear intercept.

Figure 101 shows representative micrographs of the austenite grain structure obtained for C1Mn2 and

C1Mn2Nb3 subjected to two levels of deformation at high temperature: ε=0.3 and ε=0.8. Table 12

presents the results of the quantitative analysis showing that for an applied roughing strain of 0.8 the

mean grain size closely approached the target with values of 124 and 128µm for C1Mn2 and

C1Mn2Nb3 respectively. Reducing the roughing strain to 0.3 induced larger mean grain sizes in the

microstructures however the resulting mean grain sizes remained far from the target of 200µm with

values of 161 and 138µm for C1Mn2 and C1MnNb3 respectively. The distribution of grain sizes in the

initial structures has been described in terms of histograms and they are presented for these steels in

Figure 102. It can be noted that the reduced level of roughing deformation led, particularly for C1Mn2

to a significantly more heterogeneous microstructure and a larger dispersion of grain sizes. For grades

C1Mn1Nb7 and C1Mn2Nb7, Figure 103 and Figure 104 present representative micrographs and grain

size distribution histograms for samples subjected to the same thermomechanical treatments. The

results of the quantitative analysis of the microstructures is presented in Table 12 showing that the

applied deformation with strain 0.8 similarly led to mean grain size values approaching the target of

100µm as values of 128 and 108µm were determined for C1Mn1Nb7 and C1Mn2Nb7 respectively. For

0.3 roughing strainapplied to C1Mn2Nb7 the microstructures were heterogeneous and a large

dispersion of grain size values was observed with a mean value exceeding the target and reaching

101

271µm. Despite these observations, the applied strain of 0.3 at high temperature was retained for the

experimental programme.

(a) C1Mn2 - Roughing Strain : 0.3 (b) C1Mn2 - Roughing Strain : 0.8

(c) C1Mn2Nb3 – Roughing Strain 0.3 (d) C1Mn2Nb3 - Roughing Strain 0.8

Figure 101: Initial Grain Sizes for C1Mn2 and C1Mn2Nb3

C1Mn2 - Roughing Strain: 0.3

0

0,05

0,1

0,15

0,2

25 75 125

175

225

275

325

375

425

475

525

575

625

675

725

775

825

875

925

975

Linear Intercept, µm

Relative Frequency

H

V

C1Mn2 - Roughing strain 0.8

0

0,05

0,1

0,15

0,2

25 75 125

175

225

275

325

375

425

475

525

575

625

675

725

775

825

875

925

975

Linear Intercept, µm

Relative Frequency

H

V

C1Mn2Nb3 - Roughing Strain 0.3

102

0

0,05

0,1

0,15

0,2

25 75 125

175

225

275

325

375

425

475

525

575

625

675

725

775

825

875

925

975

Linear Intercept, µm

Relative Frequency

H

V

C1Mn2Nb3 - Roughing Strain 0.8

0

0,05

0,1

0,15

0,2

25 75 125

175

225

275

325

375

425

475

525

575

625

675

725

775

825

875

925

975

Linear Intercept, µm

Relative Frequency

H

V

Figure 102: Initial grain size distribution in terms of Linear Intercept for C1Mn2 and C1Mn2Nb3

(a) C1Mn1Nb7 - Roughing Strain 0.8

(b) C1Mn2Nb7 – Roughing Strain : 0.3 (c) C1Mn2Nb7 - Roughing Strain : 0.8

Figure 103: Initial Grain Sizes for C1Mn2Nb7 and C1Mn2Nb7

103

C1Mn1Nb7 - Roughing Strain 0.8

0

0,05

0,1

0,15

0,2

25 75 125

175

225

275

325

375

425

475

525

575

625

675

725

775

825

875

925

975

Linear Intercept, µm

Relative Frequency

H

V

C1Mn2Nb7 - Roughing Strain: 0.3

0

0,05

0,1

0,15

0,2

25 75 125

175

225

275

325

375

425

475

525

575

625

675

725

775

825

875

925

975

Linear Intercept, µm

Relative Frequency

H

V

C1Mn2Nb7 - Roughing strain 0.8

0

0,05

0,1

0,15

0,2

25 75 125

175

225

275

325

375

425

475

525

575

625

675

725

775

825

875

925

975

Linear Intercept, µm

Relative Frequency

H

V

Figure 104: Initial grain size distribution in terms of Linear Intercept for C1Mn1Nb7 and C1Mn2Nb7

A criterion for mean grain size calculation and grain size distributions from reconstructed EBSD maps

Figure 105 shows two different approaches for determining the recrystallised grain size and the grain

size distribution for a sample of C1Mn2Nb3 tested at 1100°C with an applied strain of 0.35 and strain

rate of 1/s (D°=128µm) after 100s which results in a microstructure close to 100% recrystallised. In the

first approach, the grain size is determined by the mean linear intercept method inserting horizontal and

vertical lines across the micrographs obtained from quenched samples subjected to chemical etching

and determining the geometrical mean value between those determined in the horizontal and vertical

directions. The grain size distribution is characterised in terms of the relative frequency of intercept

values in the horizontal and vertical directions. In the case under analysis the mean linear intercept was

calculated as Lmean=47.3µm and the resulting distribution showed log-normal characteristics. This could

be considered a conventional approach for grain size determination. The second approach has been

selected for determination of mean grain size and grain size distributions from EBSD maps. The

calculation of mean grain size is performed using a mean value of circle equivalent diameter dceq based

on area rather than number of grains. This is due to the strong impact of the large number of small

grains measured by EBSD. These grains are actually pixel clusters and should be removed as they

appear as a consequence of noise introduced by poor indexing and resolution issues in EBSD

operation. The number is also dependent on the step size chosen. As a consequence a mean grain size

either determined by the arithmetic mean of dceq values or the mean linear intercept will lead to large

underestimation of the grain size. These effects of noise, step size and resolution on variation in mean

grain size are significantly reduced by using mean values based on area rather than number, that is, by

dividing the total area by the total diameter which can be written as shown in Figure 105 [25]. The

104

effect of small grains significantly affects the distribution of grain sizes as expressed in relative

frequency introducing a spike adjacent to the ordinate axis.

An alternative method of reducing the effect of small grains is to plot the data as an area size

probability plot, where the probability Pi on the y axis is defined as Pi=ΣAi/At [26]. This method has

been adopted here in order to better visualise the distribution of grain sizes. Using this approach for

grain size measurements in EBSD, the area based mean value of dceq was 44.1µm in close agreement

with that determined by mean linear intercepts from micrographs. Regarding the method described for

grain size measurements from EBSD maps, good correlations between hardness of steels and the size

calculated in this way have been reported. Nevertheless, no standard is yet available for grain size

determination considering the particular characteristics of EBSD maps. AM has adopted this approach

for recrystallised grain size measurements in this project.

0

0,02

0,04

0,06

0,08

0,1

0,12

0,14

0,16

0,18

0,2

0 20 40 60 80100 120

140160

180200

Linear Intercept, µm

Re

lati

ve

Fre

qu

en

cy

H

V

0

0,2

0,4

0,6

0,8

1

0 20 40 60 80 100 120 140 160 180 200

dceq (Equivalent circle diameter), µm

Are

a B

ase

d P

rob

ab

ilit

y

Geometric Mean L , µm 47,3

H V

Mean Linear Intercept, µm 50,4 44,3

STD 32,1 29,1

N° Intercepts 252 250

N° fields 5 5

Minimum (mean), µm 47,4 37,0

Maximum (mean), µm 53,4 54,4

Area based Mean Value

µmdceq

Adc

i

i

area 1,44==∑∑

Optical Linear Intercept: Mean calculation and distribution in

terms of Relative Frequency EBSD Circle Equivalent Diameter: Area based Mean value

calculation and distribution (Area Based Probability)

Figure 105: Comparison of grain size measurements from Optical Micrographs and EBSD reconstructions

in C1Mn2Nb3 – 1100°C – ε 0.35

The application of EBSD reconstruction methodology on recrystallised samples for the determination

of recrystallised grain size and grain size distributions following the criteria described above has been

performed only on one grade C1Mn2Nb3 and one testing condition (Tdef=1050°C, ε=0.35, ε=1/s and

D°=128µm). This was a consequence of the time invested on the development of the application of the

=200 µm; Copy of BC; Step=0.4 µm; Grid1561x1171

105

EBSD reconstruction technique for microstructural analysis in the project. Figure 106 shows the

reconstructed map obtained under the testing conditions, the calculation of the area based mean grain

size and the dceq grain size distribution in terms of area size probability plot. In this figure the

comparison is made with the results obtained in the preliminary tests on the same steel at testing

temperature of 1100°C. The area based mean grain size was calculated as 28.9µm, significantly finer,

as expected, than that measured for the higher test temperature of 1100°C. The plot of area based

probability clearly shows the advantages in adopting this approach in order to make valid comparisons

between data sets.

µmdceq

Adc

i

i

area 9,28==∑∑

µmdceq

Adc

i

i

area 1,44==∑∑

1050°C – t=100s 1100°C – t=100s

C1Mn2Nb3 - εεεε 0.35 - D°127µm

0

0,2

0,4

0,6

0,8

1

0 20 40 60 80 100 120 140 160 180

dceq (Equivalent circle diameter), µm

Are

a B

ase

d P

rob

ab

ilit

y

1050°C - t=100s

1100°C - t=100s

Figure 106: EBSD reconstructed maps, mean recrystallised grain size in terms of area based average and

recrystallised grain size distribution in terms of Area Based Probability for C1Mn2Nb3 – ε 0.35

2.3.4.3 Task 4.3: Quantification of precipitates

Effect of Si

The matrix dissolution technique was applied to samples water quenched directly after the deformation

from torsion tests in Task 3.5 for precipitation analysis. One deformation level and one deformation

temperature was considered (see Figure 9) to evaluate the effect of Si on the precipitation of niobium.

Torsion tests were performed on steel grade C2Mn2Nb3 and C2Mn2Si2Nb3. Samples were prepared

for matrix dissolution analysis. A hole was drilled along the length of the torsion specimen in order to

remove the inner part of the specimens and to consider only the part of the material that had undergone

the nominal deformation. After dissolution of the whole specimen, the electrolyte was filtered (pore

diameter equal to 0.45µm) and the remaining part in the filter was analysed by ICPOES. Results given

in Figure 107 show the evolution of the precipitated fraction of the total niobium content as a function

of time, which reveals that increasing silicon content decreased the growth rate of precipitates.

=200 µm; Copy of BC; Step=0.4 µm; Grid1561x1171

106

Figure 107: Precipitation kinetics of C2Mn2Nb3 and C2Mn2Si2Nb3 steels after a deformation of 0.2

applied at 1000°C

As previously mentioned in Task 3.2, according to reference [13], in the presence of niobium for steel

grade containing 0.1%C - 0% to 0.5%Si, the increase of Tnr with silicon content was explained by its

effect in accelerating Nb(CN) precipitation, which seems the opposite effect to what is observed in

Figure 107. However, in reference [13] the precipitation kinetics of Nb(CN) were estimated from Tnr

evolution following MFS analysis. In other words, precipitation was estimated based on the stopping of

recrystallisation. The recrystallisation stop is linked to the early stage of precipitation (usually

modelled using the criterion of 5% of precipitation, Equation (10)) and thus to the effect of small

precipitates, which are very difficult to detect by filtering techniques. The Tnr evolution is sensitive to

the nucleation stage of precipitation. In contrast, the filtering method does not allows determination of

small precipitates and is more sensitive to the volume fraction of precipitates. In other words, filtering

methods are more sensitive to growth rate of precipitates than to the thermodynamic effect of

nucleation stage usually modelled using supersaturation concept.

Effect of Al

The precipitation state of the Al-Nb steels (C2Mn2Al1b3, C2Mn2Al2Nb3 and C2Mn2Al2Nb7) was

investigated by TEM at different conditions. First, specimens quenched at different softening levels

were examined in order to study the effect of strain-induced precipitation on the softening kinetics. The

specimens were quenched at times corresponding to the plateau start and finish times observed in the

softening curves. Specimens corresponding to the Tata C2Mn1Nb3 steel were also analysed and the

results compared with those obtained for C2Mn2Al1Nb3 to evaluate the effect of Al on strain-induced

precipitation. Finally, the precipitation state of specimens quenched at temperatures close to the Tnr was

also investigated to analyse the effect of the precipitates during the multipass torsion tests.

From the quenched specimens carbon replicas were prepared following standard procedures and

examined in a JEOL 2010 Transmission Electron Microscope (TEM) operated at 200 KV with a LaB6

filament equipped with Energy Dispersive Spectrometry (EDS) analysis system. In the case of the

2%Al steels (C2Mn2Al2Nb3, C2Mn2Al2Nb7), ferrite was also present for some of the conditions

investigated. However, the replica analysis enables discrimination of the precipitates present in the

ferrite and martensite (quenched austenite) phases. As well as extracting the precipitates present in the

steel, the replicas reveal the microstructure of the specimen. As a result it was possible to distinguish

the precipitates in the martensite from those present in the ferrite phase. From these replicas, the

average diameter and size distributions of the precipitates present in martensite (quenched austenite)

and ferrite (if present) were measured with the aid of the DigitalMicrograph software.

First, specimens corresponding to the microstructure present before the torsion tests (quenched after

soaking at 1250ºC) were examined in order to investigate the initial precipitation state. In steel

C2Mn2Al1Nb3 no evidence of precipitates was found in these specimens. In C2Mn2Al2Nb3 these

were very scarce and difficult to find (58 particles measured, D=93±7 nm). Therefore, it can be

107

considered that all the Nb was put into solution during reheating. However, in the case of

C2Mn2Al2Nb7, a significant amount of relatively coarse precipitates with average size of 127±6 nm

were detected in the replicas, some examples and the measured precipitate size distribution are shown

in Figure 108.

TiNb Ti

TiCu

Cu

Cu

Nb

0 2 4 6 8 10

Full Scale 452 cts Cursor: 20.491 (0 cts)

0

5

10

15

20

25

30

35

40

(0-10)

(20-30)

(40-50)

(60-70)

(80-90)

(100-110)

(120-130)

(140-150)

(160-170)

(180-190)

(200-210)

(220-230)

(240-250)

(260-270)

Precipitate Diameter (nm)

Frequency (%)

Dmean= 93±7 nm

58 particles measured

C2Mn2Al2Nb3

Figure 108: Coarse Nb precipitates, EDS analysis and precipitate size distribution measured from the

C2Mn2Al2Nb7 specimen quenched after soaking at 1250ºC.

These findings agree well with the results of equilibrium calculations performed with different

solubility products found in the literature [31, 32, 33], which are summarised in Table 47. For the two

0.03%Nb steels (C2Mn2Al1Nb3, C2Mn2Al2Nb3), all the solubility products, except that given by

Palmiere et al. [31], predict equilibrium dissolution temperatures lower than 1250ºC, whereas for the

C2Mn2Al2Nb7 steel all the solubility products predict dissolution temperatures above 1250ºC.

The quenching treatments carried out to study the strain-induced precipitation evolution during

softening for the C2Mn2Al2Nb steels are represented in Figure 109. It must be remembered that at

temperatures from 1000ºC to 925ºC, γ�α phase transformation occurred concurrently with softening

increase.

0

0.2

0.4

0.6

0.8

1

0.1 1 10 100 1000 1000

0t(s)

Fractional Softening

T=1065ºC

T=1000ºC

T=965ºC

T=925ºC

C2Mn2Al2Nb3

ε=0.35

0

0.2

0.4

0.6

0.8

1

0.1 1 10 100 1000 1000

0t (s)

Fractional Softening

T=1065ºC

T=1000ºC

T=965ºC

T=925ºC

C2Mn2Al2Nb7

ε=0.35

Figure 109: Quenching treatments carried out in order to study the NbC strain-induced precipitation

during softening for the C2Mn2Al2Nb steels.

In the specimens quenched after deformation at 1000ºC, the number of precipitates found in the

martensite regions was small for the two steels, especially in the case of the C2Mn2Al2Nb3 steel, for

which only 28 particles were detected in the analysis. Example of these precipitates and the

corresponding precipitate size distributions are shown in Figure 110(a-b). The average diameters, of 76

and 60 nm for the C2Mn2Al2Nb3 and C2Mn2Al2Nb7 steels respectively, were coarse but finer than

those corresponding to the soaked specimens, 93 and 126 nm. For C2Mn2Al2Nb3 steel this could be

attributed to the low amount of precipitates measured. However, for the C2Mn2Al2Nb7 steel this

indicates that a certain amount of precipitation had occurred after deformation. It must be taken into

account that at 1000ºC, growth and coarsening processes are expected to be fast. Precipitates were also

found in the ferrite regions, some examples are displayed in Figure 110(c). As shown in the figure, the

precipitates were coarser in the ferrite than in the martensite.

108

(a) C2Mn2Al2Nb3, martensite (b) C2Mn2Al2Nb7, martensite (c) C2Mn2Al2Nb7 ferrite

Figure 110: Examples of precipitates from specimens quenched after deformation at 1000ºC, t=576s,

for C2Mn2Al2Nb steels

After deformation at 965ºC, a larger amount of precipitates was found for the two steels. Examples of

precipitates corresponding to specimens quenched at times for the plateau onset (384s) are displayed in

Figure 111(a-b). As the figure shows, again the precipitates were less frequent in the C2Mn2Al2Nb3

specimen. For the C2Mn2Al2Nb7, when the softening levels increased again (t~6000s) the

microstructure consisted mainly of ferrite with some martensite islands. However, in this case a

significant amount of precipitates were also found in the martensite regions, as shown in Figure 111(c).

(a) C2Mn2Al2Nb3, t=384s

(b) C2Mn2Al2Nb7, t=384s

(c) C2Mn2Al2Nb7, t=5760s

Figure 111: Precipitates found in the C2Mn2Al2Nb martensite regions after deformation at 965ºC

The Nb precipitates found in the ferrite regions in specimens quenched after deformation at 965ºC

were more abundant and coarser than in the martensite. They were also significantly coarser for the

C2Mn2Al2Nb3 than for the C2Mn2Al2Nb7 steel. Figure 112 shows some examples of Nb precipitates

found after deformation at the lowest temperature investigated, 925ºC, in the martensite and ferrite

regions for the specimens quenched at the plateau onset (t=672s). The precipitates were significantly

more abundant than at higher temperatures. In addition the size of the martensite precipitates, 14 and

18 nm, was finer than in the rest of the specimens studied.

At longer interpass times (5760s), the softening increased again for the two C2Mn2Al2Nb steels. At

this softening level, in the C2Mn2Al2Nb3 steel some martensite islands could be found while for the

C2Mn2Al2Nb7 steel the microstructure was ∼100% ferrite. Figure 113 illustrates some examples of the

Nb precipitates found at these conditions. The precipitate average size in martensite increased with

increasing the holding time, from 14 nm (Figure 112) at 672s to 24 nm at 5760s (Figure 113). The

precipitate sizes measured in each case, together with the ferrite fraction found in each of the quenched

specimens are summarised in Table 43. The size of the martensite precipitates is plotted in Figure 114.

The figure shows that the precipitate size decreased significantly with decreasing deformation

temperature. The precipitates measured after deformation at 1000ºC and 965ºC tended to be coarser for

Dmean = 60 ±5 nm (212 particles) Dmean = 76 ±19 nm (28 particles)

Dmean = 30 ±4 nm (94 particles) Dmean = 19 ±1 nm (241 particles) Dmean = 33 ±1 nm (212 particles)

109

the Nb3 than for the Nb7 steel, while the mean diameters determined at 925ºC were similar. The

amount of precipitates found for the two steels at 1000ºC and for the C2Mn2Al2Nb3 steel at 965ºC

was very low, so the measurements may include some of the precipitates not dissolved after the

reheating treatment.

(a) C2Mn2Al2Nb3, Martensite

(b) C2Mn2Al2Nb7, Martensite

(c) C2Mn2Al2Nb3, Ferrite

(d) C2Mn2Al2Nb3, Ferrite

Figure 112: Precipitates found in the C2Mn2Al2Nb martensite and ferrite regions after deformation at

925ºC at the time for the plateau onset (t=672s).

(a)C2Mn2Al2Nb3 (martensite) (b)C2Mn2Al2Nb3 (ferrite) (c)C2Mn2Al2Nb7 (ferrite)

Figure 113: Example of precipitates in ferrite, extracted from the C2Mn2Al2Nb3 and C2Mn2Al2Nb7

steels after deformation at 925ºC and a holding time of 5760 s.

Dmean = 14 ±1 nm (300 particles) Dmean = 18±1 nm (259 particles)

Dmean =24 ±1 nm (216 particles)

110

Table 43: Precipitate mean sizes (Dmean) and ferrite volume fractions (fα) at different deformation

temperatures for the C2Mn2Al2Nb steels.

Nº of measured

precipitates Dmean (nm)

Steel Dγ0

(µm)

Tdef

(ºC) ε tip (s)

fα

(%) Martensite Ferrite Austenite Ferrite

Initial microstructure <1 58 - 93±7 -

1000 576 17 28 20 76±19 151±22

965 384 32 94 124 30±4 91±12

672 29 300 201 14±1 18±1

C2Mn2Al2Nb3 ~65

925

0.35

5760 ~100 216 302 24±1 33±1

Initial microstructure <1 212 - 126±6 -

1000 576 17 212 139 60±5 199±31

965 384 15 241 291 19±1 20±1

965 5760 100 212 300 33±1 42±1

925 672 30 259 300 18±1 18±1

C2Mn2Al2Nb7 ~56

925

0.35

5760 100 - 300 - 30±2

0

20

40

60

80

100

120

140

1 10 100 1000 10000t (s)

Precipitate Mean Diameter

C2Mn2Al2Nb3, Initial Microstructure

C2Mn2Al2Nb7, Initial Microstructure

C2Mn2Al2Nb3, 1000ºC

C2Mn2Al2Nb7, 1000ºC

C2Mn2Al2Nb3, 965ºC

C2Mn2Al2Nb7, 965ºC

C2Mn2AlNb3, 925ºC

C2Mn2Al2Nb7, 925ºC

Figure 114: Precipitate average sizes measured in martensite for all the quenched AlNb steel

specimens.

Similarly to the case of the Al2Nb steels, for C2Mn2Al1Nb3 the softening curve obtained after

deformation at 1000ºC showed a saturation at t∼384 s for 85% fractional softening level (Task 3.5). In

order to analyse whether this saturation was due to strain-induced precipitation, a specimen was

quenched at the start of softening saturation and analysed by TEM. However, the precipitates found in

the replicas were very scarce and only 39 particles were measured with an average diameter of 44 nm,

which indicates a limited effect of strain-induced precipitation at these conditions.

C2Mn1Nb3 and C2Mn2Al1Nb3 specimens quenched after deformation at lower temperatures (900-

925ºC) were also analysed in order to investigate the effect of Al on strain-induced precipitation

kinetics without phase transformation interaction. C2Mn2Al1Nb3 specimens were quenched at the

same conditions and sent for electrolytic dissolution and ICP measurements to ArcelorMittal in order to

determine the amount of Nb precipitated. Figure 115 shows the softening curves obtained for the two

steels together with the conditions selected for TEM study. From the figure, it can be observed that

slightly retarded softening kinetics were obtained for the C2Mn1Nb3 steel.

111

0

0.2

0.4

0.6

0.8

1

0.1 1 10 100 1000 10000

Fractional Softening

t (s)

C2Mn1Nb3 T=925ºC

C2Mn2Al1Nb3 T=925ºC

(a) 925°C

0

0.2

0.4

0.6

0.8

1

0.1 10 1000

Fractional Softening

t (s)

C2Mn1Nb3 900ºC

C2Mn2Al1Nb3 900ºC

(b) 900°C

Figure 115: Softening curves and quenching treatments for C2Mn2Al1Nb3 and C2Mn1Nb3 steels

Figure 116 illustrates the evolution of strain induced precipitation in the carbon replicas extracted from

the C2Mn2Al1Nb3 steel at 925ºC. It includes TEM micrographs of the precipitates and the measured

precipitate size distributions. At an interpass time of 96s, which is close to the plateau start, strain

induced precipitation onset is evident from Figure 116(a). At this holding time it was measured by

chemical extraction that 11% of the total Nb content in the steel was precipitated, which agrees well

with the few and small Nb(C,N) particles (13nm) observed in the replicas. In Figure 116(b), which

corresponds to a larger holding time within the plateau, an increase in precipitate density was observed,

although the precipitate mean size remained unchanged. At longer interpass times of 960 and 4800s,

the amount of Nb precipitated increased up to 41 and 83% levels respectively, and larger precipitate

sizes of 28 and 20 nm were obtained. The precipitate size measured at 960s, 28 nm, was larger than that

obtained at 4800s, 20nm. This decrease in the precipitate average size with increasing interpass time

could be attributed to new precipitates forming between 960 and 4800s. On the other hand, although a

relatively large amount of precipitates were measured in each specimen, the precipitation process could

also result in significant size heterogeneities.

The results obtained for C2Mn1Nb3 at 925ºC show a similar trend. As shown in Figure 117, the

precipitate size and amount increased with interpass time. The precipitate size obtained after quenching

at 4800s was similar for the C2Mn2Al1Nb3 and C2Mn1Nb3 steels at ∼20 nm. However, it is

interesting to note that a significantly larger amount of precipitates were present in the replicas

extracted from the C2Mn1Nb3 steel after 58s (Figure 117(a)), than in the C2Mn2Al1Nb3 specimen

after 96s (Figure 116(a)).

Figure 118 shows TEM micrographs of the precipitates found in both C2Mn2Al1Nb3 and C2Mn1Nb3

steels at different holding times after deformation at 900ºC. After 96 s the ICP measurements indicated

that in the C2Mn2Al1Nb3 steel 14% of the total Nb was precipitated and an average precipitate

diameter of 7 nm was measured. After 960s the Nb precipitated and average precipitate size increased

up to 46% and 14 nm respectively, and finally for the longest interpass time investigated, 5760s, the

amount of Nb precipitated reached 82% and a particle size of 19 nm was obtained. In all cases, the

precipitate sizes were smaller and the Nb precipitated fractions slightly higher than those estimated at

925ºC for similar holding times. The precipitate state evolution for C2Mn1Nb3 at 900ºC shows that for

the same interpass time, the precipitate sizes measured for both steels were similar. However, it was

also evident that the amount of precipitates present after 96s was significantly higher for C2Mn1Nb3

than for C2Mn2Al1Nb3 (Figure 118(a)). Finally, the precipitate size measurements carried out for the

two steels, together with the ICP results obtained for the C2Mn2Al1Nb3 steel are summarised in Table

44.

112

(a) Tdef=925ºC, ε=0.35, tip=96 s (b) Tdef=925ºC, ε=0.35, tip=288 s

(c) Tdef=925ºC, ε=0.35, tip=960 s (d) Tdef=925ºC, ε=0.35, tip=4800 s

Figure 116: Precipitation state evolution for the C2Mn2Al1Nb3 steel at 925ºC.

(a) Tdef=925ºC, ε=0.35, tip=58 s (b) Tdef=925ºC, ε=0.35, tip=4800 s

Figure 117: Precipitation state evolution for the C2Mn1Nb3 steel at 925ºC.

Dmean =13 ±1 nm (223 particles) Dmean =13 ±1 nm (335 particles)

Dmean =28 ±1 nm (321 particles) Dmean =20 ±1 nm (315 particles)

Dmean =9 ±1 nm (342 particles) Dmean =20 ±1 nm (345 particles)

113

C2Mn2Al1Nb3 C2Mn1Nb3

(a) Tdef=900ºC, ε=0.35, tip=96s

(b) Tdef=900ºC, ε=0.35, tip=5760s

Figure 118: Precipitation state evolution for the C2Mn2Al1Nb3 and C2Mn1Nb3 steels after

deformation at 900ºC.

Table 44: Precipitate mean sizes (Dmean) and amount of Nb precipitated in the C2Mn1Nb3 and

C2Mn2Al1Nb3 steels.

Steel Dγ0

(µm)

Tdef

(ºC) ε tip (s)

Nº of

measured

precipitates

Dmean

(nm)

Nb

precipitated

(wt%)

Initial

microstructure

- - -

100

0

384 39 44±7 -

96 223 13±1 0.003 (11%)

288 335 13±1 0.006 (21%)

960 321 28±1 0.011 (39%) 925

4800 315 20±1 0.023 (82%)

96 298 7±1 0.004 (14%)

960 355 14±1 0.013 (46%)

C2Mn2Al1Nb3 ~102

900

0.35

5760 404 19±1 0.023 (82%)

58 342 9±1 - 925

4800 345 20±1 -

96 310 8±1 - C2Mn1Nb3 ~87

900

0.35

5760 181 16±1 -

Additionally, several specimens were water quenched at temperatures close to the Tnr in order to

establish the mechanisms leading to strain accumulation in the multipass torsion tests. In the case of the

Dmean =7 ±1 nm (298 particles)

Dmean =19 ±1 nm (404 particles)

Dmean =8 ±1 nm (310 particles)

Dmean =16 ±1 nm (181 particles)

114

2%Al steels, the microstructural analysis already carried out showed that γ�α phase transformation

was initiated at temperatures close to the Tnr and this was the main mechanism leading to strain

accumulation. However, the precipitation state of some of these specimens (C2Mn2Al2Nb3, tip=100 s

and C2Mn2Al2Nb7, tip=30 s) was also examined by TEM. The precipitates found in the

C2Mn2Al2Nb3 steel quenched after 10 deformation passes and tip = 100 s were scarce both in the

ferrite and martensite regions, and the measured average sizes were relatively coarse, of 47 and 74 nm

in the martensite and ferrite respectively. The measured precipitate sizes in the C2Mn2Al2Nb7

specimen after 10 deformation passes and tip = 30s, of 98 nm and 99 nm in the ferrite and martensite

regions, respectively, were also coarse. However, the presence of undissolved precipitates after

reheating at 1250ºC, which showed an average size of 126 nm, could be contributing to these

measurements.

Finally, the multipass torsion results showed that a significant increase in the recrystallisation critical

temperatures was observed when 0.03%Nb was added to the 1%Al steel. In order to determine if this

increase was due to the strain-induced precipitation or to the solute drag effect exerted by Nb, a

specimen was quenched after two deformation passes below the determined Tnr for the multipass

torsion test carried out at tip=30 s. Very few particles (32) with an average size of 76 nm were detected

in this steel. The limited amount of Nb particles detected indicates that Nb solute drag effect could be

the main mechanism responsible for the Tnr increase in this steel at these conditions.

Effect of Mn

The quantification of precipitates on the MnNb steels has been carried out in terms of precipitation rate

of Nb comparing the nominal amount of Nb known to have remained in solution before the

deformation tests as shown in Task 3.2 and the amount of Nb precipitated quantified by electrolytic

dissolution and Inductive Plasma spectroscopy (ICP-OES) applied on cylindrical samples extracted

from torsion test samples as described in Task 3.5. The testing conditions involving isothermal single

hit torsion tests followed by water quench after different holding times were described in Table 33.

Table 45 presents the results obtained from ICP measurements for the tests performed. Kinetics of

strain induced precipitation were derived from these measurements.

Table 45: Torsion Single Hit tests performed for precipitation studies

Grade Temp

(°C)

Initial Grain

Size (µm) Strain

Holding

Time (s)

Nominal

Nb(ppm)

Precipitated

Nb (ppm)

Precipitation

Rate %

C1Mn2Nb7 1250 1 700 6 0,9

C1Mn2Nb7 1050 106 0 1 700 8 1,1

C1Mn2Nb7 1050 106 0,35 2 700 18 2,6

C1Mn2Nb7 1050 106 0,35 10 700 22 3,1

C1Mn2Nb7 1050 106 0,35 40 700

C1Mn2Nb7 1050 106 0,35 100 700

C1Mn2Nb7 950 106 0,35 1 700

C1Mn2Nb7 950 106 0,35 2 700

C1Mn2Nb7 950 106 0,35 5 700

C1Mn2Nb7 950 106 0,35 10 700

115

2.3.5 WP 5: Modelling and construction of processing maps

The objectives of this work package were:

• Extension of recovery and recrystallisation kinetics models to more fully include the effects of

several alloy elements (Mn, Si, Al)

• Improvement of models to predict austenite grain size after recrystallisation (mean size and

distribution)

• Improvement of equations to predict austenite grain size after grain growth during long

interpass times

• Extension of a physically-based model for recovery, recrystallisation and strain induced

precipitation

• Construction of processing regime maps using new equations

2.3.5.1 Task 5.1: Assessment of current model capabilities

Current models of the project partners

In order to clarify in detail the areas in which specific improvements to current models were required, a

comparison exercise was carried out in the first semester to benchmark the capabilities and limitations

of the existing models of the project partners. This was used as a starting point for defining the way

forward for the development of the models, designing the experimental test programme to address

specific improvements and generating the necessary data for the equations.

Most published models are based on empirical equations that describe the softening and hardening

mechanisms governing the microstructural evolution of hot worked austenite. The majority of these

equations are based on those proposed by Sellars and Medina. There are also more recent and

sophisticated models concerning the mechanisms of recovery, recrystallisation and precipitation in

austenite during hot rolling which are more physically based, such as that of Zurob. The CEIT model

for recrystallisation-precipitation is detailed in [27]. The Tata model is based on similar equations from

the original work of Dutta and Sellars [28,24]. CRM focussed its modelling work on improving the

StripCam [34,35] hot rolling model. ArcelorMittal considered the empirical models proposed by

Medina [36] and the model FAST [37] developed internally. CEIT also worked on the physically based

model proposed by Zurob [38]. The models of Tata, CEIT and CRM all have a similar basis for the

calculation of austenite recrystallisation and precipitation kinetics. The main equations of the models

are summarised in Table 46.

The dissolution temperatures of Nb(CN) precipitates in each of the project steels were calculated, to

guide the choice of reheating temperature for the thermomechanical tests in WP3. The commercial

software packages Thermo-Calc and ChemSage were used, as well as StripCam and several solubility

product equations taken from the literature. The nominal steel compositions as given in Table 1 were

used. The results are shown in Table 47.

116

Table 46: Main equations for recrystallisation and precipitation kinetics

Nb(C,N) solubility product

[ ] ( )[ ]TAB

NCNbk

/

sol

s10

1412+

+=

(5)

Tata: Irvine [32] CEIT: Palmiere [24] CRM: Choquet [39]

Static recrystallisation kinetics

Time for 50% recrystallisation:

= −−

RT

QDTt rexrsrqp

orex exp5.0 εε &

Austenite fraction recrystallised:

⋅−−=

n

SR.t

tX

X50

2lnexp1

(6)

(7)

Tata: CMn Hodgson [8]

and Nb Husain [40]

CEIT: CMn and Nb

Pereda [27]

CRM: CMn and Nb

StripCam [34]

Recrystallised austenite grain size

−= −−

RT

QADd rexrqp

rex expεε & (8)

Tata : CMn and Nb

Choquet [41]

CEIT: CMn Beynon [42]

and Nb Pereda [27]

CRM: CMn and

Nb Perdrix [43]

Austenite grain growth kinetics

+=

RT

Qtkdd

g

s

mm exp0 (9)

Tata : CMn and Nb

Hodgson [8]

CEIT: CMn Sellars [44]

and Nb Hodgson [8]

CRM: CMn and Nb

Siwecki [45]

Strain induced precipitation kinetics [2]

[ ]( )

ε= −−−

2s

3

5011p050

lnexp

270000exp

kT

B

RTZNbAt

..

⋅ε=

RTQ

expZ &

(10)

(11)

Tata: Dutta [28] CEIT: Pereda [27] CRM: Not determined

117

Table 47: Calculated dissolution temperatures (°C) of Nb(C,N) precipitates in project steels

Partner Steel Thermo-Calc Irvine

[32]

Palmiere

[31]

Koyama

[33] StripCam ChemSage

C1Mn1Nb7 1173 1267 1324 1179 1181 1174

C1Mn2Nb7 1171 1267 1324 1163 1181 1174 AM

C1Mn2Nb3 1086 1148 1195 1038 1117 1064

C1Mn1Nb3 1096 1148 1195 1084 1117 1060

C1Mn1Nb1 996 1019 1056 967 1043 929 Tata

C2Mn1Nb3 1151 1241 1295 1168 1167 1106

C2Mn2Nb3Al2 1227 1241 1295 1136 1167 1067 CEIT

C2Mn2Nb7Al2 1325 1376 1443 1281 1236 1128

C2Mn2Nb3Si2 1212 1241 1295 1242 1167 1084 CRM

C2Mn2Nb7Si2 1307 1376 1443 1373 1236 1180

The Irvine and Palmiere solubility product equations predicted significantly higher dissolution

temperatures than Thermo-Calc and StripCam. The Irvine, Palmiere and StripCam equations do not

take into account the possible effects of Mn, Si or Al, unlike Thermo-Calc and ChemSage. The highest

dissolution temperatures were predicted for the 2%Al steels followed by the 2%Si steels, both with the

highest carbon content. This means that for the majority of the project steels, a reheating temperature

of 1250°C should be sufficient for complete dissolution of the Nb precipitates. However, for steels

C2Mn2Nb7Al2 and C2Mn2Nb7Si2, with a Nb content of 0.07 wt%, the selected reheating temperature

of 1250ºC could lead to partial dissolution of niobium. This was confirmed by TEM analysis of

precipitates in Task 4.3. In the high Al steels, Thermo-Calc and ChemSage also predicted that AlN

would not be completely dissolved at this temperature. The ChemSage dissolution temperatures for the

high Al and high Si steels were significantly lower than those predicted by Thermo-Calc. This was

attributed to differences in the thermodynamic data used for the calculations.

Predictions for recrystallisation curves and recrystallised grain size were carried out using the CEIT,

Tata, CRM (StripCam) and AM models in the first semester of the project for the standard conditions:

C= 0.1, 0.2; Nb = 0, 0.03, 0.07 wt%; strain = 0.2, 0.35; T = 950, 1050ºC; D = 100 µm; strain-rate = 1s-

1. The full results were presented in the 1

st annual report [46]. The main observations from this initial

comparison of the models were:

• The recrystallisation kinetics for all the steels were predicted to be much faster in the Tata

model than in the CEIT, CRM, Medina and FAST models (shorter times for 50% and 90%

recrystallisation).

• The recrystallisation kinetics for all the Nb steels were much slower in StripCam and FAST

than in the other models. In StripCam, the amount of Nb in solid solution was calculated

separately since it was not directly taken into account in the model.

• The recrystallised austenite grain sizes predicted by the models were quite similar, within

10µm of each other, despite using three different equations.

• The time for 5% precipitation of Nb(C,N) was longer in the Tata model than the CEIT model at

0.01 and 0.03Nb but shorter at 0.045 and 0.07Nb. However, combined with the faster

recrystallisation kinetics, the fraction recrystallised when pinning occurred was not always that

different from the CEIT model. StripCam did not predict precipitation pinning and was not yet

accurate enough for describing correctly the SRX kinetics for Nb alloyed steels.

Tata model

Figure 119(a) shows the calculated times for 50% recrystallisation for the 4 steels studied by Tata

under all the different conditions of deformation temperature and strain, plotted against the values

determined from the measured softening curves in the thermomechanical tests carried out in Task 3.2.

Several conclusions can immediately be drawn. Firstly, the model used for recrystallisation in CMn

steels predicted much faster kinetics than were measured in the Gleeble tests. The calculated t50 values

118

were much too short for the C1Mn1 steel, whereas those for the Nb steels were more accurate, if a little

on the high side for the lower strain tests in the 0.03 wt% Nb steels. The original model did not

consider the effect of the different C contents on the kinetics and thus does not distinguish between

steels C1Mn1Nb3 and C2Mn1Nb3, despite the 0.1 wt% difference in carbon. The necessity of

introducing a carbon effect into the model was therefore investigated based on the measured softening

curves.

Overall, the predictions of the existing recrystallisation kinetics model for the Nb steels were generally

good for deformations at 1150 and 1050°C and did not require any major modifications for the

chemistries studied at strains of 0.2 and 0.35. Improvements were required at lower strains of 0.1 or

less, where the softening started more rapidly than predicted by the current model, and at 950°C where

precipitation begins to affect the kinetics. These results indicated that the work should be focussed on

improving the treatment of lower strain deformations and precipitation and their effects on

recrystallisation kinetics. The matrix of tests in Task 3.2 showed that the current Tata equation tended

to over-predict the statically recrystallised austenite grain size as a function of strain, strain rate and

temperature, Figure 119(b), in particular at lower strains, less than 0.1. Improvement of this equation

was therefore also required.

0.0001

0.001

0.01

0.1

1

10

100

0.01 0.1 1 10 100

Measured t50rex (s)

Calculated t50rex (s)

C1Mn1

C1Mn1Nb1

C1Mn1Nb3

C2Mn1Nb3

strain <0.1

(a) time for 50% static recrystallisation

0

40

80

120

160

200

0 40 80 120 160 200

Measured recrystallised austenite grain size (µm)

Calculated recrystallised austenite

grain size (µm)

C1Mn1

C1Mn1Nb1

C1Mn1Nb3

C2Mn1Nb3

strain<0.1

(b) recrystallised austenite grain size

Figure 119: Measured versus calculated results for static recrystallisation tests using original Tata

model

CRM model

The equation used in StripCam to evaluate the dissolution temperature of Nb(CN) is based on

Choquet’s formula [39], which does not take into account the effect of alloying elements such as Si and

Mn but was found to give satisfactory correlation results in a previous study made by CRM where

Nb(CN) carbonitride content was evaluated after electrolytic dissolution. The time for 50% static

recrystallisation is expressed by the empirical equation (12). The temperature dependent effect of Mn is

explained by a solute solution effect. The effect of solute Nb was introduced in the same way as the Mn

effect by changing the activation energy. If the time for 5% niobium precipitation is reached, then the

kinetics of SRX are delayed by a factor of 30 and equation (12) is replaced by equation (13). At the

beginning of the project, no Nb precipitation model was included in StripCam, i.e. the time to reach 5%

Nb precipitation (t0.05p) was not calculated. Niobium precipitates were considered to affect the SRX

kinetics if the Nb content of the steel was non-zero.

(t < t 0.05p)

(12)

(t > t 0.05p)

(13)

119

The preliminary simulations highlighted several points to improve the StripCam model:

- A Nb precipitation model must be introduced.

- The model must be modified to evaluate the amount of Nb in solute solution during reheating

stage.

- The solid solution effect of niobium on the SRX kinetics must be verified

- The law describing the austenite grain growth must be modified since it does not predict

austenite grain size after a multi-pass rolling schedule.

2.3.5.2 Task 5.2: Modelling of static recrystallisation kinetics

Effect of Nb

The equation used to predict the time for 50% recrystallisation, t50, in the Tata model is as follows:

= −−

RT

QDTt rexrqp

orex exp5.0 εε & (14)

where To, p, q, r and Qrex are constants, ε is the strain, ε& the strain rate, D the initial austenite grain

size, R is the gas constant and T the absolute temperature. Currently, different coefficients are used for

CMn steels and Nb steels in the Tata model. One aim of this work was therefore to consolidate into one

consistent equation applicable to all the steels.

The results of the matrix of deformation tests carried out in Task 3.2 using 6 strains, 5 temperatures, 3

austenite grain sizes and 4 strain rates provided data from which new exponents for the terms in

equation (14) have been derived. The softened fraction versus time curves have been fitted with

Avrami curves, as described in Task 3.2, equation (2). The t50 and n values determined from these

curves are listed in Table 17 and Table 18. Table 48 summarises the final coefficients derived for the

t50 equation.

Table 48: Summary of new coefficents for t50 equation in Tata model

Parameter Original value Nb steels (CMn) [40] MICROTOOLS value

To 4.32 x 10-15 (2.0 x 10-19) 3 x 10-10

p 2.3 (4.0) 1.38 (all) or 1.77 (strain>= 0.1)

q 0.5 (2.0) 0.18

r 0 (0.3) 0.05

Qrex (J/mol) 252000 + 9456Mn1.6 + 92000Nb0.21 (275000) 198670+893970Nb

A value for the strain exponent p was derived by keeping strain rate, grain size and temperature

constant, taking logarithms of both sides of the equation and plotting ln(t50) against ln(strain).

Figure 120 shows the results for temperatures of 1150 and 1050°C at a strain rate of 1/s and initial

austenite grain size of 100µm. However, the tests below 0.1 strain appeared to show different softening

behaviour to the higher strain tests and therefore these points have been excluded from the regression

analysis. The value of p can be determined from the gradient of the plots and an average value of p

=1.77 was obtained from the results at 1050 and 1150°C. If the low strain points were included then the

value of p was reduced to 1.38. Both values of p were lower than the value in the existing Tata model,

indicating a weaker effect of strain than currently predicted.

120

y = -2.5521x - 4.8862

R2 = 0.998

y = -1.6009x - 4.0139

R2 = 0.9574

y = -1.8997x - 4.0168

R2 = 0.9982

y = -1.2612x - 2.9876

R2 = 0.7951

-3

-2

-1

0

1

2

3

4

-3.5 -2.5 -1.5 -0.5 0.5

ln(Strain)

ln(t

50%

rex)

C1Mn1

C1Mn1Nb1

C1Mn1Nb3

C2Mn1Nb3

average gradient = 1.83

(a) 1150°C, excluding tests <0.1 strain

y = -1.5401x - 1.9743

R2 = 0.9613

y = -1.7798x - 1.9289

R2 = 0.9846

y = -1.8517x - 3.4788

R2 = 0.9978

y = -1.6545x - 1.8522

R2 = 0.9692

-3

-2

-1

0

1

2

3

4

-3.5 -2.5 -1.5 -0.5 0.5

ln(Strain)

ln(t

50%

rex)

C1Mn1

C1Mn1Nb1

C1Mn1Nb3

C2Mn1Nb3 average gradient = 1.71

(b) 1050°C, excluding tests <0.1 strain

y = -1.3334x - 1.623

R2 = 0.9125

y = -1.1352x - 0.9379

R2 = 0.8486

y = -2.1267x - 3.885

R2 = 0.9769

y = -0.9353x - 0.7217

R2 = 0.7006

-3

-2

-1

0

1

2

3

4

-3.5 -2.5 -1.5 -0.5 0.5

ln(Strain)

ln(t

50%

rex)

C1Mn1

C1Mn1Nb1

C1Mn1Nb3

C2Mn1Nb3 average gradient = 1.38

(c) 1050°C, all tests

Figure 120: Logarithmic plot of measured t50 against strain for a strain rate of 1/s, 100µm initial grain

size

A value for the strain rate exponent r was derived by keeping strain, grain size and temperature

constant, and plotting ln(t50) against ln(strain rate). Figure 121 shows that the gradients of the linear fits

to the data for each steel were quite low, with an average value of r = 0.049. This was much lower than

the value of 0.3 in the equation currently used for CMn steels in the Tata model but closer to the value

of zero used for Nb steels.

y = -0.1477x + 1.1731

R2 = 0.5877

y = 0.0532x + 0.705

R2 = 0.2177

y = -0.117x + 0.4757

R2 = 0.6631

y = 0.0145x - 0.6245

R2 = 0.0349

-2

-1

0

1

2

3

-3 -2 -1 0 1 2 3

ln(strain rate)

ln(t

50) C1Mn1

C1Mn1Nb3

C1Mn1Nb1

C2Mn1Nb3

average gradient = -0.049

Figure 121: Logarithmic plot of t50 against strain rate for strain of 0.2, 100µm initial austenite grain

size and 1050°C temperature

A value for the grain size exponent q was derived by keeping strain rate, strain and temperature

constant, and plotting ln(t50) against ln(grain size). Figure 122(a) shows that a weaker dependence on

121

the initial austenite grain size was found from these tests, with an average value of q = 0.18, much less

than that predicted by the existing Tata equation (Figure 122(b)), where q=0.5 for Nb steels.

y = 0.3458x - 0.8922

R2 = 0.315

y = 0.092x + 0.2058

R2 = 0.2594

y = 0.0766x - 0.1721

R2 = 0.2479

y = 0.2069x - 1.5904

R2 = 0.7267

-1.2

-0.8

-0.4

0

0.4

0.8

1.2

1.6

0 1 2 3 4 5 6

ln(initial austenite grain size)

ln(t

50

)

C1Mn1

C1Mn1Nb3

C1Mn1Nb1

C2Mn1Nb3

average gradient = 0.18

(a) measured t50

y = 0.4626x - 2.3102

R2 = 0.9963

y = 0.4196x - 1.2645

R2 = 0.9961

y = 0.4804x - 2.7237

R2 = 0.9977

y = 0.4995x - 1.6632

R2 = 1

-1.2

-0.8

-0.4

0

0.4

0.8

1.2

1.6

0 1 2 3 4 5 6

ln(initial austenite grain size)

ln(t

50

)

C1Mn1

C1Mn1Nb3

C1Mn1Nb1

C2Mn1Nb3

(b) predicted t50 (original Tata model)

Figure 122: Logarithmic plot of t50 against initial austenite grain size for strain rate of 1/s, 0.2 strain

and temperature 1050°C.

A value for the activation energy for recrystallisation Qrex was derived by keeping strain rate, strain and

grain size constant and plotting ln(t50) against 1/T. Figure 123 shows that the gradient Qrex/R was

approximately constant at each strain and for each steel, with the exception of C2Mn1Nb3 at 0.2 and

0.1 strain where there were only two data points. The average gradient Qrex/R determined from the lines

was 24207 which gives an average value of Qrex = 201260 J/mol. This was lower than the current value

in the model, which predicts values of 275000 for CMn steels, 296433 for C1Mn1Nb1 and 305510 for

C1Mn1Nb3, but similar to other values reported in the literature [47]. A variation in Qrex with Nb

content was found from the individual test results, the higher Nb steels having a greater activation

energy for recrystallisation:

][893970198670(J/mol) NbQrex += (15)

The coefficient T0 was derived from the intercepts of the ln(t50) versus 1/T graphs. A range of values

was derived as this parameter is dependent on the other coefficients chosen. The best fit was obtained

with a value of 3.0 x 10-10

. This is much larger than the coefficients used in the original equation but it

should be noted that the other coefficients in the equation have also changed and affect the value of T0

derived.

To study the effect of Nb addition, a normalised t50 can be calculated which excludes the effect of

deformation conditions and initial grain size, as follows:

53.06.5

5.0

5.0 15.0−− −=εε

τ&

DD

t (16)

Figure 124 shows the τ0.5 values determined from the matrix of tests at different temperatures for

strains of 0.1, 0.2 and 0.35. Increasing Nb led to a retardation of the time for 50% recrystallisation, as

expected. At higher temperatures this can be attributed to Nb solute drag. The amount of retardation

tended to increase with decreasing temperature. This is related to the additional retardation effect of

precipitation, as shown in Figure 22. However, the magnitude of the retardation was smaller than that

observed in the Al steels studied in this project (see results of CEIT in Task 5.2).

122

y = 21567x - 17.786

R2 = 0.9496

y = 18228x - 14.35

R2 = 0.9969

y = 25384x - 18.32

R2 = 0.9995

-3

-2

-1

0

1

2

3

4

0.00068 0.00072 0.00076 0.0008 0.00084

1/T (1/K)

ln(t50% rex)

C1Mn1 0.35

C1Mn1 0.2

C1Mn1 0.1

average gradient = 21726

(a) C1Mn1

y = 28777x - 22.156

R2 = 0.9509

y = 27030x - 20.013

R2 = 0.9942

y = 23581x - 16.256

R2 = 1

y = 27514x - 19.695

R2 = 1

-3

-2

-1

0

1

2

3

4

0.00068 0.00072 0.00076 0.0008 0.00084

1/T (1/K)

ln(t50% rex)

C1Mn1Nb1 0.35

C1Mn1Nb1 0.2

C1Mn1Nb1 0.1

C1Mn1Nb1 0.15

average gradient = 26726

(b) C1Mn1Nb1

y = 27033x - 20.308

R2 = 0.9891

y = 30173x - 22.009

R2 = 1

y = 21355x - 14.035

R2 = 1

-3

-2

-1

0

1

2

3

4

0.00068 0.00072 0.00076 0.0008 0.00084

1/T (1/K)

ln(t50% rex)

C1Mn1Nb3 0.35

C1Mn1Nb3 0.2

C1Mn1Nb3 0.1

average gradient = 26187

(c) C1Mn1Nb3

y = 22191x - 17.045

R2 = 0.8852

y = 40664x - 29.728

R2 = 1

y = 48578x - 34.466

R2 = 1

-3

-2

-1

0

1

2

3

4

0.00068 0.00072 0.00076 0.0008 0.00084

1/T (1/K)

ln(t50% rex)

C2Mn1Nb3 0.35

C2Mn1Nb3 0.2

C2Mn1Nb3 0.1average gradient = 22191

(d) C2Mn1Nb3

Figure 123: Logarithmic plot of t50 against inverse temperature for strain of 0.2, 100µm initial austenite

grain size and strain rate 1/s

900

950

1000

1050

1100

1150

1200

1.0E-06 1.0E-05 1.0E-04 1.0E-03 1.0E-02

Normalised t50% rex

Tem

pe

ratu

re (

°C)

C1Mn1

C1Mn1Nb1

C1Mn1Nb3

C2Mn1Nb3

0.1 strain

(a) 0.1 strain

900

950

1000

1050

1100

1150

1200

1.0E-06 1.0E-05 1.0E-04 1.0E-03 1.0E-02

Normalised t50% rex

Te

mpe

ratu

re (

°C)

C1Mn1

C1Mn1Nb1

C1Mn1Nb3

C2Mn1Nb3

0.2 strain

(b) 0.2 strain

900

950

1000

1050

1100

1150

1200

1.0E-06 1.0E-05 1.0E-04 1.0E-03 1.0E-02

Normalised t50% rex

Te

mpe

ratu

re (

°C)

C1Mn1

C1Mn1Nb1

C1Mn1Nb3

C2Mn1Nb3

0.35 strain

(c) 0.35 strain

Figure 124: Normalised τ0.5 determined for the Nb steels at three strains

The relative effect of different alloying additions on the recrystallisation kinetics has been quantified

by a Solute Retardation Parameter (SRP), which is usually normalised by 0.1 wt% addition [23, 48]:

%100%

1.0log

5.0

5.0 ××

=

wtSRP

refττ

(17)

where τ0.5 is the normalised time for 50% recrystallisation for the alloyed steels (C1Mn1Nb1,

C1Mn1Nb3, C2Mn1Nb3) and τ0.5ref is the normalised time for 50% recrystallisation for the reference

steel C1Mn1. The average SRP values calculated for the Nb additions relative to C1Mn1 for all the

deformation conditions tested are summarised at each temperature in Table 49. The average value of

123

SRP=229 derived in this work for addition of up to 0.03 wt%Nb agrees very well with previously

reported values in the literature of 222 for a 0.035 wt%Nb steel [48] and 239 for a 0.17 wt% Nb steel

[49].

Table 49: Average SRP values calculated at each temperature for the Nb steels

Average SRP Temperature (°C)

C1Mn1Nb1 C1Mn1Nb3 C2Mn1Nb3

1150 157 126 79

1100 636 250 263

1050 454 187 207

1000 322 264 133

The values of the n-exponent in the Avrami equation which has been fitted to the softening curves to

describe the recrystallisation kinetics are plotted in Figure 125 for all the results at 1150 and 1050°C.

The n-values used in the current model are n=1 for CMn steels and n=0.69 for Nb steels. These values

are plotted as grey horizontal lines on the graphs. The value for Nb steels was clearly too low for this

dataset. Analysing all the data, an average value of n=1.09 was derived, shown as the dashed black line.

0.0

0.4

0.8

1.2

1.6

2.0

0 0.1 0.2 0.3 0.4

Strain (-)

n v

alu

e

C1Mn1

C1Mn1Nb1

C1Mn1Nb3

C2Mn1Nb3

n=1

n=0.69

n=1.09

1150°C

(a) 1150°C

0.0

0.4

0.8

1.2

1.6

2.0

0 0.1 0.2 0.3 0.4

Strain (-)

n-v

alu

e

1050°C

(b) 1050°C

Figure 125: Avrami n-values determined from measured recrystallisation curves

Figure 126 shows the final predictions of the time for 50% and 95% recrystallisation using the new

coefficients for t50 and the Avrami equation derived in the project. It can be seen by comparison with

Figure 119 that there has been a significant improvement in the accuracy of the predictions for steel

C1Mn1 in particular, the recrystallisation times having increased in line with the measured values. The

predictions for lower strain (<0.1) tests have also improved.

0.01

0.1

1

10

100

0.01 0.1 1 10 100

Measured t50rex (s)

Calculated t50rex (s)

C1Mn1

C1Mn1Nb1

C1Mn1Nb3

C2Mn1Nb3

(a) t50% rex

0.1

1

10

100

0.1 1 10 100

Measured t95rex (s)

Calculated t95rex (s)

C1Mn1

C1Mn1Nb1

C1Mn1Nb3

C2Mn1Nb3

(b) t95% rex

Figure 126: Measured versus calculated times for 50% and 95% static recrystallisation in static

recrystallisation tests using new Tata model

A further refinement to the equations can be made by considering that a critical strain must be reached

before recrystallisation is initiated and below which only recovery can occur. Examination of the stress

relaxation results in Task 3.2 indicated that this critical strain should be around 0.05, as several of the

124

tests at this strain indicated that recovery was the dominant softening mechanism. Values of t50 were

calculated using the new coefficients and strains adjusted by different values of critical strain, i.e.

ε = εapplied - εcritical. Comparison with the measured t50 values indicated that a critical strain of 0.03 gave

the optimum fit, Figure 127.

0.01

0.1

1

10

100

0.01 0.1 1 10 100

Measured t50rex (s)

Calculated t50rex (s)

C1Mn1 0.03

C1Mn1Nb1 0.03

C1Mn1Nb3 0.03

C2Mn1Nb3 0.03

Figure 127: Measured versus calculated times for 50% static recrystallisation using critical strain

adjustment in new Tata model

The final equation developed to predict the time for 50% recrystallisation, t50, was as follows:

( )

+−×= −−−

RT

NbDt rex

893970198670exp03.0100.3 05.018.038.110

5.0 εε & (18)

Effect of Si

As already mentioned in Task 5.1, no criterion defining the start of precipitation was included in

StripCam. Before starting the modelling of static recrystallisation, a precipitation model was introduced

to determine the start of niobium precipitation after deformation. The precipitation model was similar

to CEIT’s model [27] but considering Choquet instead of Palmiere solubility product to determine both

the supersaturation ratio (equation (5)) and quantity of niobium in solid solution. The model was based

on modified equations of the Dutta and Sellars models from literature data, which assume that

recrystallisation is stopped when the time for 5% precipitation is reached after the deformation. This

time (equation (10)) is dependent on the amount of Nb in solid solution [Nb], the intensity of the

deformation (ε), the temperature compensated strain rate coefficient (Zener-Hollomon parameter Z),

the deformation temperature and the supersaturation ratio (ks). The effect of the different equations for

solubility product on ks is shown in Figure 128. Choquet’s equation predicts that for temperatures

higher than 1026°C, the amount of niobium in solid solution will be higher than that predicted by

Palmiere. For temperatures lower than 1026°C, the tendency is reversed.

Figure 128: Solubility product predicted with Palmiere and Choquet equations

125

For constants A and B in equation (5) , a dependence on the composition was introduced in [27] based

on values of t0.05p from literature data. Considering Palmiere’s solubility product and after applying

the minimum square method on this data, CEIT found a relationship for A and B. Based on the same

literature data, these coefficients have now been recalculated assuming the Choquet solubility product

for each steel grade, see Figure 129 and Figure 130. A minimum square method was then applied on all

results to determine the evolution of coefficients A and B as a function of the solubility product. Red

and blue markers correspond respectively to results obtained with Palmiere and Choquet solubility

product. These results confirm that higher solubility products are obtained with Choquet’s equation

than with Palmiere’s one. The new A and B coefficients obtained with Choquet’s equation were then

introduced into equation (5) to predict the time for 5% precipitation with the StripCam hot rolling

model.

Figure 129: “A” coefficient using Choquet

solubility product

Figure 130: “B” coefficient using Choquet solubility

product

The equation for time to 5% precipitation was experimentally determined in isothermal conditions. In

anisothermal conditions the time for 5% precipitation is calculated applying Scheil’s additivity rule,

which can be expressed as:

(19)

Equations (10) and (19) predict the time for the start of precipitation. The precipitation kinetics are

then described by a KJMA model described in [27]. The time for 50% of recrystallisation, described in

StripCam, is calculated according to equation (12) when no niobium precipitation occurs (i.e. before

reaching t0.05p) and according to equation (13) when there is precipitation (i.e. when t0.05p is reached).

Finally, the recrystallisation kinetics are described by a KJMA model applying Scheil’s additivity rule

in anisothermal condition.

The predictions for recrystallisation curves and recrystallised grain size that were carried out to

compare the existing models of the partners were repeated with the new version of StripCam for the

same conditions. In Figure 131 the dashed curves are the predicted SRX kinetics of the StripCam

version at the beginning of the Microtools project, without kinetics of strain induced Nb(CN)

precipitation. The solid curves are the new predictions by StripCam considering the Nb precipitation

model.

126

(a) C1Mn1 and C2Mn1 (b) C1Mn1Nb1

(c) C1Mn1Nb3 (d) C1Mn1Nb7

(e) C2Mn1Nb3 (f) C2Mn1Nb7

Figure 131: Calculated StripCam SRX kinetics, comparing original (dashed lines) and new models

(solid lines)

The interaction between precipitation and recrystallisation was clearly observed with the “new” version

of StripCam. Indeed, Figure 131(f) shows that for conditions where T=950°C and strain=0.2, when

t0.05p is reached (t=10sec), the recrystallisation kinetics were slowed down. This

precipitation/recrystallisation interaction was not observed with the original StripCam version. The

introduction of this precipitation criterion into StripCam has improved predictions of the time to get

50% of SRX for Nb steel grades, Figure 132. This figure also shows that the solid solution effect of Nb

seems to be overestimated by StripCam. For this reason, the solid solution effect of Nb was modified.

127

Figure 132: Comparison between new and old StripCam model and experimental t50 values for Si steels

The SRX kinetics of StripCam are defined by a KJMA model according to equation (7). The time to

reach 50% static recrystallisation is expressed by equation (12). In the latter equation, the solid solution

effect of niobium is integrated into the thermal activation energy by the following expression:

(20)

To check the predictions of the CRM model compared to experimental results, the calculated t50 was

plotted as a function of the measured time from the CRM, Tata and CEIT experiments, Figure 133(a).

Blue, pink and green markers refer respectively to experimental results obtained by Tata, CEIT and

CRM on the different groups of steels. Filled markers refers to steel grades containing Nb while

unfilled markers are for steel grades that do not contain Nb. CRM and CEIT have measured SRX

kinetics by hot torsion tests with the double hit test method, while SRX kinetics were measured by

stress relaxation for Tata. Furthermore, for direct comparison with the CRM model, the same chart was

built but for calculations made with the CEIT model, Figure 133(b).

Figure 133: Comparison between model and experimental results for t50% SRX

The results reveal that the solid solution effect of Nb is better taken into account in CEIT model than in

StripCam, since filled and unfilled markers are superimposed Figure 133(b). The CEIT model

describes the time to reach 50% static recrystallisation by the following equation:

(21)

128

In the CEIT model, the solid solution effect of niobium does not only depend on the niobium content,

as is the case in StripCam, but also on the temperature. To check the validity of the hypothesis made on

the temperature dependence of the activation energy, the StripCam t0.5SRX equation was fitted to

experimental t0.5SRX values by the adjustment of the QssX parameter, see equation (22), using Excel

solver. Figure 134(a) shows results obtained for steel grades that do not contain Nb while Figure

134(b) gives results for Nb grades. The figure shows clearly that the solid solution effect of niobium is

a function of the temperature as analytically expressed by the CEIT t0.5SRX equation. This temperature

dependence is not considered in StripCam and so the StripCam t0.5SRX equation was modified

accordingly to improve predictions.

(22)

Figure 134: Optimisation of Qssx parameter for different steel grades

The modification was done in two stages. Firstly, the t0.5SRX equation was optimised considering all

t0.5SRX experimental values. In the second stage, the optimisation was only done for small t0.5SRX values

which were in the range of industrial interpass times. Nevertheless, for both stages, the formalism used

to describe the solid solution effect of niobium on t0.5SRX was the same. The formalism in equation (20)

was replaced by equation (23) where K and p are constants, QNb is a thermal activation energy and [Nb]

is the weight per cent of niobium.

(23)

To determine K, p and QNb, all experimental t0.5SRX values from CRM and CEIT were normalised

according to equation (24). Figure 135 gives the evolution of the normalised time as a function of the

temperature. During the decrease of temperature, stronger retardation behaviour appeared for steel

grades alloyed with Nb compared to CMn steel grades. This can be explained in part by the

precipitation of niobium.

(24)

129

Figure 135: Retardation effect on normalised t50

due to the presence of Nb in Si steels

Figure 136: New Nb effect in CRM model

considering a Nb correction from experimental

t0.5SRX data

To estimate and introduce into the model the effect of Nb on t0.5SRX, the τ0.5SRX of steel grades alloyed

with Nb were normalised by the τ0.5SRX of the reference steel grade:

• C2Mn2Si2Nb0 for CRM compositions

• C2Mn2Al1 and C2Mn2Al2 for CEIT compositions

The logarithms of these values were then plotted as a function of the inverse of the temperature to

estimate all coefficients:

(25)

An optimisation procedure was applied to evaluate the best K, p and QNb coefficients from all available

experimental data with a t0.5SRX less than 100s. Coefficients were then introduced into the StripCam

t0.5SRX equation using the formalism in equation (23). Comparison between experimental and calculated

t0.5SRX values using the new model is given in Figure 136. Comparison of Figure 136 with Figure 133

shows that the effect of Nb is better taken into account in the new model. The optimisation was well

performed since new calculated times for steel grades alloyed with Nb (filled markers / continuous

line) are aligned compared to calculated times of non-alloyed steel grade (unfilled markers / dashed

line). During the SRX kinetics study, no effect of Si was observed. The green markers on the graph

reveal that even without introducing a correction in the t0.5SRX equation due to the presence of silicon,

the filled markers are well aligned on unfilled markers. A retardation effect of Al on the SRX kinetics

was experimentally observed. Since no Al effect is currently included in the t0.5SRX equation, an offset

between filled pink markers and unfilled markers was still observed.

The new StripCam t0.5SRX equation taking into account the solid solution effect of niobium is given in

equation (26). A detailed comparison between experimental and calculated results per steel grade is

given in Figure 137. The results show that the StripCam t0.5SRX predictions are improved and give

comparable predictions to the CEIT model.

(26)

130

Figure 137: Detailed comparison between

calculated and experimental t0.5SRX using new

StripCam model

Figure 138: Effect of deformation on t0.5SRX for

Si steels

Concerning the strain effect on the t0.5SRX value, a weight of 2.3 for the deformation exponent is

considered. Experimental results reveal that, depending on the steel grade, the measured exponent

varies from 1.7 to 2.8 (see Figure 138). However, since no effect of silicon on SRX kinetics was

observed, an average linear regression analysis was applied for both C2Mn2Si1 and C2Mn2Si2 data. A

slope of 2.3 and equal to the one already included in StripCam was found.

Effect of Al

The time for 50% fractional softening (t0.5) and the Avrami n exponents obtained from the softening

curves corresponding to all the double hit torsion tests carried out on the Al steels at the different

deformation conditions investigated have been summarised in Table 50.

In order to compare the t0.5 data at the different conditions investigated, a normalised recrystallisation

time, 5.0τ , which is independent of strain, strain rate and grain size was calculated as follows [23]:

53.06.5

0

5.0

5.0 15.00 −− ⋅⋅

= −

εετ

&D

D

t (27)

The τ0.5 values obtained for the different steels and deformation temperatures are plotted in Figure 139.

It can be noticed that both Al and Nb additions lead to a significant retardation in the τ0.5. However, the

microstructural characterisation work carried out indicates that the mechanisms responsible for the

slower softening kinetics depend on steel composition and deformation temperature. The addition of

1wt%Al to the C2Mn2 reference steel results in a time delay at all the temperatures, which can be

attributed to Al solute drag effect on the static softening mechanisms. The same can be said for the case

of 2wt%Al addition above 1000ºC. In this temperature range, further addition of Nb enhances

retardation since the solute drag effect of Nb adds to that exerted by Al.

131

Table 50: Time for 50% fractional softening (t0.5) and Avrami n exponents determined from the

softening curves of the Al steels.

Steel TDEF(ºC) εεεε VDEF (s-1) D0 (µm) t0.5 (s) exp. n exp.

C2Mn2 1065 2.2 0.87

1000 4.24 0.81

925

∼69

12.2 0.87

1065 4.2 0.84

1000 8 0.85

925

0.35

31.1 0.84 C2Mn2Al1

1065 0.2

~100

23.15 0.82

1065 259.7 0.73

1000 16.6 0.65

965 58.15 0.51

925

0.35

6.9 0.32

C2Mn2Al2

1065 0.2

~65

28.8 0.71

1065 8.27 0.87

1000 19.31 0.7

925 1754 0.23 C2Mn2Al1Nb3

900

0.35 ~100

** **

1065 12.2 0.63

1000 51.77 0.5

965 ** 0.31 C2Mn2Al2Nb3

925

0.35 ~65

5650 0.23

1065 24.81 0.52

1000 98.45 0.43 C2Mn2Al2Nb7

965

0.35

1

~56

4156 0.26

However, at temperatures below 1000ºC for the C2Mn2Al2 and C2Mn2Al2Nb steels a more

pronounced retardation is observed. This can be attributed to the interaction between softening and

other phenomena. For 2%Al steels, as previously mentioned, γ→α phase transformation takes place

concurrently with static softening and this leads to a strong retardation effect. This behaviour can be

attributed to the competition between recrystallisation and phase transformation as both processes

share the prior austenite grain boundaries as nucleation sites for recrystallised and ferrite grains.

Therefore first consumption of austenite grain boundaries by ferrite grains could prevent to some extent

the occurrence of recrystallisation. When Nb is added, softening evolution becomes even more

complex due to its interaction with phase transformation as well as strain induced precipitation. In

C2Mn2Al2Nb steels a combination of both mechanisms results in very long softening times or even

incomplete softening. In the C2Mn2Al1Nb3 steel, strain induced precipitation of Nb(C,N) particles

appears to be the main mechanism responsible for softening retardation at the lowest temperature of

925ºC.

Therefore the results indicate that for the C2Mn2 and C2Mn2Al1 steel at all the temperatures

investigated, and for the 2%Al steels and C2Mn2Al1Nb3 at the highest temperatures, static softening

occurs due to recovery and recrystallisation, whereas at lower temperatures, for the 2%Al steels γ�α

phase transformation and for the Nb microalloyed steels strain-induced precipitation also take place

and lead to a significant retardation in the softening kinetics. Due to this, in the static recrystallisation

analysis, the latter data will be excluded.

132

900

950

1000

1050

1100

0.001 0.01 0.1 1 10τ0.5

T (ºC)

C2Mn2

C2Mn2Al1

C2Mn2Al2

C2Mn2Al1Nb3

C2Mn2Al2Nb3

C2Mn2Al2Nb7

Figure 139: Normalised t0.5 calculated using equation (27) for the different steels.

At CEIT, the following semi-empirical equation was determined for calculating the t0.05 for Nb

microalloyed steels [5]:

[ ]

⋅

−⋅

⋅⋅⋅⋅= −−− −

NbTRT

DxtD

185275000

exp180000

exp1092.9 53.06.5

0

11

5.0

15.00 εε & (28)

In Figure 140 the experimental t0.5 values are plotted against the values calculated with equation (28)

for all the steels investigated. It can be observed that for the C2Mn2 steel, a good fit between the

predicted and experimental values is obtained, while for the rest of the steels the experimental values

tend to be larger than the calculated ones. It can also be observed that the experimental t0.5

corresponding to all the 2%Al steels show a larger retardation level than the data corresponding to the

1%Al steels, independently of their Nb content. In good agreement with the results shown above, this

denotes that Al addition results in softening retardation and also indicates that equation (28) includes

adequately the effect of Nb in solid solution.

0.1

1

10

100

1000

10000

0.1 1 10 100 1000 10000t0.5 (exp.)

t 0.5 (CEIT model)

C2Mn2

C2Mn2Al1

C2Mn2Al1Nb3

C2Mn2Al2

C2Mn2Al2Nb3

C2Mn2Al2Nb7

Figure 140: Comparison of experimental t0.5 and the t0.5 values given by equation (28) for the steels

investigated.

In order to quantify the softening delay exerted by Al in solid solution the Solute Retardation

Parameter (SRP) was calculated by equation (29) [23], again excluding the conditions where

precipitation or phase transformation takes place:

%100.%

1.0ln

5.0

5.0 xwt

xSRPREF

=

ττ

(29)

133

where τ0.5 is the normalized recrystallisation time of the Al alloyed steels (C2Mn2Al1, C2Mn2Al2 and

C2Mn2Al2Nb3) and τ0.5REF is the normalized time calculated for the reference steels (i.e. C2Mn2 for

the first two steels and C2Mn2Al1Nb3 for the other steel).

The SRP values obtained at the different conditions investigated have been summarised in Table 51.

An average value of SRP = 6 was obtained for Al. This value is significantly lower than those reported

in the literature for common microalloying elements such as Nb (SRP=222) [48]. However, it must be

noticed that the amount of Al considered in this work is nearly one order of magnitude higher than the

Nb contents in the range 0.02-0.07 wt.% typically found in microalloyed steels. The retardation exerted

by 1 wt% and 2 wt% Al is equivalent to that exerted by 0.027 wt.% and 0.054 wt% Nb, respectively.

Table 51. SRP values for the Al steels calculated following equation (29).

T(ºC) SRP

1065 1000 925

C2Mn2Al1 vs. C2Mn2 5.0 4.0 7.52

C2Mn2Al2 vs. C2Mn2 6.1 7.1 -

C2Mn2Al2Nb3 vs. C2Mn2Al1Nb3 5.52 - -

Taking into account the above results the equation proposed by Fernandez et al. [5] for the time to

reach 50% recrystallisation was implemented to include the effect of Al in solid solution as follows:

[ ] [ ]( )

+⋅

−

×= −−− −

AlNbTRT

DtD

027.0185275000

exp180000

exp1092.9 53.06.5

0

11

0.5SRX

15.00 εε & (30)

where [Nb] and [Al] represent the wt.% concentrations of dissolved Nb and Al, respectively. Figure

141 illustrates the good correlation between experimental data and the values calculated using equation

(30).

0.1

1

10

100

1000

10000

0.1 1 10 100 1000 10000

t0.5SRX (exp.)

t 0.5SRX (CEIT model)

C2Mn2

C2Mn2Al1

C2Mn2Al1Nb3

C2Mn2Al2

C2Mn2Al2Nb3

C2Mn2Al2Nb7

Figure 141: Comparison between t0.5 experimental data and predictions of equation (30).

Physical modelling

Although semi-empirical models are a very useful tool in order to describe the austenite microstructural

evolution during hot working, physical models are not limited to the conditions they were developed

for, and in addition, they can provide valuable insight into the processes that occur during hot rolling.

Therefore, at CEIT the applicability of a physical model in order to describe the effect of Al on the

static softening of the project steels was investigated. As in the case of the empirical modelling

approach, the conditions at which phase transformation or strain-induced precipitation took place were

excluded.

134

In the model, recrystallisation evolution is modelled based on the JMAK approach. Assuming a random

distribution of nuclei and site-saturation conditions, the evolution of the recrystallised fraction with

time can be expressed as:

−−= ∫

3

0

)(exp1

t

REXREXREX dtFtMNX (31)

where REXN is the initial number of recrystallisation nuclei,

REXF is the driving force for

recrystallisation and )(tM is grain boundary mobility. REXF can be related to the instantaneous

dislocation density, )(tρ , through a relationship of the type:

2)(2

1btFREX µρ= (32)

In this equation µ is the temperature dependent shear modulus of the matrix

( ( )[ ]Pa1810/300)(91.01081 9 −−⋅×= KTµ [51]) and b is the Burgers vector. )(tρ is related to the

flow stress of the austenite through a forest type hardening relation:

)()( tbMt Ty ρµασσ += (33)

where yσ is the yield stress, M the Taylor factor (M = 3.1 for FCC metals) and

Tα a constant of the

order of 0.15.

The recovery kinetics are modelled using the approach of Verdier et al. [52]. In their model, the rate of

stress relaxation due to dislocations is given by:

( ) ( ) ( )

−

−

−−=

−

kT

Vt

k

U

EM

t

dt

td aya

T

dyy σσ

α

νσσσσ )(sinhexp

9

)(64)(

23

2

T (34)

where E is Young´s modulus ( ( )0.3312 += µE Pa [51]), dν is the Debye frequency, and aU and aV

are the activation energy and activation volume for the recovery process. Following [53], the activation

volume can be expressed as:

aa lbV 2= (35)

where al is an activation length which varies depending on the recovery controlling mechanism. If

either climb of edge dislocations or glide of jogged screw dislocations are the recovery rate controlling

mechanisms, the activation length can be approximately described by [54]:

ρ1kla = (36)

where k1 is a constant. Combining equations (33), (35) and (36) yields a value for the activation length

due to dislocations of:

y

Ta

bMkl

σσµα

−= 1 (37)

In order to apply the model, if the experimental flow curves for the deformed austenite are available,

the initial dislocation density and the recrystallisation driving force can be calculated through equations

(33) and (32), respectively. Recrystallisation progression after deformation is evaluated by the

numerical integration of equation (31). At each time interval, the dislocation density decrease due to

recovery is calculated using equations (33) and (34). The calculated dislocation density is then used as

input for equation (31), thus taking the effect of recovery on the driving force for recrystallisation into

account.

Several works have discussed the application of physical models in order to predict the softening

kinetics of austenite. However, there are still uncertainties concerning the values of some of the

parameters involved, and some of them can vary depending on steel composition. In the case of

recrystallisation, the number of recrystallisation nuclei, REXN , the driving force for recrystallisation,

REXF , and grain boundary mobility )(tM can be affected by steel composition. In the case of recovery,

135

both the activation energy and volume, aU and aV , have also been reported to be dependent on both

steel composition and deformation conditions [53]. In order to apply the model, first the parameters

corresponding to the base C2Mn2 steel will be considered, and next, the effect of Al addition will be

investigated.

Firstly, modelling of the softening evolution in the base C2Mn2 steel was undertaken. To allow a

comparison with the experimental softening data, a simulated fractional softening value is calculated.

The yield stress of the initial softened material, 0σ , and of the deformed material, mσ , are obtained

from the experimental flow curves for each test condition. The value of the partly softened material,

rσ , varies with interpass time and can be calculated by using a mixture rule that combines the

recrystallised fraction at each time, REXX (obtained from the recrystallisation model, equation (31),

coupled to the recovery model), with the stress present in the unrecrystallised material at each step,

)(tσ (obtained from the recovery model, equation (34)):

)()1( tXX REXREXREXr σσσ −+= (38)

In the above equation REXσ is the value of the yield stress of the fully recrystallised matrix. In the

absence of precipitation, only the effect of the grain size difference between the initial undeformed and

recrystallised material on the stress level should be taken into account in order to calculate REXσ . In

order to do so, the following dependence proposed by Yoshie et al. has been considered [55]: 07.0

0

0

−

=

D

DREXREX σσ (39)

where 0D is the initial grain size and REXD the grain size of the recrystallised microstructure.

In this work, the number of nuclei,REXN , was estimated through the experimentally measured

recrystallised grain size, REXD , as:

13

23

4−

= REX

REX

DN π (40)

The recrystallisation driving force, REXF , was calculated from the experimental flow stress curves by

applying equations (32) and (33).

The activation energy for the recovery process, aU , is expected to lie between 0.6 and 1 times Qdiff,

where Qdiff is the activation energy for self-diffusion or solute-diffusion, depending on the recovery

rate controlling process [54]. The self-diffusion activation energy of the austenite ∼286 kJ/mol is higher

than the activation energy for the diffusion of the alloying elements commonly considered to retard

softening processes in austenite (∼260-270 kJ/mol for Nb or Mn), and therefore values close to 286

kJ/mol have been employed in different works [56]. In terms of the determination of the activation

volume for recovery, aV , several authors have used stress relaxation tests [57,58]. However, there is a

considerable spread within the determined values, ranging from 15b3 [59] to 45b

3 or 230-690b

3 [58],

with b the Burgers vector magnitude. Bearing in mind that steel composition and deformation

conditions can have an influence on the mechanisms affecting recovery in this work, the values

determined by Smith et al. [57] were considered. In their work, tests with deformation conditions

similar to those employed in this study (ε=0.2 to 0.5, ε&=0.1 to 1 s-1, TDEF=850 to 950ºC) were carried

out with a steel whose composition was quite similar to the present CMn steel (0.16%C-1.46%Mn-

0.4%Si-0.03%Al). These authors obtained a value of aU = 314 kJ/mol and a value of 1k = 0.31 in

equation (37) in order to calculate aV . It should be noted that in [57] a constant value of aV during

softening was assumed and the calculations were made taking the initial internal stress due to

dislocations into consideration. The same approach has been taken in the present study.

136

A commonly used approach for estimating the grain boundary mobility for CMn steels is to consider a

fraction of Turnbull’s mobility [60]. This equation, which ignores all possible attachment kinetics,

provides an upper estimate for the grain boundary mobility:

RTb

VDM MGB

Pure 2

δ= (41)

where δ is the grain boundary width (assumed 1 nm), GBD is the grain boundary self-diffusion

coefficient (

−= −

RT

159000exp10x5.7D 5

GB (m2/s)), R is the gas constant, VM is the molar volume

austenite (6.85x10-6

(m3/mol)), and T is the absolute temperature.

In the present work, the value of )(tM in Equation (31) for the base CMn steel was calculated by

fitting the t0.5 softening time predicted with the model to the experimental value measured at each test

temperature. The obtained mobility values are summarised in Table 52, together with the ratio to

PureM given by Equation (41). The resulting values are in the range of those considered in other works

[59]. However, it must be mentioned that in this case taking an average value of this ratio for the three

test temperatures leads to a significant error between the experimental results and the predictions of the

model, which indicates that there might be an additional effect of temperature on this parameter. An

increase in this ratio would indicate an enhanced effect of temperature on reducing mobility as the

temperature decreases.

Table 52: Calculated grain boundary mobilities for the C2Mn2 steel and the ratio between mobility for

a pure material calculated by equation (41) and these values.

T (ºC)

ε

Mobility

⋅ sJ

m4

MPURE/Mobility

1065 2.26E-10 1.9

1000 8.86E-11 2.4

925

0.35

1.43E-11 6.3

The temperature dependence of the grain boundary mobility calculated for the C2Mn2 steel has been

shown to fit well to an Arrhenius type relationship of the form ( )RTQMM −= exp0 , with M0=5.03

sJ

m

⋅

4

and Q=264800 J/mol. This type of relationship is usually found to be valid for pure materials,

with Q values close to the grain boundary diffusion coefficient. However, in this case the calculated

exponential factor is considerably higher than the grain boundary diffusion coefficient of iron more

closely related to the diffusion activation energies of solute Mn (264 kJ/mol) or to the activation energy

for Fe self-diffusion (286 kJ/mol). The supposition implied in the Turnbull estimation, i.e. that during

grain boundary migration the atoms transfer in a way that is similar to the elementary action involved

in atom transport during grain boundary self diffusion, seems to fail in this case. The relatively high

Mn content of this steel (2%) could have an effect on retarding mobility as well. As a consequence, the

mobility of recrystallizing boundaries would be better explained by solute drag due to manganese

atoms.

Therefore, the following equation was used for modelling grain boundary mobility for the base steel:

−=RT

MNTI

264800exp03.5

(42)

137

Figure 142 shows the softening evolution predicted by the model (solid lines) compared to measured

softening data (symbols). In Figure 142(b) the predictions of the softening and recrystallisation models

for temperatures of 1065ºC and 925ºC are plotted. From the figure it can be observed that the softening

curves predicted by the model fit reasonably well the experimental results. It can also be noted that the

model predicts that the fractional softening levels are of 27-30% when recrystallisation is predicted to

start (5%), while fractional softening levels of 50% correspond to recrystallised fractions of ∼27-30%.

These values are in the range of the metallographic measurements for the C2Mn2Al1 steel (see Task

4.1).

0

0.2

0.4

0.6

0.8

1

0.1 10 1000t (s)

Fractional Softening

T=1065ºC

T=1000ºC

T=925ºC

C2Mn2, εεεε=0.35

0

0.2

0.4

0.6

0.8

1

0.1 1 10 100 1000t (s)

Fractional Softening

C2Mn2, εεεε=0.35

Rex., 1065ºC

Softening, 1065ºC

Rex., 925ºC

Softening, 925ºC

Figure 142: (a) Comparison between the model predictions and experimental softening data and (b)

softening and recrystallisation model predictions for the C2Mn2 steel at 925 and 1065ºC.

The above experimental results denote that 1 to 2% Al addition leads to noticeable retardation in the

softening kinetics in the steels investigated. In order to take into account the retarding effect of solute

atoms on the recrystallisation kinetics, the model proposed by Cahn [50] is usually employed. In the

model, the steady impurity composition profile of a grain boundary moving at a constant velocity is

calculated, and then the composition profile is used to formulate the force exerted by the impurity

atoms. By assuming a constant solute cross-boundary diffusion coefficient and an edge-shaped

interaction energy profile, two approximated limiting laws for the drag force can be obtained for high

and low boundary velocities (low and high driving forces). In the case of recrystallisation after

deformation at high temperatures, relatively low driving forces are obtained. In this regime, the model

predicts a linear relationship between the driving force and the grain boundary velocity, which allows

the following effective mobility for the solute affected grain boundary to be calculated:

1

1−

+= s

INT

s CM

M α (43)

where INTM is the intrinsic mobility of the impurity free material (calculated in this case with equation

(42)), Cs is the impurity concentration and α can be calculated from:

( )

−

=

kT

E

kT

E

DE

kTN bb

b

V sinh

2δα (44)

δ is the grain boundary width (assumed as 1 nm), Nv is the number of atoms per unit volume (Nv = 1/

VM =1.46x105

(m-3)), Eb is the binding energy of solute atoms to grain boundaries and D is the cross-

boundary diffusion coefficient. According to the model, the main compositional parameters affecting

the drag force are the cross-boundary diffusivity, D, and the interaction energy of the solute with the

grain boundaries, Eb. The equations shown above indicate that in the low driving force case, impurities

with larger absolute Eb values lead to higher drag effects while faster diffusing impurities result in

lower drag effect.

138

The value of Eb can be calculated by assuming that the grain boundary is built up of dislocations from

Cottrell’s formula [61]:

Fe

FeFeb

r

rrrE

−

−

+=

σσ

µ1

1

3

4 3 (45)

where σ is Poisson’s ratio for iron and rFE and r are the atomic radii of iron and of the solute,

respectively (Table 53).

Estimating the cross-boundary diffusivity is difficult in general, and it has been approximated as the

diffusivity of the solute atoms in the bulk as impurity, DBulk, [29], or as a multiple of this value, with

values ranging from 10DBulk [62] to 100DBulk

[63]. With regard to Al diffusivity (DBulk), it must be

mentioned that there are significant differences within the diffusion coefficients found in the literature.

In the present work, the diffusion coefficient indicated in Table 53 [64] was chosen for the

calculations.

Table 53: Al bulk diffusion coefficient and atomic radius data employed.

Al [64]

D0 (m2/s)

4109.5 −x

Diffusion coefficient in γ:

−RT

QD 0

0 exp

Q0 (kJ/mol) 241

Fe Al Atomic radius (nm) [61,65]

0.127 0.1432

In order to apply the model to the C2Mn2Al1 and C2Mn2Al2 steels, the solute drag retardation effect

due to Al addition was estimated through equations (43) and (44) by fitting the calculated 50%

softening times, t0.5, to the experimental data, taking the value of the cross-boundary diffusivity (D) as a

fitting factor. An average value of D = 7DBulk, was obtained. This value is in the range of the values

obtained for other microalloying additions [62]. In Figure 143 the experimental softening data obtained

for both steels at different deformation conditions are compared to the model’s predictions. The figure

shows fairly good agreement between the experimental and predicted softening data in the case of

C2Mn2Al1 steel (Fig. 143(a,c)), whereas for the C2Mn2Al2 steel (Fig. 143(b,d)) although the fit

cannot be considered bad, there is a slight tendency for the model to overestimate the softening, mainly

at the highest temperature. On the other hand, for both steels and lower deformation ε=0.2, the model

clearly overestimates the experimental softening results.

Model deviations, which are mainly observed for the highest Al content and lower deformation,

suggest a possible overestimation of the calculated recovery kinetics. In the model it is assumed that

the recovery rate is only controlled by dislocation glide or climb, however, in the presence of solutes,

solute drag could also play a role in recovery. This means that in addition to the retarding effect

produced by Al on recrystallisation kinetics (modified mobility term), a retardation effect of Al on the

recovery rate should also be considered in modelling. Although the effect of solute atoms on recovery

has been less studied than their effect on recrystallisation, data that indicate that elements like Nb or

Mo in solid solution may retard the recovery kinetics of austenite have also been reported [54]. Taking

this into account, the effective activation length for the calculation of the activation volume in equation

(36) should include contributions from both the solute-atoms and dislocations. A simple model, which

considers the two contributions added in parallel, is considered here, leading to an equation of the form

[59]:

2

n

1SDDisloceffective K

C

Kl

1

l

1

l

1+=+=

ρ (46)

139

where C represents the atomic concentration of the solute. Taking the values of K1 = 0.31 and aU = 314

kJ/mol [57], as previously used for the C-Mn steel, and n= 2/3 [54], the constant K2 was adjusted. The

best fit was obtained with a value of K2 = 1x10-8 and D=5Dbulk. The results obtained with the modified

model at different conditions, shown in Figure 144, indicate that in most cases better predictions are

obtained when using the second approach.

0

0.2

0.4

0.6

0.8

1

0.1 10 1000t (s)

Fractional Softening

T=1065ºCT=1000ºCT=925ºC

C2Mn2Al1

εεεε=0.35

(a) C2Mn1Al1, 0.35 strain

0

0.2

0.4

0.6

0.8

1

0.1 1 10 100 1000t (s)

Fractional Softening

T=1065ºC

T=1000ºC

C2Mn2Al2

εεεε=0.35

(b) C2Mn1Al2, 0.35 strain

0

0.2

0.4

0.6

0.8

1

0.1 1 10 100 1000t (s)

Fractional Softening

T=1065ºC

C2Mn2Al1

εεεε=0.2

(c) C2Mn2Al1, 0.2 strain

0

0.2

0.4

0.6

0.8

1

0.1 1 10 100 1000t (s)

Fractional Softening

T=1065ºC

C2Mn2Al2

εεεε=0.2

(d) C2Mn2Al2, 0.2 strain

Figure 143: Comparison between the experimental softening/recrystallisation data and the model

(D=7Dbulk) predictions at different temperatures and strains for the C2Mn2Al steels

Finally, it can be noted that although the model predictions are significantly improved using this

approach, the fit tends to be worse at the highest softening levels both for the C2Mn2 (Figure 142) and

for the Al steels (Figure 144). In several cases, at long interpass times the mechanical softening tends to

deviate from the predicted curve and the model overestimates the experimental softening. This type of

behaviour, in which the softening shows retardation at high softening levels, has also been observed in

other cases [66] and has been attributed to the heterogeneity of the stored energy of deformation. This

suggests that the fit may be improved by assuming a non-uniform stored energy distribution; however,

within the simplicity of the model a good fit is obtained for the data considered.

140

0

0.2

0.4

0.6

0.8

1

0.1 10 1000t (s)

Fractional Softening

T=1065ºCT=1000ºCT=925ºC

C2Mn2Al1

εεεε=0.35

(a) C2Mn1Al1, strain=0.35

0

0.2

0.4

0.6

0.8

1

0.1 1 10 100 1000t (s)

Fractional Softening

T=1065ºC

T=1000ºC

C2Mn2Al2

εεεε=0.35

(b) C2Mn1Al2, strain=0.35

0

0.2

0.4

0.6

0.8

1

0.1 1 10 100 1000t (s)

Fractional Softening

T=1065ºC

C2Mn2Al1

εεεε=0.2

(c) C2Mn1Al1, strain=0.2

0

0.2

0.4

0.6

0.8

1

0.1 1 10 100 1000t (s)

Fractional Softening

T=1065ºC

C2Mn2Al2

εεεε=0.2

(d) C2Mn1Al2, strain=0.2

Figure 144: Comparison between the experimental softening data and the predictions of the modified

model (D=5Dbulk, K2 = 1x10-8) at different deformation conditions for the C2Mn1Al steels

Physical modelling of solute drag was also investigated by Tata within the project. Solute drag on grain

boundaries has long been recognised as an important mechanism for limiting the rate of

recrystallisation and grain growth during hot rolling of steels. It is less potent than pinning of grain

boundaries by precipitates which can halt grain boundary movement completely. Solute drag is thus

most effective in non-microalloyed steels and in microalloyed steels prior to pinning. The first

complete model explaining the phenomenon was developed by Cahn [50], as described in equations

(43) and (44). Cahn’s model is an example of a continuum model which smoothes over the crystalline

nature of the grains. An alternative atomistic approach was taken by Lücke and Stüwe [67] in which

they consider atomic layers on either side of the grain boundary. The number of atomic layers on which

the solute drag force needs to be evaluated is limited, simplifying the calculations, making it feasible to

remove the simplifications made by Cahn. An example of such an approach in which site saturation is

taken into account is given by Mendelev and Srolovitz [68].

In this project it was originally intended to pursue the atomistic approach, including the effect of

multiple solutes in the slow speed regime (when solute retardation is effective) to incorporate the

effects of solute drag from all solutes into the recrystallisation kinetics equations by modifying the time

to 50% recrystallisation. However, this analysis implies that the time to t50 will be inversely

proportional to the grain boundary speed, and thus directly proportional to the solute composition.

∑∝∝i

iiCPv

t α11

50 (47)

141

This is contradicted by numerous experimental results which show that both t0 (the recovery time to

the start of recrystallisation) and t50 have an exponential dependence on composition, for example [69-

72]. This implies that what is happening prior to recrystallisation during initial recovery is playing an

important role in determining the recrystallisation kinetics. In the light of the above it was decided to

investigate the initiation of recrystallisation, t0, rather than develop an atomistic model of

recrystallisation as originally intended. An examination of recrystallisation incubation also better

complements the work of the other partners, who concentrated on the progress of recrystallisation.

In order to investigate the recovery and recrystallisation kinetics plots of fraction softened versus log

time were used, where the fraction softened is defined as

0

0

σσσ −

=F (48)

where F is the fraction softened, σ0 is the initial stress at the start of relaxation, and σ is the current

relaxation stress. With this definition curves can be plotted even if the test was not long enough to

capture the end of recrystallisation or recovery. Also, much of recovery can be described by an

equation of the form

( )BtA

RTF += 1ln (49)

which is independent of stress and therefore of the applied strain for a given temperature. R and T have

their usual meanings, and A and B are parameters.

C1Mn1Nb3

1050 °C

0.0

0.2

0.4

0.6

0.8

1.0

0.001 0.1 10 1000

Time (s)

Softened fra

ctio

n (

-)

0.35 strain

0.2 strain

0.15 strain

0.1 strain

0.075 strain

0.05 strain

Recovery

Figure 145: Example Fraction Softened plot versus Log Time

An example of such a plot is given in Figure 145 where it can be seen that the softening curves for

different starting strains follow the same path before successively diverging as they start to

recrystallise. The fitted recovery curve follows the data remarkably well considering that it is a simple

recovery model. The kink in the data around a time of 0.1s at which the initial relaxation curves and the

recovery line come together seems to be the point that any post-dynamic recovery due to the hit comes

to an end, and from which fully static recovery can then continue. (Nothing in the recorded data

suggests that this is a machine effect.)

Using the results of low strain tests (0.05 and 0.1 strain) the following values of A and B were found to

describe the recovery curves of all the steels remarkably well, with no account having to be taken of the

different steel chemistries: - 51023.1 ×=A

−=RT

ExpB71100

97400 (50)

The recovery curves are shown in Figure 146. Even at these low strains, recrystallisation can be seen to

accelerate softening taking the curves above the fitted recovery lines especially for C1Mn1 and to a

lesser extent the C1Mn1Nb1 steel. Unlike the current recovery model, more sophisticated recovery

theories of Nes [54] and Verdier et al. [52] predict that the rate of softening slows down at high

fractions softened so that values cannot exceed unity. It is therefore remarkable that many of the

142

recovery curves deviate so little from the simple model predictions before making the transition to the

creep regime. Only the Nb containing steels (Figure 146(b-d)) at 950 °C show any significant slow

down, and rather than gradual deceleration, it is an abrupt change in slope, suggesting that precipitates

have formed, making dislocation movement more difficult.

Low Strain

C1Mn1

0.0

0.2

0.4

0.6

0.8

1.0

0.001 0.1 10 1000Time (s)

Soft

ened f

raction (

-)

0.1 950°C0.05 1050°C0.1 1050°C0.1 1150°C 950°C Fit1050°C Fit1150°C Fit

(a) C1Mn1

Low Strain

C1Mn1Nb1

0.0

0.2

0.4

0.6

0.8

1.0

0.001 0.1 10 1000

Time (s)

Soft

ened f

raction (

-)

0.1 950°C0.05 1050°C0.1 1050°C0.1 1150°C 950 °C Fit1050 °C Fit1150 °C Fit

(b) C1Mn1Nb1

Low Strain

C1Mn1Nb3

0.0

0.2

0.4

0.6

0.8

1.0

0.001 0.1 10 1000Time (s)

Soft

ened f

raction (

-)

0.1 950 °C0.05 1050 °C0.1 1050 °C0.1 1150 °C0.05 1150 °C 950 °C Fit1050 °C Fit1150 °C Fit

(c) C1Mn1Nb3

Low Strain

C2Mn1Nb3

0.0

0.2

0.4

0.6

0.8

1.0

0.001 0.1 10 1000Time (s)

Soft

ened f

raction (

-)0.1 950 °C0.05 1050 °C0.1 1050 °C0.05 1150 °C 950 °C Fit 1050 °C Fit1150 °C Fit

(d) C2Mn1Nb3

Figure 146: Recovery curves fitted to low strain test results

Although not required for the determination of the start of recrystallisation, the relaxation curve after

recrystallisation completed was also investigated. It is assumed that once recovery and/or

recrystallisation has completed that softening continues via a creep mechanism. As an example, the

flow stress curves in Figure 147 correspond to the fraction softening curves in Figure 145. It seems that

in the final creep regime that the stress curves converge together rather than the fraction softening

curves.

C1Mn1Nb1

1050 °C

0

10

20

30

40

50

1 10 100 1000Time (s)

Str

ess (

MP

a)

0.35 strain

0.2 strain

0.15 strain

0.1 strain

0.075 strain

0.05 strain

Figure 147: Example plot of Relaxation Stress versus Log Time

143

In the creep regime the stress decreases roughly linearly with log time: -

( )tBACreep 11 ln+=σ (51)

At 1050°C and 1150°C it was found that all the steels behaved the same, but at 950°C they behaved

differently, Table 54.

Table 54: Stress Relaxation Parameters in Creep Regime

Temp (°C) Steel A1 (MPa) B1 (s-1)

1150 All 18.3 -1.9

1050 All 19.8 -1.68

C1Mn1 33 -3.4

C1Mn1Nb1 38.9 -3.5

C1Mn1Nb3 43.7 -3.6 950

C2Mn1Nb3 49.1 -3.7

The creep curves can be plotted on the fraction softened graphs, but the lines are displaced depending

on the initial stress level as shown in Figure 148 for the C1Mn1Nb1 steel at different temperatures. The

area between the recovery line (which is also plotted) and the creep lines defines the region in which

recrystallisation can occur. This can be helpful in deciding whether recrystallisation has started or

completed in marginal cases.

C1Mn1Nb1

1150 °C

0.0

0.2

0.4

0.6

0.8

1.0

0.001 0.1 10 1000Time (s)

Soft

ened f

raction (

-)

0.35 strain0.2 strain0.15 strain0.1 strainRecovery0.35 Creep0.1 Creep

(a) 1150 °C

C1Mn1Nb1

1050 °C

0.0

0.2

0.4

0.6

0.8

1.0

0.001 0.1 10 1000Time (s)

Soft

ened f

raction (

-)

0.35 strain0.2 strain0.15 strain0.1 strain0.075 strain0.05 strainRecovery0.35 creep0.05 Creep

(b) 1050 °C

Figure 148: Example plots of Fraction Softening Plots for C1Mn1Nb1 Steel including Fitted Creep and

Recovery Lines

In order to determine the starting time for recrystallisation it was decided to project the lines when

recrystallisation was clearly under way back onto the fitted recovery curves, and use the points where

they crossed. The results are shown for the C1Mn1 steel which had more curves that showed

recrystallisation than the other steels, and whose results were most self-consistent, Figure 149.

Using this data, t0 for the C1Mn1 steel was found to be a function of temperature and strain, Figure

150(a) (all tests used were at a strain rate of 1 s-1 and had an initial austenite grain size of about 100

µm).

)98.0(R 000,194

exp1087.8 271.211

0 =

×= −− εRT

t (52)

144

C1Mn1

1150 °C

0.2

0.3

0.4

0.5

0.6

0.7

0.01 0.1 1 10

Time (s)

Soft

ened f

raction (

-)

(a) 1150 °C

C1Mn1

1050 °C

0.2

0.3

0.4

0.5

0.6

0.7

0.01 0.1 1 10

Time (s)

Soft

ened f

raction (

-)

(b) 1050 °C

C1Mn1

950 °C

0.2

0.3

0.4

0.5

0.6

0.7

0.1 1 10 100

Time (s)

Soft

ened f

raction (

-)

(c) 950 °C

0.2

0.3

0.4

0.5

0.6

0.7

0.

01

0.

1

110

0.35 strain0.2 strain0.15 strain

0.1 strain0.075 strain0.05 strain0.35 Fit0.2 Fit0.15 Fit

0.1 Fit0.075 FitRecovery

Figure 149: Determination of Recrystallisation Start Times for C1Mn1 Steel

C1Mn1

0.01

0.1

1

10

0.01 0.1 1

Strain (-)

Tim

e (

s) 950

1050

1150

950 Fit

1050 Fit

1150 Fit

(a) C1Mn1

C1Mn1Nb1

0.01

0.1

1

10

0.01 0.1 1

Strain (-)

Tim

e (

s) 950

1050

1150

950 Fit

1050 Fit

1150 Fit

(b) C1Mn1Nb1

C1Mn1Nb3

0.01

0.1

1

10

0.01 0.1 1

Strain (-)

Tim

e (

s) 950

1050

1150

950 Fit

1050 Fit

1150 Fit

(c) C1Mn1Nb3

C2Mn1Nb3

0.01

0.1

1

10

0.01 0.1 1

Strain (-)

Tim

e (

s)

1050

1150

1050 Fit

1150 Fit

(d) C2Mn1Nb3

Figure 150: Recrystallisation Start Times, t0, as a function of Strain for each Temperature

145

The number of recrystallisation curves was less for the other steels and the variability greater, and so

they were evaluated as a simple multiple of the predicted times for the C1Mn1 steel, Figure 150(b-d).

Even so, the fit was quite good. The ratios and corresponding solute retardation parameters (assuming

that niobium was the dominant retarder) are given in Table 55.

Table 55: t0 Ratio of Steels Relative to C1Mn1 and corresponding

Solute Retardation Parameters with respect to Niobium

Steel Ratio (-) Nb (Wt%) SRP (-)

C1Mn1 1 0 -

C1Mn1Nb1 2.1 0.009 358

C1Mn1Nb3 3.6 0.028 199

C2Mn1Nb3 4.0 0.029 208

The t0 ratios and SRPs are plotted in Figure 151. Surprisingly, the t0 ratios vary linearly with niobium

content, and the SRP value varies with niobium content. The expectation was that the t0 ratios should

increase exponentially with niobium content, in which case the SRP values should be independent of

Nb.

0

1

2

3

4

5

0 0.01 0.02 0.03

Nb (Wt%)

Rela

tive T

ime (

-)

(a) t0 Ratio

0

100

200

300

400

0 0.01 0.02 0.03

Nb (Wt%)

SR

P (

%)

(b) SRP

Figure 151: Recrystallisation Start Time Ratio and Solute Retardation Parameter as a function of Nb

content

To investigate this further the t0 ratios were compared with the results of Yamamoto et al. [69] for the

effect of Nb on the start of recrystallisation at 900 °C, Figure 152.

y = e45.888x

R2 = 0.9781

y = e48.503x

R2 = 0.9175

1

10

100

0 0.02 0.04 0.06 0.08 0.1

Nb (Wt%)

Rela

tive R

ex S

tart

Tim

e (

-)

Yamamoto

This Work

Yamamoto Fit

This Work Fit

Figure 152: Comparing Relative Recrystallisation Start Times with the results from Yamamoto [69]

Yamamoto examined the effect of soluble Nb on recrystallisation using decarburised samples, allowing

far higher Nb additions to be investigated than in this study without precipitation. It is clear that the

two sets of results are consistent with each other both in terms of the trend and the variability of

146

individual results. The exponential relationship is therefore taken to be valid, and can be incorporated

into the t0 equation:

71.211

0 5.48194000

exp1087.8 −−

+×= εNbRT

t (53)

where Nb is in Wt%. Sellars [73] used the data from Yamamoto to obtain an equation for 5%

recrystallisation (not to be confused with 5% precipitation), taken to be the nominal start of

recrystallisation:

−

××= −− Nb

TRTDt 185

1075.2exp

300000exp1075.6

542

0

20

5 ε (54)

The form of the equation is very similar to equation (53), but with the addition of a dependence on the

initial austenite grain size.

It is not unreasonable to assume that Nb is delaying the start of recrystallisation through solute drag of

the dislocations. However, these results do not provide evidence that this is the mechanism. According

to Nes [54] if solute drag is the rate limiting mechanism during recovery, then the recovery should

depend on the strain of the preceding hit. However, it was found that recovery was independent of both

the Nb level and the strain, equations (49) and (50). These results are at variance with many workers,

including Yamamoto et al. [69], Jonas [48] and Maruyama et al. [74]. However, their observations that

Nb delays recovery (as well as recrystallisation) are based on double hit tests in which the stress is

removed between hits and the number of data points is limited, making it impossible to properly follow

the details of the initial rapid recovery.

If Nb is not affecting the driving force for recovery or recrystallisation, it must be affecting the kinetics

in some other way. The relationship for the recrystallised grain size, equation (59), indicates that the

grain size decreases with increasing Nb content, which means that Nb increases the number of

nucleation sites for recrystallised grains, but delays the time that they first become active. This is an

interesting possibility, because it may explain why the subsequent recrystallisation curves have the

same shape, because their kinetics remain essentially the same. To study this further would require

more work, for example using Fe-30%Ni model alloys, to allow the austenite microstructure to be

quenched out and studied in detail. Two possible mechanisms for the nucleation of recrystallised grains

are (i) sub-grain rotation and growth, and (ii) strain-induced boundary migration. Either mechanism

could be affected by the amount of soluble Nb.

2.3.5.3 Task 5.3: Modelling of dynamic recrystallisation kinetics

The peak stress value in dynamic recrystallisation is a function of strain rate and temperature.

Increasing the silicon content generates an increase of the stress of austenite due to solid solution effect

(Figure 153), as was also observed in [76].

Figure 153: Influence of strain rate and temperature on peak stress

147

The influence of temperature and strain rate on peak stress were analysed by the following equations

which were originally developed for creep but have found applicability in the high strain rates

encountered in hot working. Their effect can be expressed by the so called Zener-Hollomon (ZH)

parameter given in equation (55). The link between the ZH parameter and the peak stress can be

expressed according to power, exponential or hyperbolic sine law depending on the stress level to

estimate. The hyperbolic sine law is a more general law and is usually preferred to model peak stress.

(55)

From experimental data obtained in task 3.3 (Table 30), the peak stress was modelled using a “sinh”

law. Figure 154 and Figure 155 show examples of the regression analysis performed to determine the

coefficients of equation (55), which are given in Table 56 for each steel grade.

Figure 154: "n" exponent of ZH parameter Figure 155: “A” coefficient of ZH parameter

Table 56: Coefficients used to describe peak stress as a function of ZH parameter in Si steels

In StripCam, the saturation stress is expressed according to equation (56). Regression analyses were

performed from the data in Table 30 to determine the activation energy and strain rate exponent, Figure

156. The strain rate seems to affect the saturation stress slightly more than indicated by the equation.

(56)

Considering the results of steel grade C2Mn2Si2, C2Mn2Si2Nb3 and C2Mn2Si2Nb7, the niobium

effect on the activation energy was plotted in Figure 157. In contrast to equation (56), the experimental

results obtained in the MICROTOOLS project revealed that Nb generates an increase of the activation

energy. Furthermore, increasing the silicon content decreased the activation energy.

148

Figure 156: Activation energy and strain rate exponent of saturation stress for Si steels

Figure 157: Nb effect on activation energy of

saturation stress of Si steels

Figure 158: Strain rate exponent of critical strain

equation for Si steels

StripCam describes the influence of strain rate and temperature (i.e. ZH parameter) on critical strain

according to:

(57)

Experimental results were used to determine the strain rate exponent and activation energy for

comparison with the equation. Figure 158 shows the strain rate influence on critical strain. The results

were in agreement with the StripCam equation. They also showed that increasing Si content increased

the critical strain for DRX. The activation energy results were not satisfactory and additional torsion

trials should be performed at different temperatures to estimate the temperature effect on critical strain

since only three temperatures were used to perform the linear regression analysis.

2.3.5.4 Task 5.4: Modelling of austenite grain size

Effect of Nb

The statically recrystallised austenite grain size, drex is calculated as follows:

−= −−

RT

QADd rexrqp

rex expεε & (58)

where A, p, q, r and Qrex are constants, ε is the strain, ε& the strain rate, D the initial austenite grain size,

R is the gas constant and T the absolute temperature. The results from the matrix of uniaxial

compression tests carried out in Task 3.2 using 6 strains, 5 temperatures, 3 austenite grain sizes and 4

149

strain rates provided data from which new exponents for the terms in the equation have been derived.

Table 57 summarises the final coefficients derived for the drex equation.

Table 57: Summary of new coefficents for drex equation in Tata model

Parameter Original value all steels [41] MICROTOOLS value

A 45 8.16-98.62Nb (all)

6.84 – 82.68Nb (strain>=0.1)

p 0.375 0.1875

q 0.6 0.57 (all)

0.68 (strain>=0.1)

r 0.1 0.055

Qrex (J/mol) 25000 zero

A value for the strain exponent q was derived by keeping strain rate, grain size and temperature

constant, taking logarithms of both sides of the equation and plotting ln(drex) against ln(strain). Figure

159 shows the results for a temperatures of 1050°C at a strain rate of 1/s and initial austenite grain size

of 100µm. The values of q determined from the gradient of the plots varied quite widely, with an

average value of 0.57. The grain sizes for strains of 0.05 and 0.075 did not fit the same pattern of

behaviour as those at higher strains. Some of the tests at strains <0.1 did not lead to full

recrystallisation, therefore the grain sizes will correspond to recovered or partially recrystallised

microstructures and should be excluded from the analysis. Figure 159(b) shows that a more consistent

gradient was obtained in this case, with an average value of q = 0.68. Both values were in good

agreement with the value in the current Tata model of 0.6.

y = -0.588x + 2.3867

R2 = 0.879

y = -0.6125x + 2.7732

R2 = 0.8214

y = -0.2583x + 2.9527

R2 = 0.2935

y = -0.8144x + 2.0821

R2 = 0.956

0

1

2

3

4

5

-4 -3 -2 -1 0

ln(strain)

ln(D

rex)

C1Mn1

C1Mn1Nb1

C1Mn1Nb3

C2Mn1Nb3

1050°C

(a) 1050°C

y = -0.6206x + 2.3256

R2 = 0.7886

y = -0.6711x + 2.6805

R2 = 0.6581

y = -0.685x + 2.2978

R2 = 0.701

y = -0.7493x + 2.1821

R2 = 0.8698

0

1

2

3

4

5

-4 -3 -2 -1 0

ln(strain)

ln(D

rex)

C1Mn1

C1Mn1Nb1

C1Mn1Nb3

C2Mn1Nb3

1050°C

(b) 1050°C, strain <0.1 excluded

Figure 159: Logarithmic plot of drex against strain for strain rate of 1/s, ~100µm austenite grain size

A value for the strain rate exponent r was derived by keeping strain, initial grain size and temperature

constant and plotting ln(drex) against ln(strain rate). Figure 160 shows the results for a strain of 0.2

applied at 1050°C. An average value of r = 0.055 was obtained, indicating that there was only a small

effect of strain rate on recrystallised grain size.

A value for the grain size exponent p was derived by keeping strain rate, strain and temperature

constant and plotting ln(drex) against ln(initial grain size), Figure 161. The effect of initial grain size

was quite similar in all steels, with the exception of one large value from the largest initial grain size in

steel C1Mn1Nb3. If this point was included in the analysis, the average value of p = 0.258. If this point

was excluded then the effect of grain size was reduced, giving an average value of p = 0.146.

150

y = -0.0335x + 3.4528

R2 = 0.1548

y = -0.082x + 3.925

R2 = 0.6742

y = -0.0481x + 3.4486

R2 = 0.7696

y = -0.0569x + 3.6524

R2 = 0.6148

1.5

2.5

3.5

4.5

-3 -2 -1 0 1 2 3

ln(strain rate)

ln(D

rex)

C1Mn1

C1Mn1Nb1

C1Mn1Nb3

C2Mn1Nb3

1050°C

y = 0.2578x + 2.4805

R2 = 0.1445

2.5

3.0

3.5

4.0

4.5

5.0

5.5

3 3.5 4 4.5 5 5.5

ln(Initial austenite grain size) (µm)

ln(R

ecry

sta

llise

d a

uste

nite

gra

in s

ize

) (µ

m)

C1Mn1

C1Mn1Nb1

C1Mn1Nb3

C2Mn1Nb3

Figure 160: Logarithmic plot of drex against strain

rate for constant strain of 0.2, ~100µm austenite

grain size and temperature

Figure 161: Logarithmic plot of drex against initial grain

size for strain rate of 1/s, 0.2 strain and 1050°C

deformation temperature

To assess the accuracy of the relationship between the initial and recrystallised austenite grain size,

some additional grain size data from Gleeble tests at 1050°C applying 0.2 strain which were performed

previously within Tata on commercial plate steels of similar chemistry to those within project

MICROTOOLS were included in the analysis. Figure 162 shows that this data fits well with the current

results. A value of p = 0.1875 was derived from the combined set of data if the large grain size from

C1Mn1Nb3 was excluded.

y = 0.1459x + 2.845

R2 = 0.2211

y = 0.1875x + 2.6896

R2 = 0.2839

2.5

3.0

3.5

4.0

4.5

3 3.5 4 4.5 5 5.5 6

ln(Initial austenite grain size) (µm)

ln(R

ecry

sta

llise

d a

uste

nite

gra

in s

ize

) (µ

m)

MICROTOOLS

MICROTOOLS + Tata

Figure 162: Logarithmic plot of drex against initial grain size for strain rate of 1/s, 0.2 strain and 1050°C

deformation temperature including additional Tata data

A value for the activation energy Qrex can be determined from the gradient of a plot of ln(drex) against

inverse temperature, Figure 163. However, there was a large variation between the results for different

steels and strains, with both negative and positive effects of temperature on the grain size. Therefore it

was not possible to deduce a value for Qrex from this data. The existing value in the model is Qrex =

25000 J/mol. Other researchers have also found no temperature dependence and therefore do not

include a T term in their equations [27, 42, 43].

151

y = -554.31x + 3.6477

R2 = 0.0666

y = -8098.1x + 9.5818

R2 = 0.7831

y = 3587.6x + 0.6716

R2 = 0.2739

y = -3538.8x + 6.6047

R2 = 0.3149

2

3

4

5

0.00065 0.0007 0.00075 0.0008 0.00085

1/Temperature (1/K)

ln(D

rex)

(µm

)

C1Mn1

C1Mn1Nb1

C1Mn1Nb3

C2Mn1Nb3

0.35

(a) 0.35 strain

y = 94.143x + 3.2909

R2 = 0.0019

y = -4137.9x + 6.6809

R2 = 0.4638

y = 4704.3x + 0.2064

R2 = 0.4749

y = 1585x + 2.4339

R2 = 0.4451

2

3

4

5

0.00065 0.0007 0.00075 0.0008 0.00085

1/Temperature (1/K)

ln(D

rex)

(µm

)

C1Mn1

C1Mn1Nb1

C1Mn1Nb3

C2Mn1Nb3

0.2

(b) 0.2 strain

Figure 163: Logarithmic plot of drex against inverse temperature for constant strain, strain rate of 1/s,

~100µm austenite grain size

Finally, a value for the constant A can be determined from the intercept of the graphs. A relationship

with the Nb content of the steel was found. If the T term was excluded from the equation and the value

of q = 0.68, then A can be calculated as A = 6.84 – 82.68Nb. A slightly better fit to the overall grain

size data was found using q = 0.57, and the corresponding value of A = 8.16 – 98.62Nb.

Substituting the new coefficients shown in Table 57 back into equation (58) and re-calculating the

grain sizes led to a significant improvement in the predictions for all the tests (strain, strain rate,

temperature and initial grain size conditions), Figure 164(a). The outlying point on the right hand side

was from steel C1Mn1Nb3 with the large initial grain size. Additional points where the equation under-

predicted the grain size significantly were from 0.1 strain tests, where the measured grain size was

large compared with most of the other tests or it was not certain that recrystallisation had occurred

rather than recovery. The graph also includes the additional grain size data from previous Tata Gleeble

tests on commercial plate steels described above. These older results are consistent with the current

data and confirm that the modified coefficients produce more accurate predictions of drex for uniaxial

compression Gleeble tests. The relative error between the calculated and measured grain sizes has been

greatly reduced, especially for low strain deformations (Figure 164(b)).

The final equation to calculate the recrystallised austenite grain size that was determined in the project

was:

055.057.01875.0)62.9816.8( −−−= εε &DNbd rex (59)

Figure 165 shows how predictions of the old and new grain size equations vary with strain and

temperature compared with the measured data. The new equation predicts smaller grain sizes than the

original equation and a variation in grain size with Nb content which gives better overall agreement

with the measured data.

152

0

50

100

150

200

0 50 100 150 200

Measured recrystallised grain size (µm)

Calculated recrystallised grain size (µm)

original MICROTOOLS

new MICROTOOLS

original Tata

new Tata

(a) original and modified Tata drex equation

0

1

2

3

4

5

0.0 0.1 0.2 0.3 0.4

Strain (-)

Error in calculated/measured Drex (-)

original MICROTOOLS

new MICROTOOLS

(b) Relative error between calculated and measured

recrystallised austenite grain size

Figure 164: Comparison between measured and predicted statically recrystallised austenite grain size,

all data, using original and new equations.

0

20

40

60

80

100

120

140

160

180

0 0.1 0.2 0.3 0.4

Strain (-)

Recrystallised austenite grain size

(µm)

C1Mn1

C1Mn1Nb1

C1Mn1Nb3

C2Mn1Nb3

original model

new model CMn

new model Nb1

new model Nb3

1150°C

(a) 1150°C

0

20

40

60

80

100

120

140

160

180

0 0.1 0.2 0.3 0.4

Strain (-)

Recrystallised austenite grain size

(µm)

C1Mn1

C1Mn1Nb1

C1Mn1Nb3

C2Mn1Nb3

original model

new model CMn

new model Nb1

new model Nb3

1050°C

(b) 1050°C

0

20

40

60

80

100

120

140

160

180

0 0.1 0.2 0.3 0.4

Strain (-)

Recrystallised austenite grain size

(µm)

C1Mn1

C1Mn1Nb1

C1Mn1Nb3

C2Mn1Nb3

original model

new model Nb1

new model Nb3

new model CMn

950°C

(c) 950°C

Figure 165: Comparison between original and new Tata recrystallised austenite grain size equations

and experimental data

153

Effect of Al

Figure 166 shows the recrystallised grain sizes obtained for the different steels at the different

deformation conditions. As already mentioned, from the data no significant effect of temperature on the

recrystallised grain size is observed. However, decreasing the applied strain leads in all cases to an

increase in the austenite grain size. This behaviour is in good agreement with that reported by other

authors who only have found an effect of the initial grain size and strain, and not temperature [42,30].

(a) C2Mn2 steel

(b) C2Mn2Al1 steel

(c) C2Mn2Al2 steel

(d) C2Mn2AlNb steels

Figure 166: Recrystallised grain sizes obtained for the project steels.

Figure 167 shows the predictions of several models found in the bibliography for the statically

recrystallised grain size in C-Mn and microalloyed steels [42,30,75] plotted against the experimental

data obtained in the present work. As shown in the picture, the data corresponding to the Nb and Al

steels show trends similar to the other steels studied in the present work. Equations from references 42

and 75, which were fitted for C-Mn and Nb microalloyed steels, tend to predict austenite grain sizes

finer than the experimental ones, whereas the best fit is obtained with the equation from reference 30.

0

20

40

60

80

100

120

900 950 1000 1050 1100

T (ºC)

Dγ R

EX (µm)

C2Mn2Al1Nb3, def=0.35

C2Mn2Al2Nb3, def=0.35

C2Mn2Al2Nb7, def=0.35

0

20

40

60

80

100

120

900 950 1000 1050 1100

T (ºC)

Dγ R

EX (µm)

C2Mn2Al2 def=0.35

C2Mn2Al2 def=0.2

0

20

40

60

80

100

120

900 950 1000 1050 1100

T (ºC)

Dγ R

EX (µm)

C2Mn2Al1 def=0.35

C2Mn2Al1 def=0.2

0

20

40

60

80

100

120

900 950 1000 1050 1100

T (ºC)

Dγ R

EX (µm)

C2Mn2 def=0.35

C2Mn2 def=0.2

154

30

40

50

60

70

80

90

100

110

30 40 50 60 70 80 90 100 110

DSRX (experimental)

DSRX (calculated)

C2Mn2

C2Mn2Al1

C2Mn2Al2

C2Mn2Al2Nb3

C2Mn2Al2Nb7

C2Mn2Al1Nb3

(a) 167.0

0743.0−= εDDSRX [42], CMn steels

30

40

50

60

70

80

90

100

110

30 40 50 60 70 80 90 100 110

DSRX (experimental)

DSRX (calculated)

C2Mn2

C2Mn2Al1

C2Mn2Al2

C2Mn2Al2Nb3

C2Mn2Al2Nb7

C2Mn2Al1Nb3

(b) 67.067.0

01.1−= εDDSRX [75], Nb microalloyed steels

30

40

50

60

70

80

90

100

110

30 40 50 60 70 80 90 100 110

DSRX (experimental)

DSRX (calculated)

C2Mn2

C2Mn2Al1

C2Mn2Al2

C2Mn2Al2Nb3

C2Mn2Al2Nb7

C2Mn2Al1Nb3

(c) 156.0

04.1−= εDDSRX [30], Nb microalloyed steels

Figure 167: Predictions of equations found in the bibliography for calculating the statically

recrystallised grain size plotted against the experimental data obtained in this work.

Austenite grain growth after recrystallisation

The austenite grain size after grain growth, d, is calculated as follows:

+=

RT

Qtkdd

g

s

mm exp0 (60)

where ks and Qg are constants, t is the time for grain growth, d0 the initial (recrystallised) austenite

grain size and T the absolute temperature. The current Tata model uses coefficients from the work of

Hodgson and Gibbs, Table 58 [8], where m=7 for CMn steels and m=4.5 for Nb steels. However, these

values predict more grain growth in Nb steels than in CMn steels, which seems unrealistic. Previous

unpublished work within Tata showed that the coefficients for Nb steels predicted far too much grain

growth during long holding times at 1100 and 1000°C when very little growth was observed

experimentally, and although some growth was measured in CMn steels, it was less than predicted by

the equations. Figure 168 compares the predictions of the current equation for Nb steels with the results

from Task 3.4 for grain growth at 1150, 1050 and 950°C, starting from an initial recrystallised grain

size of 30µm. The lack of measured grain growth at 950°C and the small amount of growth at 1050°C

after 0.1 strain were reasonably well predicted. However, the amount of grain growth after 0.2 strain at

1050°C and especially 1150°C was significantly over-estimated.

155

Table 58: Summary of coefficents for grain growth equation (60) [8]

Parameter CMn steels Nb steels

m 7 4.5

ks 1.45 x 1027

4.1 x 1023

Qg (J/mol) -400000 -435000

0

40

80

120

160

200

240

0 2 4 6 8

ln(Hold time) (s)

Ave

rage a

uste

nite g

rain

siz

e (

µm

)

C1Mn1 1050 0.2

C1Mn1 1050 0.1

C1Mn1 1150 0.2

C1Mn1 950 0.2

original model 1150

original model 1050

original model 950

(a) C1Mn1

0

40

80

120

160

200

240

0 2 4 6 8

ln(Hold time) (s)

Avera

ge a

uste

nite g

rain

siz

e (

µm

)

C1Mn1Nb1 1050 0.2

C1Mn1Nb1 1050 0.1

C1Mn1Nb1 1150 0.2

C1Mn1Nb1 950 0.2

original model 1150

original model 1050

original model 950

(b) C1Mn1Nb1

0

40

80

120

160

200

240

0 2 4 6 8

ln(Hold time) (s)

Ave

rage a

uste

nite g

rain

siz

e (

µm

)

C1Mn1Nb3 1050 0.2

C1Mn1Nb3 1050 0.1

C1Mn1Nb3 1150 0.2

C1Mn1Nb3 950 0.2

original model 1150

original model 1050

original model 950

(c) C1Mn1Nb3

Figure 168: Measured and predicted austenite grain size after grain growth as a function of holding

time, temperature and strain

The grain growth behaviour can be analysed by taking logarithms of both sides of equation (60) and re-

arranging it to plot ln(dm-do

m) versus ln(t). This should give a straight line with gradient equal to 1 for

the most appropriate value of m. Graphs were plotted for all three steels, Figure 169, but it was not

possible to derive new values of m due to the scatter in the measured grain size data and the lack of

grain growth even in the C1Mn1 samples. Previous unpublished work within Tata indicated that a

value of m = 4.3 was optimal for CMn steels whereas m = 7.0 was more suitable for Nb steels (up to

0.037 wt% Nb). It was hoped to confirm these results with the current work but it has not been

possible. The limited results for steel C1Mn1Nb1 suggest that m = 4.3 may also be appropriate for 0.01

wt% Nb steels. Re-plotting Figure 168 with these new values of m gives an improved estimation of the

grain sizes after a hold time of up to 900s, Figure 170. This will reduce the calculated grain size at the

entry to the finishing mill in a TMCR rolling schedule compared with the original model.

156

y = -0.5876x + 19.417

R2 = 0.6403

y = 0.3522x + 14.79

R2 = 0.3491

y = -1.1486x + 24.351

R2 = 0.75

y = 16.1

R2 = 0

0

5

10

15

20

25

0 2 4 6 8

ln(Hold time) (s)

ln(d

^m

- d

0^m

)

C1Mn1 1050 0.2

C1Mn1 1050 0.1

C1Mn1 1150 0.2

C1Mn1 950 0.2

(a) C1Mn1

y = 1.0707x + 11.208

R2 = 1

y = 0.9597x + 14.582

R2 = 1

y = -1.6916x + 25.867

R2 = 1

0

5

10

15

20

25

0 1 2 3 4 5 6

ln(Hold time) (s)

ln(d

^m

- d

0^m

)

C1Mn1Nb1 1050 0.2

C1Mn1Nb1 1050 0.1

C1Mn1Nb1 1150 0.2

C1Mn1Nb1 950 0.2

(b) C1Mn1Nb1

Figure 169: Analysis of austenite grain growth data as a function of holding time, m = 4.5

0

40

80

120

160

200

240

0 2 4 6 8

ln(Hold time) (s)

Ave

rage a

uste

nite g

rain

siz

e (

µm

)

C1Mn1 1050 0.2

C1Mn1 1050 0.1

C1Mn1 1150 0.2

C1Mn1 950 0.2

new model 1150

new model 1050

new model 950

(a) C1Mn1, m = 4.3

0

40

80

120

160

200

240

0 2 4 6 8

ln(Hold time) (s)

Avera

ge a

uste

nite g

rain

siz

e (

µm

)C1Mn1Nb1 1050 0.2

C1Mn1Nb1 1050 0.1

C1Mn1Nb1 1150 0.2

C1Mn1Nb1 950 0.2

new model 1150

new model 1050

new model 950

(b) C1Mn1Nb1, m = 4.3

0

40

80

120

160

200

240

0 2 4 6 8

ln(Hold time) (s)

Ave

rage a

uste

nite g

rain

siz

e (

µm

)

C1Mn1Nb3 1050 0.2C1Mn1Nb3 1050 0.1C1Mn1Nb3 1150 0.2C1Mn1Nb3 950 0.2new model 1150new model 1050new model 950

(c) C1Mn1Nb3, m = 7.0

Figure 170: Measured and predicted austenite grain size after grain growth as a function of holding

time, temperature and strain using new values of m.

157

2.3.5.5 Task 5.5: Modelling of recrystallisation-precipitation interactions

Effect of Nb

The multipass torsion tests performed in Task 3.6 to investigate the Tnr, RLT and RST as a function of

steel chemistry, strain and interpass time have been modelled using the new Tata recrystallisation and

grain growth equations derived in Tasks 5.2 and 5.4. Figure 171 compares the predictions of the

fraction softened determined from the measured flow stress curves (

) and the recrystallised fraction predicted by the new Tata model for steels C1Mn1Nb3 and C2Mn1Nb3

at strains of 0.3 and 0.1 and interpass times of 10 and 30s. The model showed the correct trends with

strain and interpass time at 0.3 strain but the predicted RLT was lower than the measured value

indicating that recrystallisation was occurring too quickly or pinning was occurring at too low a

temperature in the model. It should be noted that the model is only predicting softening due to

recrystallisation and does not include recovery effects which may be contributing to the overall

softening. The round robin tests in Task 3.2 also showed that the recrystallisation kinetics determined

from the torsion tests were slower than those determined from Gleeble uniaxial compression tests. The

Tata model was calibrated using Gleeble tests and therefore would be expected to predict faster

recrystallisation, and thus a greater fraction recrystallised, than the torsion tests under the same

conditions.

The torsion tests indicated that incomplete softening occurred at all temperatures when 0.1 strain was

applied per pass. The model also predicted partial recrystallisation but the fraction recrystallised

decreased steadily with decreasing temperature. The predictions of the model for 0.05 strain are also

shown in the graphs and it can be seen that partial recrystallisation similar to the behaviour observed in

the torsion tests was predicted. This suggests that either the strain exponent in the t50 equation should

be larger, to increase the time required to complete recrystallisation at lower strains, or the critical

strain for initiating recrystallisation should be increased in the model, to obtain better agreement with

the torsion results. Figure 171(e) shows that increasing the strain exponent p from 1.38 (Tata value) to

2.8 (CEIT value for an initial austenite grain size of 100µm) gives a much better prediction of the

softened fraction for the torsion data on steel C1Mn1Nb3. This therefore provides a method of relating

the Tata model to the torsion data, using the grain size dependent strain exponent p = 5.6D-0.15

from the

CEIT model.

The effect of C in the model on the recrystallisation behaviour was much stronger than was indicated

by the torsion tests. No effect of carbon is included in the equation for time for 50% recrystallisation

(t50) but there is an effect on the time for 5% precipitation (t5%p) via the solubility product term for

Nb(C,N) precipitation (Table 46). These two equations interact in the model and if t5%p is less than

the time for 95% recrystallisation then recrystallisation is stopped by precipitation pinning. This leads

to the plateau in predicted fraction recrystallised at lower temperatures.

158

0

20

40

60

80

100

120

800900100011001200

T (ºC)

FS (

%)

C1Mn1Nb3 def=0.3 tip=30s

C1Mn1Nb3 def=0.3 tip=10s

C1Mn1Nb3 def=0.1 tip=30s

Tnr=1025ºC

RLT=1063ºC

RST=932ºC

RLT=1105ºC

RST=946ºC

Tnr=1042ºC

(a) C1Mn1Nb3 measured

0

0.2

0.4

0.6

0.8

1

1.2

800900100011001200

Temperature (°C)

Fra

ctio

n r

ecry

sta

llise

d

0.3 strain, 10s

0.3 strain, 30s

0.1 strain, 30s

0.05 strain, 30s

RLT = 980°C RLT = 1060°C

RST = 920°C

RST = 940°C

C1Mn1Nb3

(b) C1Mn1Nb3 predicted, new model

0

20

40

60

80

100

120

800900100011001200

T (ºC)

FS

(%

)

C2Mn1Nb3 def=0.3 tip=30s

C2Mn1Nb3 def=0.3 tip=10s

C2Mn1Nb3 def=0.1 tip=30s

Tnr=1035ºC

Tnr=1048ºCRLT=1113ºC

RST=953ºC

RLT=1063ºC

RST=958ºC

(c) C2Mn1Nb3 measured

0

0.2

0.4

0.6

0.8

1

1.2

800900100011001200

Temperature (°C)

Fra

ctio

n r

ecry

sta

llise

d

0.3 strain, 10s

0.3 strain, 30s

0.1 strain, 30s

0.05 strain, 30s

RLT = 1040°C

RLT = 1060°C

RST = 1000°C

RST = 1020°C

C2Mn1Nb3

(d) C2Mn1Nb3 predicted, new model

0

0.2

0.4

0.6

0.8

1

1.2

800900100011001200

Temperature (°C)

Fra

ctio

n r

ecry

sta

llise

d

0.3 strain, 10s, p=2.8

0.3 strain, 30s, p=2.8

0.1 strain, 30s, p=2.8

RLT = 1080°C RLT = 1160°C

RST = 920°C

RST = 940°C

C1Mn1Nb3

(e) C1Mn1Nb3 predicted, new model, p =2.8

Figure 171: Measured and predicted fractional softening for multipass torsion tests using Tata model

Effect of Al

The microstructural characterisation work carried out with the 2%Al-Nb steels showed that as well as

strain-induced precipitation γ�α phase transformation occurred after deformation. As a result, it was

not possible to relate the softening behaviour with the start or the progression of Nb(C,N) precipitation.

Therefore, in this analysis only the data corresponding to the C2Mn1Nb3 and C2Mn2Al1Nb3 steels

will be considered.

159

The softening curves obtained for the two steels at the temperatures at which strain-induced

precipitation occurred (900 and 925ºC), together with the precipitate size measured in each case are

displayed in Figure 172. It can be observed that in both cases the softening kinetics is slightly retarded

for the C2Mn1Nb3, whereas approximately similar precipitate sizes have been measured for the two

steels. Unfortunately, the amount of Nb precipitated was only measured in C2Mn2Al1Nb3 specimens,

so this could not be directly compared. However, the replica analysis carried out in Task 4.3 showed

that at the first precipitation stages a significantly larger amount of precipitates were found in the

C2Mn1Nb3 replicas. These observations suggest that strain-induced precipitation kinetics were

retarded for the C2Mn2Al1Nb3. The reasons for this apparent delay steel could be various; on the one

hand, it could be attributed to the larger Mn content for this steel (2%) compared to the C2Mn1Nb3

steel (1%). The potential of Mn for retarding strain-induced precipitation due to a reduction in the

carbon activity coefficient has also been reported by other authors [77,78]. On the other hand, Al could

lead to a similar effect. Finally, it must be remembered that in the case of the C2Mn2Al1Nb3 steel, all

the N is pinned in form of AlN precipitates, therefore only NbC strain-induced precipitation is expected

to take place in this steel, which is expected to be delayed compared to Nb(C,N) precipitation.

0

0.2

0.4

0.6

0.8

1

0.1 1 10 100 1000 10000t (s)

Fractional Softening

C2Mn1Nb3 900ºC

C2Mn2Al1Nb3 900ºC

D=7 nm

D=14 nm

D=19 nm

D=8 nmD=16 nm

t(s)

(a) 900°C

0

0.2

0.4

0.6

0.8

1

0.1 1 10 100 1000 10000t (s)

Fractional Softening

C2Mn1Nb3 T=925ºC

C2Mn2Al1Nb3 T=925ºC

D=13 nm

D=13 nm

D=28 nm

D=20 nm

D=9 nm

D=20 nm

t(s)

(b) 925°C

Figure 172: Measured softening curves and precipitate sizes for C2Mn1Nb3 and C2Mn2Al1Nb3 steels.

The amount of Nb precipitated measured by electrolytic dissolution and ICP for the C2Mn2Al1Nb3

steel at the two temperatures investigated has been plotted in Figure 173(a). It can be observed that the

precipitation evolution is similar for the two steels although it is slightly retarded for the highest

temperature, 925ºC. The data obtained could be well fitted to two Avrami curves. The n exponent

obtained, n∼0.65 is in good agreement with the values found in the bibliography for other microalloyed

steels, n∼0.6 [27,79]. In Figure 173(b) the precipitate fraction evolution obtained for the two steels has

been plotted normalised by the equilibrium precipitate volume fraction for each temperature. In order

to obtain the precipitate fraction, a NbC precipitate stoichiometry and the solubility product obtained

by Palmiere et al. [31] were employed.

Usually, the time for strain-induced precipitation onset (t0.05p) is defined as the time for 5% precipitate

equilibrium fraction. According to this, the chemical dissolution technique would yield t0.05p values of

19 s for T=900ºC and 23 s for T=925ºC for the C2Mn2Al1Nb3. On the other hand, several authors had

also calculated the time for strain-induced precipitation onset as the time for the plateau onset in the

softening curves. In previous works it was observed that the time for strain-induced precipitation

obtained by chemical dissolution technique was shorter than that obtained from the plateau detection

[27]. Figure 174 shows the precipitation start times determined for the C2Mn2Al1Nb3 by chemical

extraction, and the approximated range times for the plateau onset obtained from the softening curves

for the C2Mn2Al1Nb3. In addition, the results predicted by the CEIT model for strain-precipitation

onset if chemical dissolution is employed as the precipitation detection technique (circles) or if

mechanical testing is employed as the detection technique (triangles) have been included. The figure

shows that for the C2Mn2Al1Nb3 steel the experimental data obtained by chemical analysis or plateau

detection conditions are significantly retarded compared to the predictions of the model. This agrees

well with the findings shown above. The reasons for the retarded precipitation kinetics for the

160

C2Mn2Al1Nb3 steel have already been discussed. Finally, the data shows clearly that there is a

significant difference between the times for strain-induced precipitation times determined using the two

methods; the time onset determined by plateau detection is retarded by a factor of approximately ∼10.

This shift is in good agreement with the model predictions.

0

0.005

0.01

0.015

0.02

0.025

1 10 100 1000 10000

Time (s)

Nb precipitated (%)

925ºC900ºC

(a)

0

0.2

0.4

0.6

0.8

1

1 10 100 1000 10000Time (s)

f v

925ºC900ºC

(b)

Figure 173: (a) Nb precipitated (%) measured for the C2Mn2Al1Nb3 by electrolytic dissolution and

ICP and (b) precipitate volume fraction evolution normalised by the equilibrium precipitate volume

fraction.

850

900

950

1000

1050

1100

1150

1200

1 10 100 1000 10000

Time (s)

Temperature (ºC)

C2Al1Nb3 T0.05p, plateau

C2Al1Nb3 T0.05p, chemicalextraction

CEIT MODEL

PREDICTIONS FOR

t0.05p detected by

chemical analysis

CEIT MODEL PREDICTIONS

FOR t0.05p detected by

mechanical testing (plateau)

Figure 174: Strain-induced precipitation start times determined experimentally by chemical extraction

and estimated from the softening curves plateaux and CEIT model predictions for both conditions.

161

2.3.5.6 Task 5.6: Construction of processing regime maps

Effect of Nb

From the multipass torsion tests carried out in Task 3.6 on steels C1Mn1Nb3 and C2Mn1Nb3, the

recrystallisation critical temperatures RLT, RST and Tnr were determined,

. These have been plotted against interpass time for a strain per pass of 0.3 in Figure 175, from which

different microstructural evolution regimes can be identified as a function of temperature. At

temperatures above the RLT, complete recrystallisation occurred in the steels. Between the RLT and

RST is the partial recrystallisation regime, whilst between RST and Ar3 there is no recrystallisation and

strain accumulation occurs in the austenite. Finally, below the Ar3 temperature phase transformation

occurs. The RLT, RST and Tnr temperatures were slightly higher in the C2Mn1Nb3 steel due to the

higher carbon content, whereas the Ar3 temperature was much lower. This led to a much wider

temperature range where strain accumulation can occur in the higher carbon steel.

700

800

900

1000

1100

1200

10 30 50

Interpass time (s)

Temperature (°C)

RLT

Tnr

RST

Ar3Strain Accumulation (No Rex)

Strain Accumulation (Partial Rex)

Complete Recrystallisation

Phase Transformation

C1Mn1Nb3

0.3 strain

(a) C1Mn1Nb3

700

800

900

1000

1100

1200

10 30 50

Interpass time (s)

Temperature (°C)

RLT

Tnr

RST

Ar3Strain Accumulation (No Rex)

Strain Accumulation (Partial Rex)

Complete Recrystallisation

Phase Transformation

C2Mn1Nb3

0.3 strain

(b) C2Mn1Nb3

Figure 175: Processing regime maps derived from multipass torsion tests on C1Mn1Nb3 and

C2Mn1Nb3 steels.

Figure 176 plots the equivalent processing regime maps based on the predictions of the Tata model

from Task 5.5, including additional interpass times up to 50s. Maps were also calculated for 0.1 strain

for comparison with the higher strain, although torsion testing was only carried out at an interpass time

of 30s at this strain and so the equivalent experimental map cannot be constructed. The calculated maps

show a much wider range of temperatures at which complete recrystallisation occurs and a narrower

range for partial recrystallisation compared with the torsion maps for 0.3 strain. At an interpass time of

50s there was no partial recrystallisation regime predicted, with a rapid transition from complete to no

recrystallisation due to precipitation. The higher critical temperatures for recrystallisation and wider

temperature regime for no recrystallisation and strain accumulation in C2Mn1Nb3 were replicated by

the model. At 0.1 strain, the model predicted much higher RLT values at each interpass time but similar

RST values to 0.3 strain, so the range of temperatures over which partial recrystallisation was predicted

to occur was much wider. The torsion tests at 0.1 strain and 30s interpass time indicated that partial

recrystallisation occurred at all temperatures from the first pass at 1180°C down to at least 1000°C.

Substituting the value of the strain exponent p in the t50 equation with the term from the CEIT equation

(equation (28)), as in Task 5.5, raised the predicted RLT temperatures significantly at 0.3 strain thus

widening the partial recrystallisation regime (Figure 176(e)-(f)). At 0.1 strain, partial recrystallisation

was predicted from 1180°C downwards for all interpass times up to 50s.

162

700

800

900

1000

1100

1200

10 30 50

Interpass time (s)

Temperature (°C)

RLT

Tnr

RST

Ar3

Strain Accumulation (No Rex)

Strain Accumulation (Partial Rex)

Complete Recrystallisation

Phase Transformation

C1Mn1Nb3

0.3 strain

(a) C1Mn1Nb3, 0.3 strain

700

800

900

1000

1100

1200

10 30 50

Interpass time (s)

Temperature (°C)

RLT

Tnr

RST

Ar3Strain Accumulation (No Rex)

Strain Accumulation (Partial Rex)

Complete Recrystallisation

Phase Transformation

C2Mn1Nb3

0.3 strain

(b) C2Mn1Nb3, 0.3 strain

700

800

900

1000

1100

1200

10 30 50

Interpass time (s)

Temperature (°C)

RLT

Tnr

RST

Ar3

Strain Accumulation (No Rex)

Strain Accumulation (Partial Rex)

Complete Recrystallisation

Phase Transformation

C1Mn1Nb3

0.1 strain

(c) C1Mn1Nb3, 0.1 strain

700

800

900

1000

1100

1200

10 30 50

Interpass time (s)

Temperature (°C)

RLT

Tnr

RST

Ar3

Strain Accumulation (No Rex)

Strain Accumulation (Partial Rex)

Complete Recrystallisation

Phase Transformation

C2Mn1Nb3

0.1 strain

(d) C2Mn1Nb3, 0.1 strain

700

800

900

1000

1100

1200

10 30 50

Interpass time (s)

Temperature (°C)

RLT

Tnr

RST

Ar3

Strain Accumulation (No Rex)

Strain Accumulation (Partial Rex)

Complete Recrystallisation

Phase Transformation

C1Mn1Nb3

0.3 strain

(e) C1Mn1Nb3, 0.3 strain, p=2.8

700

800

900

1000

1100

1200

10 30 50

Interpass time (s)

Temperature (°C)

RLT

Tnr

RST

Ar3Strain Accumulation (No Rex)

Strain Accumulation (Partial Rex)

Complete Recrystallisation

Phase Transformation

C2Mn1Nb3

0.3 strain

(f) C2Mn1Nb3, 0.3 strain, p=2.8

Figure 176: Processing regime maps calculated using Tata model, corresponding to multipass torsion

tests

Effect of Si

The critical recrystallisation temperatures from Table 35 were used to construct a first set of processing

maps for the Si steels. These maps highlight interactions between recrystallisation and retardation

mechanisms (solute drag, precipitation) under different processing conditions. The different

recrystallisation regimes for a strain per pass of 0.3 are given in Figure 177 and Figure 178. Regions

where complete, partially complete or no recrystallisation takes place are considered. The results

revealed that no major effect of interpass time on recrystallisation temperatures was observed.

Increasing the niobium level increased recrystallisation temperatures (RLT, RST and Tnr). However, as

163

already highlighted in Task 3.2, increasing the silicon content from 1% to 2% did not clearly affect

recrystallisation regimes.

Figure 177: Processing regime maps – Si steel grades without niobium

Figure 178: Processing regime maps – Si steel grades with niobium

Effect of Al

From the multipass torsion tests carried out on the Al steels, the recrystallisation critical temperatures

RLT, RST and Tnr were determined. These have been plotted for all the steels analysed against the

interpass time in Figure 179. From these plots, the microstructural evolution regimes can be identified

as a function of processing temperature: at temperatures above the RLT the steels recrystallise

completely, between the RLT and the RST partial recrystallisation occurs and strain accumulation

processes start, and below the RST recrystallisation is prevented and all the applied strain is retained.

Although as aforementioned γ�α phase transformation may start at temperatures significantly higher

than those determined mechanically, the Ar3 determined from the multipass torsion tests has also been

included in the plots.

164

5 30 55 80

Interpass time (s)

STRAIN ACCUMULATION

(Partial Rex.)

COMPLETE

RECRYSTALLISATION

C2Mn2Al1

5 30 55 80

Interpass time (s)

C2Mn2Al1Nb3 COMPLETE

RECRYSTALLISATION

STRAIN ACCUMULATION

(No Rex.)

STRAIN ACCUMULATION

(Partial Rex.)

C2Mn2Al2 RLTC2Mn2Al2 TnrC2Mn2Al2 RSTC2Mn2Al2 Ar3

C2Mn2Al2 RLTC2Mn2Al2 TnrC2Mn2Al2 RSTC2Mn2Al2 Ar3

C2Mn2Al2 RLTC2Mn2Al2 TnrC2Mn2Al2 RSTC2Mn2Al2 Ar3

C2Mn2Al2 RLTC2Mn2Al2 TnrC2Mn2Al2 RSTC2Mn2Al2 Ar3

C2Mn2Al2 RLTC2Mn2Al2 TnrC2Mn2Al2 RSTC2Mn2Al2 Ar3

C2Mn2Al2 RLTC2Mn2Al2 TnrC2Mn2Al2 RSTC2Mn2Al2 Ar3

C2Mn2Al2 RLTC2Mn2Al2 TnrC2Mn2Al2 RSTC2Mn2Al2 Ar3

C2Mn2Al2 RLTC2Mn2Al2 TnrC2Mn2Al2 RSTC2Mn2Al2 Ar3

800

900

1000

1100

1200

5 30 55 80

Interpass time (s)

T (ºC)

STRAIN ACCUMULATION

(Partial Rex.)

COMPLETE

RECRYSTALLISATION

C2Mn2 1200

800

900

1000

1100

1200

5 30 55 80

Interpass time (s)

T (ºC)

C2Mn2Al2

STRAIN ACCUMULATION

(Partial Rex.)

COMPLETE

RECRYSTALLISATION

γ→α γ→α γ→α γ→α PHASE

TRANSFORMATION

5 30 55 80

Interpass time (s)

C2Mn2Al2Nb3

STRAIN ACCUMULATION

(Partial Rex.)

RECRYSTALLISATION

γ→α γ→α γ→α γ→α PHASE

TRANSFORMATION

STRAIN ACCUMULATION(No Rex.)

5 30 55 80

Interpass time (s)

STRAIN ACCUMULATION (No Rex.)

C2Mn2Al2Nb7 RECRYSTALLISATION

γ→α γ→α γ→α γ→α PHASE

TRANSFORMATION

STRAIN ACCUMULATION

(Partial Rex.)

Figure 179: Plots representing the different recrystallisation, strain accumulation and γ�α phase

transformation regimes for the Al steels as a function of interpass time.

Comparison of the data corresponding to the C2Mn2 and C2Mn2Al1 steels shows that the solute drag

effect due to 1%Al addition has a small but noticeable effect in increasing the potential for strain

accumulation in the investigated steels, this effect being enhanced for the shortest interpass times. The

potential for strain accumulation is clearly increased with 0.03%Nb addition to the C2Mn2Al1 steel. It

can also be observed that in this case below 950ºC recrystallisation was completely prevented for all

the interpass times studied leading to a wide temperature processing window for strain accumulation.

In addition, for tip=30 s the amount of NbC precipitation found close to the Tnr was small, denoting that

as well a providing strain accumulation, Nb may be left in solution after hot rolling available for further

precipitation after deformation. Finally, the figures denote that the temperatures for strain accumulation

onset are also very high for the 2%Al steels. In this case, it seems that γ�α phase transformation

starting at temperatures close to the Tnr significantly contributes to this behaviour. However, it must be

taken into account that as a result of γ�α phase transformation a significant loss of ductility during the

multipass deformation schedules was observed, and more than half of the investigated specimens broke

during the tests. This indicates that for hot rolling purposes, lower Al levels would be more convenient.

Plate and strip rolling processing maps

In order to study the effect of alloying additions on the microstructural evolution of the austenite under

hot rolling conditions, the CEIT model [27] was selected from all the project models to generate plate

and strip rolling processing maps. For plate rolling, schedules proposed by Tata for final gauges from

50 to 25 mm and End Hold Temperatures (EHT) from 850 to 1000ºC were simulated, and the following

steel compositions were considered: 0.1%C-1%Mn-0.03%Nb (C1Mn1Nb3), 0.2%C-2%Mn-1%Al

(C2Mn2Al1) and 0.2%C-2%Mn-1%Al-0.03%Nb (C2Mn2Al1Nb3).

In the model [27], the effect of Al addition on the static softening kinetics was taken into account by

incorporating the solute retardation parameter obtained from the double hit torsion tests (equation

(29)). For calculating the recrystallised grain size, the equation taken from reference 30, which showed

a reasonable fit for the project steels (see Figure 167), was employed. Finally, it must be remembered

165

that the results suggested that Al retards the strain-induced precipitation kinetics. However, due to the

limited data available, this effect was not quantified and, therefore, it was not taken into account in the

calculations.

The model results obtained in the plate simulations have been represented in Figure 180 in the form of

different processing maps. These display the final austenite grain sizes obtained after hot rolling

(Figure 180(a-c)) and the amount of strain accumulated after the last pass (Figure 180(d-f)) for the

different EHT and gauge combinations. For the three steel compositions considered, the modelling

results indicate that the final austenite grain size tends to decrease with increasing the End Holding

Temperature. This seems to be related with the configuration of the hot rolling schedules. In the hot

deformation sequences provided by Tata, for the same final gauge the number of rolling passes applied

decreases with increasing the End Holding Temperature. As a result, higher deformation values are

applied in the rolling passes, and according to the model this results in finer recrystallised austenite

grain sizes. In addition, finer recrystallised grain sizes tend to be obtained for the thicker final gauges.

The effect is enhanced for the lower EHT values. Again, this seems to be related to the configuration of

the rolling schedules. In the plate hot rolling schedules designed by Tata, although a smaller total strain

is applied for obtaining a thicker gauge length, this is given in less rolling passes.

The maps also show that, similar microstructures are predicted at low End Holding Temperatures for

the three steel compositions considered. However, at EHT higher than 900ºC, the finest final austenite

grain sizes are obtained for the C2Mn2Al1Nb3, while the Al1 steel tends to result in the coarsest

microstructures. This is related to the strain accumulation potential of the three steels. In the case of the

Al1 steel, the static softening kinetics is retarded due to 1%Al solute drag effect, which is equivalent to

the retardation exerted by 0.027%Nb in solid solution; however in the case of the C1Mn1Nb3 strain-

induced precipitation also takes place resulting in higher strain accumulation levels. As a result, refined

recrystallised grain sizes are obtained. For the C2Mn2Al1Nb3 steel, the two effects are added. This is

also clearly reflected in the maps displaying the accumulated strain (Figure 180(d-f)).

For strip rolling, a series of 16 rolling schedules supplied by ArcelorMittal were considered, based on a

representative industrial schedule of thin gauge hot rolling of advanced high strength steels (AHSS),

Table 59. According to industrial needs the process parameters for the construction of the maps were

selected as Finish Rolling Temperature (FRT) between 850 and 950°C and gauge thickness of the final

hot rolled product between 2 and 6mm.

The following criteria were proposed for constructing the processing regimes:

� Constant roughing conditions

� Constant Entry Temperature to Finishing Mill: 1045°C

� Fixed Entry Thickness to Finishing Mill: 38mm

� Deformation Temperature evolution during Finishing Rolling: Deformation Temperature

in each pass derived from the share of the total temperature drop between each pass

derived from the reference industrial schedule

� Applied Strain evolution during Finishing Rolling: a) Deformation in F7 is constant as

used mainly for strip shape control, b) strain per pass derived from the share of total strain

in each stand derived from the reference industrial schedule.

� Interstand Cooling rate during Finishing Rolling: Constant cooling rate, derived from the

reference industrial schedule: F1-F2: 10°C/s # F2-F3:4°C/s # F3-F4:14°C/s # F4-

F5:20°C/s # F5-F6: 27°C/s # F6-F7: 50°C/s

� Interpass Times during Finishing Rolling: Derived from deformation temperature

evolution and cooling rates described above

The maps were calculated for the following steel compositions: 0.1%C-1%Mn-0.03%Nb (C1Mn1Nb3),

0.1%C-1%Mn-0.07%Nb (C1Mn1Nb7) and 0.2%C-2%Mn-1%Al-0.03%Nb (C2Mn2Al1Nb3). The final

austenite grain size and the accumulated strain maps are displayed in Figure 181. For the three

166

compositions considered, as the final gauge decreases finer grain sizes and higher accumulated strain

levels are obtained. In this case, the number of deformation passes was constant for all the schedules

simulated. Therefore this grain size refinement and higher strain accumulations levels can be directly

related to the larger strain applied in order to obtain thinner final gauges. In addition, the maps show

that the grain size decreases slightly with decreasing FRT, while the accumulated strain tends to

increase slightly. At lower temperatures, lower interpass softening levels are obtained, and as a result

the amount of strain accumulated tends to be higher. This leads to refined austenite microstructures.

Final grain size (µµµµm) Accumulated strain after last pass

40 50

50

5050

50

6060

60

7070

70

80

80

80

90

90

100

100

110

120130140

30 35 40 45 50850

900

950

1000

Gauge (mm)

En

dH

old

ing

Te

mp

era

ture

(ºC

)

(a) C1Mn1Nb3, Grain Size (µm)

0.07

0.08

0.080.09

0.09

0.09

0.1

0.1

0.10.1

0.11

0.11

0.11

0.11 0.12

30 35 40 45 50850

900

950

1000

Gauge (mm)E

nd

Ho

ldin

g T

em

pe

ratu

re(º

C)

(d) C1Mn1Nb3, Accumulated Strain

50 60

60

6060

60

7070

70

80

80

80

90

90

100

100110120130140

30 35 40 45 50850

900

950

1000

Gauge (mm)

(b) C2Mn2Al1, Grain Size (µm)

0.07

0.08

0.08

0.09

0.09

0.090.09

0.1

0.1

0.10.1

0.1

30 35 40 45 50850

900

950

1000

Gauge (mm)

(e) C2Mn2Al1, Accumulated Strain

40

40

4040

5050

50

6060

60

7070

70

80

8080

90

90

100

100110120130140

30 35 40 45 50850

900

950

1000

Gauge (mm)

(c) C2Mn2Al1Nb3, Grain Size (µm)

0.070.08

0.08

0.0

9

0.09

0.090.09 0.1

0.10.1

0.11

0.11

0.11

0.11

0.120.12

0.12

0.12

0.13

0.13

30 35 40 45 50850

900

950

1000

Gauge (mm)

(f) C2Mn2Al1Nb3, Accumulated Strain

Figure 180: Grain size and strain accumulated after the lass past processing maps obtained employing

the CEIT model for the plate hot rolling simulations.

167

Finally, from the comparison of Figure 181 (a) and (b) it is evident that finer microstructures are

obtained for the C1Mn1Nb7 than for the C1Mn1Nb3 steel. This is a result of the higher potential for

strain accumulation due to enhanced solute drag effect and strain-induced precipitation for the

0.07%Nb steel. This is also reflected in the accumulated strain maps (Figure 181(d-f)). However, it is

interesting to note that the results obtained for the C2Mn2Al1Nb3 and C1Mn1Nb7 steels are very

similar. The results obtained in the simulation suggest that Al additions can also be helpful to obtain

adequately conditioned austenite grain microstructures during hot rolling.

Final grain size (µµµµm) Accumulated strain after last pass

55

6

66

7

77

8

88

9

99

10

10

10

11

11

11

12

12

12

13

13

13

14

14

14

15

2 3 4 5 6800

820

840

860

880

900

Gauge (mm)

En

dR

oll

ing

Te

mp

era

ture

(ºC

)

(a) Grain Size, C1Mn1Nb3 (µm)

0.25 0.25

0.250.3

0.3

0.3

0.3

0.3

5

0.35

0.35

0.4

0.4

0.45

2 3 4 5 6800

820

840

860

880

900

Gauge (mm)E

nd

Ro

llin

gT

em

pe

ratu

re(º

C)

(d) Accumulated strain, C1Mn1Nb3

44

55

5

66

67

77

88

89

99

10

10

10

11

11

11

12

12

12

13

13

13

2 3 4 5 6800

820

840

860

880

900

Gauge (mm)

(b) Grain Size, C1Mn1Nb7 (µm)

0.3

0.3

0.3

0.3

5

0.3

5

0.35

0.35

0.4

0.4

0.4

0.4

5

0.450.5

2 3 4 5 6800

820

840

860

880

900

Gauge (mm)

(e) Accumulated strain, C1Mn1Nb7

44

55

56

66

7

77

88

89

99

10

10

10

11

11

11

12

12

12

13

13

13

2 3 4 5 6800

820

840

860

880

900

Gauge (mm)

(c) Grain Size, C2Mn2Al1Nb3 (µm)

0.3

0.3

0.3

0.35

0.35

0.3

50.3

5

0.4

0.4

0.4

0.4

5

0.45

0.5

2 3 4 5 6800

820

840

860

880

900

Gauge (mm)

(f) Accumulated strain, C2Mn2Al1Nb3

Figure 181: Final austenite grain size, accumulated strain and recrystallised fraction processing maps

obtained employing the CEIT model for strip hot rolling simulations.

168

Table 59: Reference Industrial Hot Rolling Schedule for Processing Regime Maps in Strip Rolling

Entry Temperature

(°C)

Thickness

(mm)

Interpass Time

(s)

Strain per

pass

Cooling Rate

(°C/s)

Strain Rate

(1/s)

1258 (reh) 220

R1 1240 200 19,4 0,11 1

R2 1220 150 19,4 0,33 2

R3 1210 120 19,4 0,26 2

R4 1180 90 21,0 0,33 4

R5 1150 60 14,0 0,47 9

R6 1125 38,6 15,8 0,51 17

F1 1045 19,1 4,3 0,81 10 12

F2 1004 9,87 2,2 0,76 4 31

F3 995 6,13 1,4 0,55 14 56

F4 976 4,06 0,9 0,48 20 96

F5 958 2,98 0,7 0,36 27 142

F6 940 2,39 0,5 0,25 49 168

F7 914 2,06 0,5 0,17 172

2.3.6 WP6: Application and validation

The objectives of this work package were:

• Validation of the developed models by thermomechanical tests and laboratory hot rolling

trials

• Application of the models and maps to design optimised rolling schedules to achieve different

product requirements for hot-rolled strip and plate, such as:

o Avoid coarse austenite regions

o Refine austenite grain size

o Optimise grain size/properties for minimal alloy additions

o Reduce rolling times/increase mill throughput

2.3.6.1 Task 6.1: Design of validation tests

Gleeble multi-hit tests on industrial material

A large number of single and double hit tests had already been performed in Task 3.2 as part of the

model development work. The validation tests were designed to concentrate on applying these results

to multi-hit deformation tests, which are more representative of the conditions where the models will

be applied.

A series of Gleeble multi-hit deformation tests were defined to validate the new model on samples of

the industrial plate steel used for the laboratory pilot rolling trials described below, identified as 6AM2.

This steel has the chemistry 0.11C, 0.36Si, 1.38Mn, 0.034Nb wt%, which is similar to steel

C1Mn1Nb3 but with slightly higher Mn and Nb content and thus provided a good test of the validity of

the models developed within the project.

The first set of tests were “Tnr”-type tests, similar to those performed by torsion in Task 3.6, to validate

the recrystallisation kinetics equations. The number of deformations that can be applied was more

limited in uniaxial compression. The samples were reheated at 1200°C for 15 minutes and then eight

169

deformations were applied at temperature intervals of 25°C and a strain rate of 1/s. The samples were

held at the deformation temperature for the interpass time minus 5s, to allow isothermal softening,

before being cooled to the next deformation temperature in the remaining 5 seconds. The pass strains

and interpass times were chosen to be typical of the range encountered in industrial plate mill rolling

and are defined in Table 60. The flow stress data were analysed as described in Task 3.6 to determine

the fraction softened and the critical temperatures for recrystallisation. The objective was to perform

tests which included the complete, partial and no recrystallisation regimes. Due to the limited number

of hits it was not always possible to cover the full range of recrystallisation behaviour in a single test.

Table 60: Conditions for multi-hit Gleeble validation tests on steel 6AM2

Steel Strain per

pass

Total interpass

time (s)

Deformation temperatures (°C)

35 1100, 1075, 1050, 1029, 1000, 975, 950, 925 0.3

10 1150, 1125, 1100, 1075, 1050, 1025, 1000, 975 6AM2

0.1 35 1150, 1125, 1100, 1075, 1050, 1025, 1000, 975

A second set of tests was performed on steel 6AM2 to investigate the grain size evolution during a hot

rolling simulation. Samples were reheated at 1200°C for 15 minutes and then deformations of 0.2 strain

were applied at 5 equally spaced temperatures between 1200°C and temperatures of 1100, 1000 and

900°C at a strain rate of 1/s and interpass time of 35s. Additional samples were also held at the final

temperature for up to 900s to assess the grain growth during a hold. A third set of tests were performed

at 1000°C under the same conditions but applying a strain of 0.05, to assess the effect of low strain

passes. Samples were quenched out at intermediate temperatures and times and the prior austenite grain

size measured using the same methods as described in Task 4.2. The full matrix of tests is shown in

Task 6.3, Table 63.

Multipass deformation tests were also carried out by torsion in order to validate the modelling and

processing maps generated in task 5.6. The test schedules were planned in order to simulate industrial

rolling schedules for both plate and strip proucts, and after the tests the specimens were water-

quenched in order to investigate the microstructures developed. The conditions employed in the hot

rolling simulations are summarised in Table 61.

Table 61: Tests carried out in order to simulate plate and strip hot rolling schedules.

Steel Type of

simulation Schedule simulated

Specimen quenched

after:

900ºC End Holding Temperature-30 mm gauge

900ºC End Holding Temperature -50 mm gauge

1000ºC End Holding Temperature -30 mm gauge C2Mn2Al1Nb3

1000ºC End Holding Temperature -50 mm gauge Final rolling pass

C2Mn2Al1

plate

1000ºC End Holding Temperature -50 mm gauge

4 passes + 115 s

900ºC Finish Rolling Temperature-3 mm gauge C2Mn2Al1Nb3 strip

900ºC Finish Rolling Temperature -6 mm gauge Final rolling pass

Torsion simulation of industrial plate schedules

A set of torsion tests was performed by CEIT to try to simulate complete plate mill rolling schedules

for two example plates. It is not possible to perform enough deformation passes in uniaxial

compression to simulate a full schedule, but the number of deformations in torsion is not limited in the

same way. The rolling schedules for a 25mm and 50mm hot rolled plate were supplied by Tata,

170

Figure 182. A larger number of passes were used to roll the plate to 25mm gauge compared with

50mm. The 50mm schedule contained a longer hold time after roughing to reduce the temperature for

entry to the finishing mill. The finish rolling temperature for both schedules was similar at around

825°C. The pass deformations, temperatures, strain rates and interpass times were simulated on steel

C1Mn1Nb3, which is a similar chemistry to many industrial grades. It was not possible to achieve

precisely the same strain rates in combination with the other process conditions, with rates between 1 –

1.5 /s applied in torsion whereas the industrial rates ranged from 1 – 6 /s. Otherwise, the simulation

conditions replicated as close as possible the industrial schedule.

0

0.04

0.08

0.12

0.16

0 5 10 15 20 25

Pass number

Reduction

50mm

25mm

(a) pass reductions

700

750

800

850

900

950

1000

1050

0 5 10 15 20 25

Pass number

Temperature (°C)

50mm

25mm

(b) pass temperatures

Figure 182: Example industrial plate rolling schedules used for validation torsion tests

Laboratory plate mill validation tests

The objective of the validation rolling trials at Tata was to generate at least two different austenite

microstructures during hot rolling on the Tata pilot plate mill to validate the equations for recrystallised

fraction and recrystallised austenite grain size developed in the project. Calculations were made with

the Tata model to construct processing regime maps, which show the effect of changing plate gauge

and end hold temperature (EHT) on the final recrystallised fraction and austenite grain size for a

reference plate rolling schedule. The hold gauge was fixed. Predictions were also made with the CEIT

equations for t50% recrystallisation time, t5% precipitation time and recrystallised austenite grain size

substituted into the Tata model, which showed similar trends. The selected parameters were:

• Plate gauges: 25, 30, 35, 40, 45 and 50mm

• EHT: 850, 900, 950 and 1000°C

• Reheat temperature: 1250 and 1200°C

• Hold gauge: 100mm

The rolling schedules were first calculated for producing these plates on Tata’s industrial plate mill,

using an offline version of the mill scheduler software. Controlled rolled schedules were chosen with

one hold, and finish rolling temperatures still in the fully austenitic region, to avoid complications from

phase transformation occurring at lower rolling temperatures. The exact same schedules cannot be

reproduced on the laboratory mill due to the smaller initial feedstock (140mm c.f. 230mm thickness),

so it was decided to replicate the finishing mill reduction sequence from the industrial mill, but modify

the roughing sequence to achieve the hold gauge in fewer passes (four). The laboratory mill schedules

were run through the laboratory mill scheduling software, to determine the pass temperatures and

timings, and check the schedules were feasible within the mill engineering limits.

The resulting processing regime maps for a reheat temperature of 1250°C are shown in Figure 183.

Points were identified on the maps where distinctly different microstructures should be generated

according to the model predictions. It was decided to roll plates to two gauges: 30mm and 50mm, with

171

two end hold temperatures: 1000°C and 900°C. Additional trials were proposed to quench out the plate

at intermediate gauges during these schedules, such as at the hold gauge, the first pass after the hold

and at 40mm. In total, six trials were planned, as follows:

1. roll to 50mm plate, EHT=1000°C; quench final plate

2. roll to hold gauge (100mm) and quench immediately, to obtain austenite grain size before hold

3. roll to 30mm plate, EHT=1000°C; quench intermediate sample at 40mm; quench final plate

4. roll to 30mm plate, EHT=900°C; quench intermediate sample at 40mm; quench final plate

5. start rolling to 30mm plate, EHT=900°C; quench after first pass after the hold (~85mm), to

obtain austenite grain size

6. start rolling to 30mm plate, EHT=1000°C; quench plate at 50mm gauge, to obtain austenite

grain size

3D Wafer Plot of Frac Rex against Gauge and EHT

Lab Plate Process regime maps new Tata 6AM2 1250C.sta 10v*30c

Frac Rex = Wafer

> 0.9

< 0.9

< 0.7

< 0.5

< 0.3

< 0.1

24 26 28 30 32 34 36 38 40 42 44 46 48 50 52

Gauge (mm)

840

860

880

900

920

940

960

980

1000

1020

En

d H

old

Te

mp

era

ture

(°C

)

(a) Recrystallised fraction

3D Wafer Plot of Dmean against Gauge and EHT

Lab Plate Process regime maps new Tata 6AM2 1250C.sta 10v*30c

Dmean = Wafer

> 80

< 72

< 52

< 32

< 12

24 26 28 30 32 34 36 38 40 42 44 46 48 50 52

Gauge (mm)

840

860

880

900

920

940

960

980

1000

1020

En

d H

old

Te

mp

era

ture

(°C

)

(b) Average austenite grain size (µm)

Figure 183: Processing regime maps for laboratory plate rolling mill at Tata Steel, using a 0.11C

0.034Nb steel, calculated using the Tata metallurgical model showing target validation trials.

The Tata model was also used to predict the recrystallised fraction and austenite grain size for the

proposed rolling schedules. Figure 184 shows examples for EHTs of 1000 and 950°C and plate gauges

of 30, 40 and 50mm. The austenite grain size predictions (Fig. 184(c,d)) for the two EHTs were quite

similar but there was a large difference in predicted recrystallised fraction (Fig. 184(a,b)) after the hold

at pass 4, due to the difference in pass reductions and temperature in the finishing schedule. The plates

with a 1000°C EHT were predicted to continue partially recrystallising in the finishing passes whereas

plates with a 950°C EHT were predicted to stop recrystallising after pass 6.

172

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14

Pass number

Calculated fraction recrystallised (-) 50mm

40mm

30mm

(a) Recrystallised fraction, EHT=1000°C

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14

Pass number

Calculated fraction recrystallised (-) 50mm

40mm

30mm

(b) Recrystallised fraction, EHT=950°C

0

50

100

150

200

250

300

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14

Pass number

Calculated average austenite grain size (µm)

50mm

40mm

30mm

(c) Average austenite grain size, EHT=1000°C

0

50

100

150

200

250

300

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14

Pass number

Calculated average austenite grain size (µm)

50mm

40mm

30mm

(d) Average austenite grain size, EHT=950°C

Figure 184: Recrystallised fractions and austenite grain sizes for laboratory plate rolling schedules,

using a 0.11C 0.034Nb steel and two end hold temperatures, calculated using Tata metallurgical model

Pilot hot strip mill validation tests

Table 62 presents the reference laboratory hot rolling schedule, representative of R&D developments in

thin gauge AHSS steels. The process parameters for the construction of the maps were selected as FRT

between 800 and 900°C and gauge thickness between 2 and 6mm. The selected outputs of the

processing regime maps were chosen as i) Mean recrystallized grain size Drex, ii) Recrystallized

fraction XReX and iii) Retained strain ∆ε. A set of 16 laboratory rolling schedules were constructed

using the same criteria described in Task 5.6. The CEIT model was applied for predicting the selected

output parameters. In this way, reference processing maps for validation tests in laboratory rolling were

constructed. Figure 185 presents the resulting processing maps for the selected steel C2Mn2Al1Nb3,

from which the laboratory mill trials were designed for validation of the maps. Four processing

conditions were selected for laboratory rolling trials represented by the following combinations of FRT

and gauge thickness:

1. Gauge Thickness: 2mm / FRT: 800°C

2. Gauge Thickness: 3mm / FRT: 900°C

3. Gauge Thickness: 6mm / FRT: 850°C

4. Gauge Thickness: 4mm / FRT: 850°C

These conditions were selected in order to obtain the maximum differences in the resulting

microstructures.

173

Table 62: Pilot Strip Hot Rolling Schedules for validating Processing Regime Maps

Stand

Entry

Temperature

(°C)

Thickness

(mm)

Interpass

Time (s)

Strain per

pass

Strain Rate

(/s)

1250°C, 30m 40

R1 1200 35 7,5 0,15 1

R2 1160 26 11,5 0,34 1

R3 1100 17 12 0,49 1

F1 1030 11 9,5 0,50 3

F2 980 7 7,5 0,52 3

F3 920 4 6 0,65 3

F4 840 2 6 0,80 3

(a) Mean austenite

grain size (µm)

(b) Recrystallised

fraction

(c) Retained strain

Figure 185: Processing Maps for C2Mn2Al1Nb3 under selected conditions of

laboratory hot rolling derived from application of CEIT predictive model

Laboratory mill trials were designed and performed together by CRM and AM following the conditions

derived from the constructed laboratory schedules as described above. These tests were performed

followed by water quenching after 5s. The recrystallised austenite grain size was selected as the

parameter for validation of the tests by comparing experimental and predicted values measured at mid-

thickness of the strips. Sampling for metallographic preparation was planned at mid-length of the

strips. Two approaches were adopted for the determination of Drex: the conventional one determining

174

the mean linear intercept from optical micrographs and the alternative one derived from the application

of the reconstruction software on EBSD maps as described in Task 4.2.

2.3.6.2 Task 6.2: Single and double hit validation tests

It was decided to focus the validation tests on multipass deformations, as described in Task 6.1.

2.3.6.3 Task 6.3: Multipass validation tests

Gleeble multi-hit tests on industrial material

The stress-strain curves measured in the multi-hit tests on steel 6AM2 are shown in Figure 186. There

was a gradual increase in flow stress with decreasing temperature when a strain of 0.05 was applied. A

larger increase in flow stress was obtained at a strain of 0.2 at the same interpass time of 35s, with

significant amounts of strain accumulating from hit 5 (1000°C) onwards. Reducing the interpass time

to 10s led to strain accumulation at higher temperatures. Note that the temperatures of the 0.2 strain

hits were 50°C higher for the 10s interpass time compared with the corresponding hit at 35s interpass

time (Table 60), hence the flow stress was lower at each strain. The Tnr was determined in the standard

manner by plotting Mean Flow Stress against inverse temperature, Figure 187. Temperatures of

1009°C and 1056°C were obtained for 0.2 strain and interpass times of 35s and 10s respectively. No Tnr

could be determined for the 0.05 strain test.

0

50

100

150

200

250

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8

Strain (-)

Stress (MPa)

10s

35s

(a) 0.2 strain, 10 and 35s

0

20

40

60

80

100

120

140

0 0.1 0.2 0.3 0.4 0.5

Strain (-)

Stress (MPa)

(b) 0.05 strain, 35s

Figure 186: Measured flow stress curves from multi-hit validation tests on steel 6AM2

The fraction softened was calculated from the flow curves using the method described in Task 3.6

(equation (4)) and was plotted against temperature, Figure 188. The RLT, RST and Tnr temperatures

have been identified on the graph for each steel. Full recrystallisation occurred at temperatures of

1025°C and above with an applied strain of 0.2 and interpass time of 35s. The RLT was raised to

1100°C when the interpass time was reduced to 10s. Below this temperature partial recrystallisation

occurred. It was not possible to perform sufficient hits to define the RST in these tests. The Tnr lay

between the RLT and RST, but closer to the RLT. When the strain was reduced to 0.05 at the same

interpass time, partial recrystallisation occurred at all temperatures.

175

MFS data

High T Regr.

Low T Regr.

test1 Tnr Analysis; Tnr = 1009°C

1000/T / inv.K

0.840.820.80.780.760.74

Mean F

low

Str

ess / M

Pa

180

170

160

150

140

130

120

110

100

90

80

(a) 0.2 strain, 35s

MFS data

High T Regr.

Low T Regr.

test3 Tnr Analysis; Tnr = 1056°C

1000/T / inv.K

0.80.780.760.740.720.7

Mean F

low

Str

ess / M

Pa

160

150

140

130

120

110

100

90

80

70

(b) 0.2 strain, 10s

MFS data

High T Regr.

Low T Regr.

test2 Tnr Analysis

1000/T / inv.K

0.80.780.760.740.720.7

Mean F

low

Str

ess / M

Pa

100

90

80

70

60

50

(c) 0.05 strain, 35s

Figure 187: Mean flow stress versus inverse temperature plots to determine Tnr from multi-hit tests on

steel 6AM2

The softening behaviour can be verified by examining the normalised fraction softened plots in Figure

189. At 0.2 strain, the initial softening can be attributed to recovery up to the marked line. Above this,

the rate of softening increased at all temperatures indicating that recrystallisation was occurring. At the

higher temperatures and 35s interpass time, the slope of the curve then decreased again as

recrystallisation was completed. At lower temperatures with 35s time the curve did not tail off within

the available interpass time and so only partial recrystallisation occurred. At 0.05 strain, however, there

was no steep increase in slope of the curve after the initial recovery period, suggesting that

recrystallisation was not the dominant softening mechanism and recovery was probably continuing. At

the lowest temperatures, the gradient of the curve was the same in both the early and later stages of

softening, indicating that only recovery occurred during the interpass time. None of the curves reached

complete softening within 35s.

The predictions of the new Tata model are also included on Figure 188 as dotted lines. It can be seen

that the model predicted the softening at 0.2 strain very well for both interpass times, although the

softening started at a slightly higher temperature than determined from the flow curves. At 0.05 strain,

the model correctly predicted partial recrystallisation during most of the hits, although the fraction

softened was a little higher than determined from the flow curves. These results show that the model

can be used to accurately predict the transition between complete and partial recrystallisation and the

fraction softened during multi-hit deformations in a Nb microalloyed plate steel.

176

0

0.2

0.4

0.6

0.8

1

1.2

800900100011001200

Temperature (°C)

Fraction softened (-)

0.2 strain 35s

0.05 strain 35s

0.2 strain 10s

0.2 strain 30s calc

0.05 strain 30s calc

0.2 strain 10s calc

RLT Tnr

predicted RST

Figure 188: Measured and predicted fraction softened as a function of temperature for multi-hit

validation tests on steel 6AM2

0

0.2

0.4

0.6

0.8

1

0.001 0.01 0.1 1 10 100

Time in stress relaxation (s)

Softened fraction (-)

Hit 1 1100°C

Hit 2 1075°C

Hit 3 1050°C

Hit 4 1025°C

Hit 5 1000°C

Hit 6 975°C

Hit 7 950°C

Hit 8 925°C

recovery

recrystallisation

(a) 0.2 strain, 35s

0

0.2

0.4

0.6

0.8

1

0.001 0.01 0.1 1 10 100

Time in stress relaxation (s)

Softened fraction (-)

Hit 1 1150°C

Hit 2 1125°C

Hit 3 1100°C

Hit 4 1075°C

Hit 5 1050°C

Hit 6 1025°C

Hit 7 1000°C

Hit 8 975°C

recovery

recovery

(b) 0.05 strain, 35s

Figure 189: Normalised fraction softened plots for multi-hit validation tests on steel 6AM2

Austenite grain size validation tests

Table 63 shows the matrix of tests performed on the industrial steel 6AM2 at strains of 0.2 and 0.05

and the measured austenite grain sizes. The measurements are plotted against the predictions of both

the original and new Tata models in Figure 190 and shows that the predictions have been improved in

the new model. In particular, the predicted grain sizes in the earlier passes are smaller, in line with the

measurements, and the large amount of grain growth in the hold time at 1100°C and to a lesser extent

1000°C predicted by the original model has been significantly reduced. In the 900°C set of tests, the

model predicted that recrystallisation stopped after the deformation at 975°C (pass 3) and therefore

there was no further change in grain size, which was consistent with the measured results.

Table 63: Matrix of grain size validation tests performed on plate steel 6AM2

Deformation pass temperature (°C) Strain per

pass

Strain rate

(/s) 1 2 3 4 5

Hold time at pass 5 temperature

(s)

0.2 1.0 1200 1150 1100 1050 1000 0, 10, 30, 100, 900

0.2 1.0 1200 1175 1150 1125 1100 0, 10, 30, 100, 900

0.2 1.0 1200 1125 1050 975 900 0,900

0.05 1.0 1200 1150 1100 1050 1000 0

177

0

20

40

60

80

100

120

140

160

180

Pass

1

Pass

2

Pass

3

Pass

4

Pass

5

Hold

10s

Hold

30s

Hold

100s

Hold

900s

Austenite grain size (µm)

1100°C Measured

1100°C Predicted

1100°C Predicted original

(a) 1100°C, 0.2 strain

0

20

40

60

80

100

120

140

160

180

Pass

1

Pass

2

Pass

3

Pass

4

Pass

5

Hold

10s

Hold

30s

Hold

100s

Hold

900s

Austenite grain size (µm)

1000°C Measured

1000°C Predicted

1000°C Predicted original

(b) 1000°C, 0.2 strain

0

20

40

60

80

100

120

140

160

180

Pass 1 Pass 2 Pass 3 Pass 4 Hold 900s

Austenite grain size (µm)

900°C Measured

900°C Predicted

900°C Predicted original

(c) 900°C, 0.2 strain

0

50

100

150

200

250

300

Pass 1 Pass 2 Pass 3 Pass 4 Pass 5

Austenite grain size (µm)

1000°C Measured

1000°C Predicted

1000°C Predicted original

(d) 1000°C, 0.05 strain

Figure 190: Measured and predicted austenite grain size for multi-hit validation tests on industrial steel

Torsion simulation of industrial plate schedules

The predictions of the Tata and CEIT models for the torsion tests performed on steel C1Mn1Nb3 to

simulate industrial rolling schedules for 25mm and 50mm gauge plates are shown in Figure 191. The

fractional softening data determined from the torsion flow curves at each pass using the method

described in Task 3.6 (equation (4)) were compared with the predictions of the CEIT model, the

original Tata model and the new Tata model using the recrystallisation coefficients derived in WP5. It

can be seen that the predictions of the CEIT model are in good agreement with the torsion results,

which is not surprising as the model was derived from torsion test data. The Tata model is based on

uniaxial compression test results and the original model did not accurately reproduce the partial

recrystallisation observed in the higher temperature passes of the torsion tests. The new Tata model

predicted slightly more softening at each temperature, closer to the measured data. The modelling work

in Task 5.5 showed that the torsion tests could be better simulated by the Tata model if the grain size

dependent strain exponent p = 5.6D-0.15

from the CEIT model (equation (28)) was used in the t50

equation. Figure 191(e-f) shows the predictions of the new Tata model but with a modified strain

exponent p. This gives even better agreement with the torsion test results.

178

0

20

40

60

80

100

120

800900100011001200T (ºC)

FS (%)

Experimental results

Ceit model

Tata model

Nb(C,N) prec

1011ºC

Nb(C,N) prec

882ºC

(a) 25mm schedule, measured + CEIT model +

original Tata model

0

20

40

60

80

100

120

800900100011001200T (ºC)

FS (%)

Experimental Results

Ceit Model

Tata model

Nb(C,N) prec

905°C

(b) 50mm schedule, measured + CEIT model +

original Tata model

0

20

40

60

80

100

120

800900100011001200T (ºC)

FS (%)

Experimental results

Ceit model

New Tata model

Nb(C,N) prec

1011ºC

Nb(C,N) prec

909ºC

(c) 25mm schedule, new Tata model

0

20

40

60

80

100

120

800900100011001200T (ºC)

FS (%)

Experimental Results

Ceit Model

new Tata model

Nb(C,N) prec

912°C

(d) 50mm schedule, new Tata model

0

20

40

60

80

100

120

800900100011001200T (ºC)

FS (%)

Experimental results

Ceit model

New Tata model, CEIT p

Nb(C,N) prec

1011ºC

Nb(C,N) prec

932ºC

(e) 25mm schedule, new Tata model + CEIT p

value

0

20

40

60

80

100

120

800900100011001200T (ºC)

FS (%)

Experimental Results

Ceit Model

new Tata model,CEIT p

Nb(C,N) prec

912°C

(f) 50mm schedule, new Tata model + CEIT p

value

Figure 191: Measured and predicted fractional softening for multipass torsion tests based on industrial

plate rolling schedules

In order to validate the predictions of the simulations performed to build the processing maps in Task

5.6 several multipass torsion tests were carried out by CEIT, which aimed to simulate real plate and

strip hot rolling schedules.

In the case of plate rolling, simulations for End Hold Temperatures of 900 and 1000ºC and final

thickness values of 50 and 30 mm were carried with the C2Mn2Al1Nb3 steel. After the test, the

179

specimen was quenched and the microstructure analysed and compared with the model predictions. In

addition, a simulation was carried out with the C2Mn2Al1 steel for EHT 1000ºC and a final thickness

of 50 mm. In this latter case a specimen was also quenched at an intermediate deformation level (4

passes + 115 s). Due to the limitation of the torsion machine, the test schedules could not be exactly

reproduced and some modifications were carried out in the deformation sequences. Primarily this

resulted in the use of a lower strain rate than in the actual schedule, particularly in the later passes, and

some slightly higher or lower strains in selected rolling passes. The temperatures and interpass times

were precisely as planned.

The strain-stress curves obtained in the rolling simulations carried out with the C2Mn2Al1Nb3 and the

C2Mn2Al1 steel are shown in Figure 192. The first four deformation passes were similar for all the

simulations carried out and represent the high temperature roughing passes. In the rest of the cases, the

stress levels of the curves increased significantly with decreasing EHT. The stress levels obtained for

the C2Mn2Al1Nb3 and C2Mn2Al1 steels were very similar.

0

50

100

150

200

250

0 0.5 1 1.5 2 2.5 3

Strain

Stress (MPa)

900ºC 50mm

900ºC 30mm

1000ºC 50mm

1000ºC 30mm

0

50

100

150

200

250

0 0.5 1 1.5 2 2.5 3

Strain

Stress (MPa)

C2Mn2Al1 steel

1000ºC, 50 mm

(a) C2Mn2Al1Nb3. (b) C2Mn2Al

Figure 192: Stress-strain curves obtained in the plate rolling torsion simulations

From the flow curves, the anisothermal softening between deformation passes was calculated for each

of the tests carried out and this is compared with the CEIT model predictions in Figure 193. From the

figures a relative good fit was observed for all the simulations, although some deviations were obtained

in the first passes. At these initial passes very high temperatures combined with very low deformations,

out of the range for which the model was developed [5], are probably the cause of the model failure.

The microstructures obtained from the specimens quenched after the different simulations are

illustrated in Figure 194. For the C2Mn2Al1Nb3 steel, in all the cases microstructures with a certain

strain accumulation level were obtained, although this seemed to be significantly lower for the 1000ºC-

50 mm schedule (Figure 194(c)). In good agreement with the processing maps constructed for the plate

rolling simulations, the micrographs denoted that refined microstructures were obtained for the highest

EHT considered, 1000ºC, compared to 900ºC. The figures also show that the microstructures obtained

after the 50 mm-1000ºC hot rolling simulation for C2Mn2Al1Nb3 (Figure 194(c)) and C2Mn2Al1

(Figure 194(e)) were very similar.

180

0

20

40

60

80

100

120

85095010501150

FS (%)

T (ºC)

900ºC 50mm

CEIT Model

0

20

40

60

80

100

120

7509501150

FS (%)

T (ºC)

900ºC 30mm

CEIT Model

(a) C2Mn2Al1Nb3, 900ºC-50mm (b) C2Mn2Al1Nb3, 900ºC-30mm

0

20

40

60

80

100

120

85095010501150

FS (%)

T (ºC)

1000ºC 50mm

CEIT Model

0

20

40

60

80

100

120

85095010501150

FS (%)

T (ºC)

1000ºC 30mm

CEIT Model

(c) C2Mn2Al1Nb3, 1000ºC-50mm (d) C2Mn2Al1Nb3, 1000ºC-30mm

0

20

40

60

80

100

120

85095010501150

T (ºC)

FS (%)

1000ºC 50mm

CEIT Model

(e) C2Mn2Al1, 1000ºC-50mm

Figure 193: Anisothermal experimental softening results and CEIT model predictions for the plate

rolling simulations.

In order to compare the microstructures with the model predictions, the microstructures shown above

were characterised. In the case of recrystallised equiaxed microstructures, the average equivalent

diameter criteria has been used; however, in the present case deformed microstructures are obtained.

Therefore, as well as the equivalent area diameter, the average grain size measured by linear

intersection were calculated. The results obtained together with the CEIT model predictions are

summarised in Table 64. The simulations of the actual schedules tended to give refined grain sizes

compared to the target schedules. This was due to the higher deformation values applied in some of the

deformation passes.

Comparison of the grain size measurements carried out shows that for the deformed microstructures,

the average equivalent diameter tended to give larger grain size measurements than the linear

intersection method, whereas for the recrystallised microstructures the two values were very similar.

For the C2Mn2Al1Nb3 steel, the agreement between the linear intercept and the model grain size

predictions were excellent. The grain size refinement predicted by increasing the End Holding

Temperature was confirmed by the measurements. For the C2Mn2Al1 steel and 1000ºC-50 mm the fit

181

was a bit worse. For the same conditions, the model predicted slightly coarser microstructure for the

Al1 than for the C2Mn2Al1Nb3 steel (63 vs. 39 µm); however, this does not agree with the

experimental findings.

A C2Mn2Al1 steel was also quenched at an intermediate stage of the 1000ºC-50 mm rolling schedule,

after 4 rolling passes + 115s, to investigate the accuracy of the model during the hot deformation

schedule. It should be noted that the amount of deformation applied in some of the rolling passes was

as low as ε=0.06. Previous experience indicates that in these cases the CEIT model for predicting the

recrystallised grain size tends to overestimate the experimental data.

C2Mn2Al1Nb3

(a) 900ºC, 50 mm, final microstructure

(b) 900ºC, 30 mm, final microstructure

(c) 1000ºC, 50 mm, final microstructure

(d) 1000ºC, 30 mm, final microstructure

C2Mn2Al1

(e) 1000ºC-50 mm, final microstructure

(f) 1000ºC-50 mm, 4 passes + 115 s

Figure 194: Microstructures obtained after the plate rolling torsion simulations carried out with the

C2Mn2Al1Nb3 and C2Mn2Al1 steels.

182

Table 64: Comparison of the experimental grain size measurements and the predictions of the CEIT

model for the plate rolling torsion simulations.

Steel Condition

Average Grain

size

(distribution),

(µm)

Average Grain

size (linear

intersection)

(µm)

Grain size, CEIT

model, target

rolling schedule

(µm)

Grain size, CEIT

model, actual

rolling schedule

(µm)

900ºC-50 mm 86±3 62±3 71 60

900ºC-30 mm 93±4 44±2 89 50

1000ºC-50 mm 38±1 35±2 48 39 C2Mn2Al1Nb3

1000ºC-30 mm 20±1 19±1 30 28

1000-50 mm, final

microstructure 40±1 37±2 70 63

C2Mn2Al1 1000-50 mm, 4 passes

+ 115 s 145±6 117±14 264 261

The grain size evolution predicted by the CEIT model for the C2Mn2Al1 steel at 1000ºC-50 mm is

illustrated in Figure 195. The figure shows that during the first deformation passes the predicted

recrystallised grain size increased significantly (354 µm) compared to the initial grain size (100 µm)

due to the small amount of deformation applied. The experimental measurement carried out after the

fourth deformation pass (145 µm) confirms that the model results (261 µm) overestimate the

experimental grain size. However, it must also be noted that in good agreement with the predictions of

the model, the grain size obtained after the fourth rolling pass was larger than the initial grain size.

0

50

100

150

200

250

300

350

400

900100011001200

T (ºC)

Drex (µm)

Drex

Linear Intercept measurements

Average Equivalent Diameter

D ( µµ µµ

m)

Predicted Grain size

Figure 195: Grain size predictions obtained for the C2Mn2Al1 steel (1000ºC-50 mm plate schedule)

and experimental measurements.

Multipass torsion tests were carried out in order to simulate strip hot rolling schedules with the

C2Mn2Al1Nb3 steel, using the same Finish Rolling Temperature, 900ºC, and two different gauges, 6

and 3 mm. The conditions obtained in the torsion machine were very close to the proposed schedules.

The stress-strain curves obtained from the tests are shown in Figure 196. The flow stresses

corresponding to the three initial passes are the same for the two rolling schedules, and therefore

similar stress levels were obtained for both sequences. In the next passes lower stress levels were

obtained for the 3 mm schedule due to the higher amount of deformation applied, which allows higher

interpass softening levels to occur.

183

0

50

100

150

200

250

0 0.5 1 1.5 2 2.5 3 3.5

Strain

Stress (MPa)

900ºC 3mm

900ºC 6mm

Figure 196: Stress-strain curves obtained in the strip rolling simulations carried out with the C2Al1Nb3

steel.

The anisothermal softening between passes obtained from the flow curves are compared with the model

predictions in Figure 197 for the two strip rolling simulations. From the figure, good agreement

between the experimental data and the model predictions can be observed. Again, some deviations are

observed at the highest deformation temperatures.

0

20

40

60

80

100

85095010501150

T (ºC)

FS (%)

900ºC 6mm

CEIT Model

(a) 6mm gauge

0

20

40

60

80

100

85095010501150

T (ºC)

FS (%)

900ºC 3mm

CEIT Model

(b) 3mm gauge

Figure 197: Anisothermal experimental softening results and CEIT model predictions for the strip

rolling simulations.

Images of the microstructures obtained after the last pass and cooling to 800ºC at 20ºC/s cooling rate

are shown in Figure 198. In the two cases, microstructures with a high level of strain accumulation

were obtained, the microstructure for the 3mm simulation being slightly refined compared to the 6 mm

case.

(a) C2Mn2Al1Nb3, FRT 900ºC, 6mm

(b) C2Mn2Al1Nb3, FRT 900ºC, 3mm

Figure 198: Final austenite microstructures obtained after strip rolling simulations on C2Mn2Al1Nb3.

184

The grain size measurements and the model predictions are summarised in Table 65. In this case the

differences between the average equivalent diameter and the linear intersections measurements were

smaller than in the plate rolling simulations. The table also shows good agreement between the grain

size measurements carried out and the predictions of the model.

Table 65: Comparison of the experimental grain size measurements and the predictions of the CEIT

model for the strip rolling simulations carried out.

Steel Condition Average Grain

size (distribution),

(µm)

Average Grain size

(linear intersection)

(µm)

CEIT model,

target rolling

schedule

(µm)

CEIT model,

actual rolling

schedule

(µm)

900ºC-6 mm, final

microstructure 16±1 14±1 14 13

C2Mn2Al1Nb3 900ºC-3 mm, final

microstructure 9±1 9±1 6 6

For non-equiaxed grain structures, the grain boundary area per unit volume, Sv is often considered more

representative than the mean grain size:

SV (mm-1)=2000/Dmean(microns) (61)

The pancaked microstructures were therefore also characterised in an additional way, by measuring the

mean thickness of the grains in a direction perpendicular to the elongation direction (deformation

direction). From this value, Sv was calculated applying the equation (2) developed for torsion given in

[81]. The sum of the accumulated strains predicted by the microstructural model in the last passes (in

the non-recrystallisation regime) was used for the calculation. The values of Sv were compared with

those calculated from the grain sizes in Table 64 and the value of Dmean predicted by the model using

equation (61), Table 66. It was observed that the values of Sv calculated from the different methods

correlated quite well. Therefore, the measurement of the specific grain boundary area performed by the

linear intersection method was quite confident and comparable to that calculated by the equation

developed for torsion from the measurement of thickness of the pancaked grains.

Table 66: Comparison of the values of Sv determined from experimental grain size measurements and

the predictions of the CEIT model for the plate rolling torsion simulations.

Steel Condition Sv (torsion eq.)

(mm^-1)

Sv (linear

intercept)

(mm^-1)

Sv (distribution)

(mm^-1)

Sv model

(mm^-1)

Plate 900ºC-50 mm 31 32 23 33

Plate 900ºC-30 mm 43 45 22 40

Plate 1000ºC-50 mm 59 57 53 51 C2Mn2Al1Nb3

Plate 1000ºC-30 mm 100 105 100 71

Plate 1000-50 mm,

final microstructure 53 54 50 32

C2Mn2Al1 Plate 1000-50 mm,

4 passes + 115 s 19 17 14 8

Strip 900°C 3mm 219 222 222 333 C2Mn2Al1Nb3

Strip 900°C 6mm 132 143 125 154

185

2.3.6.4 Task 6.4: Pilot rolling trials

Laboratory plate mill rolling

Tata Steel used a sample of a Nb microalloyed industrial slab from one of the plate mills (see Task 2.3)

for validation rolling trials on their laboratory pilot plate mill (sample code 6AM2). The slab was sawn

into blocks of size approximately 140 x 140 x 400 mm, taken from the top half of the 230mm slab, in

preparation for rolling. The pilot mill is a two-high, single stand reversing plate mill on which the

reheated blocks can be controlled rolled down from 140mm to gauges of ~10mm. A direct quenching

unit is attached at the exit of the rolling stand in which the plates can be quenched to room temperature

if required. Additionally, small samples can be gas cut off the end of the plate at intermediate rolling

passes, to study the microstructure evolution during the rolling schedule. The roll gap, mill stand loads

and interpass timings were automatically recorded by the mill computer. Surface temperatures of the

plate before each pass were measured with handheld pyrometers.

Six blocks from the commercial slab were rolled, using the schedules designed in Task 6.1. The blocks

were reheated at 1250°C and soaked for at least an hour at this temperature to ensure that all of the Nb

was in solution before rolling. The schedules had to be modified slightly from the design, due to

difficulties that occurred during the rolling trials. The hold gauge was reduced slightly from 100mm to

93mm to avoid too large a reduction in the first pass after the hold. The end hold temperature of 900°C

was increased to 950°C, to prevent the plate becoming too cold on the bottom surface during the long

hold time required to reach this temperature. This results in the plate turning up during rolling passes

after the hold so that it was not flat enough to finish rolling in trials 3 and 4. The final gauge of 30mm

was therefore not reached, the plate having to be finished at 40mm gauge. These bent plates also cannot

physically be entered into the quench unit so a piece was gas cut off the end of the final plate. Trial 3

was repeated (replacing the planned trial 6) to try to reach the final 30mm gauge, but the same problem

occurred and the plate finished at 40mm again. The gas cut intermediate and final plate samples were

quenched into a water bath as quickly as possible to try to obtain the prior austenite grain structure. The

trial conditions are summarised in Table 67. The actual schedules rolled are illustrated in Figure 199

for EHT of 1000°C and 950°C. The arrows indicate the gauges at which samples were quenched out

for microstructural examination.

Table 67: Summary of validation laboratory plate rolling trials at Tata Steel on slab 6AM2

Trial Sample

code

Hold

gauge

(mm)

EHT (°C)

(Aim/Actual)

FRT (°C)

(Actual)

No. of passes

(Aim/Actual)

Final gauge

(mm)

(Aim/Actual)

Sample

gauge

(mm)

1 A 93 1000/1008 995 8/8 50/49 49

2 C 93 - 1065 4/4 93/93 93

3 E 93 1000/998 942 9/10 30/34 40

4 G 93 950/950 925 10/14 30/41 41

5 H 93 950/951 942 5/5 84/84 84

6 I 93 1000/998 980 8/10 30/39 39

Through thickness slices ~20mm wide were taken from each of the quenched plates and intermediate

gas cut samples and tempered overnight in a furnace at 500°C to improve the response of the austenite

grain boundaries to chemical etching. The slices were then ground, polished and etched in 2% Nital for

optical metallographic examination. Example micrographs showing the microstructures of the plates at

the mid-thickness position are shown in Figure 200. In most cases, the plate had not been quenched fast

enough to fully transform to martensite, so the microstructures were predominantly bainitic with some

martensite at the surface of the plate. It was difficult to quantify the prior austenite grain sizes from

these samples but an indication of the grain size can be obtained from the micrographs. In samples A

and C, the microstructure at the plate centre was mostly bainitic, but the prior austenite grain

boundaries were delineated with ferrite. An estimate of the prior austenite grain size only could be

186

made in sample A, whilst in sample C three areas were measured using the ASTM chart comparison

technique. Sample H had transformed to martensite near the surface and was re-etched in aqueous

picric acid plus Teepol (wetting agent) to reveal the prior austenite grains. An ASTM measurement was

made from three areas at the 2mm sub-surface position. The grain size results are shown in Table 68.

850

900

950

1000

1050

1100

1150

1200

0 20 40 60 80 100 120 140

Roll gap (mm)

Temperature (°C)

6AM2A

6AM2C

6AM2E

6AM2I

40mm

EHT=1000°C

100mm

50mm

(a) EHT = 1000°C

850

900

950

1000

1050

1100

1150

0 20 40 60 80 100 120 140

Roll gap (mm)

Temperature (°C)

6AM2C

6AM2G

6AM2H

EHT=950°C

40mm

100mm

85mm

(b) EHT = 950°C

Figure 199: Tata laboratory plate mill rolling schedules for two End Hold Temperatures. Arrows

indicate passes at which samples were quenched for microstructural examination.

Table 68: Estimated prior austenite grain sizes in laboratory validation plates

Sample Gauge

(mm)

Measurement location ASTM grain size Equivalent MLI

grain size (µm)

6AM2A 49 Mid-thickness 5.0 – 5.5 (approx.) ~50

6AM2C 93 Mid-thickness 4.0 80

6AM2H 84 Sub-surface 4.5 – 5.0 ~60

Sample C which was quenched at the thickest gauge of 93mm and the highest temperature of 1065°C,

at the start of the hold in the schedule, had the coarsest austenite grain size of around 80µm. Sample H

which was quenched at a gauge of 84mm from a temperature of 942°C after the first pass after the hold

had a grain size of approximately 60µm. These two samples had coarser grains than the other samples

which had been quenched from thinner gauges. These grain sizes are in excellent agreement with the

predictions of the model in Figure 184, which predicted a grain size of 83µm at the start of the hold

(pass 4) and 57µm in the first pass after the hold (pass 5) in the 950°C EHT schedule.

All of the samples appeared to contain recrystallised austenite grains apart from sample G1 which

clearly showed large, pancaked austenite grains. This plate had been held to a lower end hold

temperature of 950°C and then received 6 finishing passes with the final pass at 925°C, the lowest FRT

of all the plates. This was consistent with the predictions of the model shown in Figure 184 which

indicated that recrystallisation should stop in the 2nd

pass after the hold in the 950°C EHT schedule

whereas some partial recrystallisation should continue during finishing in the 1000°C EHT schedule.

Samples A, E1 and I1, which were quenched out 2 or 3 passes from the end of the complete 1000°C

EHT schedules and had FRTs between 990 and 972°C, all had a finer, uniform, recrystallised grain

structure consistent with repeated recrystallisation in the finishing passes. The grain sizes appeared to

be quite similar for the 40mm and 50mm plates and for both EHTs, which is again consistent with the

predictions of the model in Figure 184.

187

(a) 6AM2A, mid-thickness

(b) 6AM2C, mid-thickness

(c) 6AM2E1, mid-thickness

(d) 6AM2G1, mid-thickness

(e) 6AM2H, mid-thickness

(f) 6AM2I1, mid-thickness

Figure 200: Optical micrographs of Tata laboratory validation plate samples after quenching

Pilot hot strip mill rolling

A validation heat was cast at CRM to perform validation rolling trials on a steel grade containing

0.2%C-2%Mn-0%Si-1%Al-0.03%Nb. From the ingot, blocks of dimensions 60mm length x 120mm

width x 40mm thickness were machined. The blocks were reheated at 1250°C for 1h in a reheating

furnace to assure complete dissolution of niobium in the austenite phase and to limit macro-

segregation. They were then hot rolled on the CRM pilot reversing mill using the rolling conditions

defined in Task 6.1. After the last rolling pass, hot rolled plates were quenched in a water bank to

produce a full martensitic microstructure. The reference rolling temperatures and experimental rolling

temperatures measured by pyrometers during discontinuous pilot rolling trials are given in Table 69.

The target finishing rolling temperatures were successfully achieved whilst a 60-80°C temperature

difference was observed for the first two roughing passes due to the time needed to move the block

from the reheating furnace to the pilot mill. The total rolling forces measured during the pilot rolling

trials are also included in Table 69.

188

After rolling, two metallographic samples were machined per plate to reveal the resulting austenitic

microstructure after rolling. One sample was sent to ArcelorMittal to perform some EBSD

reconstruction analysis. The second sample was tempered at 500°C for 1h to enable the prior austenite

grain boundaries to be revealed after Bechet-Beauchard etching and to perform light optical

microscopy observations. The microstructures obtained a maximum of 5 seconds after the last pass are

given in Figure 201. For the processing regime map of C2Mn2Al1Nb3 (Figure 185), predictions of

recrystallised grain size, recrystallised fraction and retained strain fraction are summarised in Table 70.

Table 69: Discontinuous pilot rolling conditions – Strip validation trials

Table 70: Summary of predicted values from processing regime maps according to pilot strip rolling

validation conditions

189

Figure 201: Austenitic microstructure of grade C2Mn2Al1Nb3 after last validation rolling pass

The microstructure for the condition with FRT=800°C – thickness= 2mm reveals the presence of small

equiaxed ferrite grains (~2-3µm) in a matrix of non-recrystallised austenite grain. The presence of

ferrite was not predicted by the processing regime maps since the model used to construct the maps

does not consider phase transformation from austenite during rolling. In the optical microstructures of

the other rolling conditions, no clear difference in terms of grain size was observed. Indeed, as

predicted by the model, only a small difference between recrystallised grain size should be observed

between thicknesses of 3mm-4mm-6mm, which are within the accuracy domain of the measurement.

However, regarding the microstructure of the condition FRT=850°C– thickness= 6mm and as predicted

in the processing regime map, the austenite grains appeared less elongated than for other conditions

highlighting less retained strain. To conclude regarding the validation trials, no clear difference was

observed on optical microstructures since as predicted by the model only small differences should be

observed. The main difference between all conditions would have been observed with the condition of

a FRT=800°C, however due to the presence of ferrite and the possible interaction effect with austenite

recrystallisation, the microstructure of this condition could not be considered for direct comparison.

2.3.6.5 Task 6.5: Validation against pilot mill and industrial mill data

Plate mill data

The equations for prediction of recrystallisation kinetics and austenite grain size can be combined with

hot flow stress equations and rolling models to predict the mill stand loads. This provides a means of

190

assessing the accuracy of the models in predicting the strain accumulation in the finishing mill. The

Sims equation [80] is commonly used to predict the load from the roll bite geometry and mean flow

stress. Comparisons have been made between the model predictions and the measured loads on the Tata

pilot plate rolling mill and an industrial plate mill.

The loads recorded by the mill logging system during the pilot rolling trials of three of the validation

plates in Task 6.4 are plotted against pass number in Figure 202 (dashed lines). The rolling schedule

for the first 4 passes was the same for each plate, and the loads were reasonably consistent. The

finishing schedule loads were also similar for most plates. There was a drop in load in the first pass

after the hold for plate E before the load increased in line with the other plates. The final two passes of

plate A also had lower measured loads. The solid lines show the predicted loads for the plates. Plates A

and E were both rolled with an end hold temperature of 1000°C to final aim gauges of 50mm and

30mm respectively. Excellent agreement was obtained between the predicted and measured loads

throughout the rolling schedule. The loads during the roughing passes of plate G were well predicted

but after the hold they were over-estimated by the model. This plate was held to a lower EHT of 950°C,

and the model predicted that recrystallisation stopped in the 2nd

finishing pass (pass 6) and therefore

significant amounts of strain were accumulated in the remaining passes, Figure 203, which led to the

calculation of a large flow stress and thus load in these passes. The amount of strain accumulated in the

finishing passes of the plates with an EHT of 1000°C was much smaller as recrystallisation continued

for all passes in plate A and until the penultimate pass in plate E, leading to more accurate load

predictions.

0

40

80

120

160

200

0 1 2 3 4 5 6 7 8 9 10 11

Pass number

Total mill load (tonnes)

6AM2A

6AM2E

6AM2G

6AM2A calc

6AM2E calc

6AM2G calc

Figure 202: Measured and predicted mill stand

loads for Tata pilot plate rolling trials

0.0

0.2

0.4

0.6

0.8

1.0

0 1 2 3 4 5 6 7 8 9 10 11

Pass number

Strain (-)

6AM2A total

6AM2E total

6AM2G total

6AM2A applied

6AM2E applied

6AM2G applied

Figure 203: Applied strain and calculated total

accumulated strain per pass for Tata pilot plate

rolling trials

The same calculations have been performed for a number of plates of different chemistries rolled on an

industrial plate mill and compared with the forces on the mill stands logged at each pass in the rolling

schedule. Figure 204(a) shows the results for all the plates of one particular CMn grade produced in

one year. There was no increase in force throughout the rolling schedule, as the steel continues to

recrystallise in all passes. This shows that the model is in excellent agreement with the measured mill

data in the absence of precipitation and strain accumulation. Figure 204(b) shows an example of the

results for an individual Nb microalloyed plate. The agreement between measured and predicted force

using the new model was again good until pass 13, where the predicted force started to increase

significantly. As was observed for the laboratory plate mill schedules, this point corresponds to the

pass at which recrystallisation stops (due to precipitation pinning of austenite grain boundaries) and

significant strain accumulation begins in the model calculations. The same behaviour was found for all

the Nb microalloyed plates analysed.

191

23

45

67

89

1011

1213

1415

1617

1819

2021

2223

24

Pass number

0

5

10

15

20

25

30

35

40

Fo

rce

(M

N)

Measured

New model

(a) CMn plates

2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

Pass number

0

10

20

30

40

50

60

Fo

rce

(M

N)

Measured

Original model

New model

(b) Nb microalloyed plate

Figure 204: Measured and predicted mill stand forces for typical industrial plate mill rolling schedules

It can be concluded from the analysis of both the laboratory and industrial plate mill loads that the

model is accurate during the passes where complete or partial recrystallisation occurs, but predicts too

much strain accumulation once recrystallisation has stopped due to precipitation of Nb(C,N).

Pilot hot strip mill data

Based on measured rolling forces and temperatures during pilot discontinuous hot rolling trials (see

Table 69), the temperature range at which rolling forces start to accumulate was estimated. The

methodology described in [82] was employed. The conversion of the total rolling force to mean flow

stress of materials requires the knowledge of the plate width, the roll pass reduction and the roll radius.

The average rolling pressure was calculated according to equation (62). Finally, considering plane

strain compression conditions and removing the contribution of the friction to the total force, the

material flow stress was calculated with equation (63).

hRw

FPtot

∆=

P= total pressure (Pa)

F = rolling force (N)

W = plate width (m)

∆h = reduction (mm)

(62)

Q

PP tot

×=

32

Q = geometric coefficient (63)

Q is a geometric factor describing the friction hill. This parameter is function of the roll pass geometry

and friction coefficient [35]. A friction coefficient of 0.25 was estimated from StripCam simulations.

Results of the pilot rolling force analysis are given in Figure 205 showing the evolution of the material

mean flow stress as function of the average rolling temperature per rolling pass. The figure reveals that

no significant difference was observed in rolling forces for conditions where the final rolling thickness

was in the range 2 to 4 mm. For these conditions, rolling forces start to accumulate at around 1000°C.

Concerning the rolling condition where the final strip thickness was 6mm, rolling forces start to

accumulate at around 950°C, which is one pass later than previous conditions. As experimentally

observed, less total deformation was applied in the finishing stage for the 6mm condition, leading to

less internal energy available for recrystallisation and consequently to lower non-recrystallisation

temperature range.

192

Figure 205: Evolution of material mean flow stress during pilot rolling trials

2.4 Conclusions

WP1: Eight coordination meetings of all the partners have been held during the project, hosted by each

partner in turn.

WP2: Provision of Materials

Task 2.1 and 2.2: Production of laboratory casts and laboratory rolling

o A matrix of casts based around a reference steel containing 0.1C, 1.0Mn, 0.03Al, 0.005N 0.02P

wt % was defined. The steels contained systematic variations in Mn, Si, Al, C and Nb

additions.

o A total of 19 laboratory ingots were cast between the project partners and rolled down to plate

or strip material on pilot rolling mills to provide the steels for investigation.

o This has enabled the study of the effects of Mn, Si and Al individually, the interaction effect of

each element with Nb and the influence of increasing the amount of Nb on the interaction

effect.

Task 2.3: Provision of industrial material

o An industrially cast Nb microalloyed slab sample for the validation trials in WP6 was obtained

from a Tata plate mill.

WP3: Thermomechanical testing

Task 3.2: Solute drag effect on static recrystallisation kinetics

o A large thermomechanical test programme to study static recrystallisation kinetics was

completed. The effects of Nb, Al, Si, Mn and C content, strain, temperature, strain rate and

austenite grain size were investigated.

o Tests on the 0.1 wt% C MnNb series of steels showed that the rate of softening decreased with

decreasing strain (0.35 � 0.05), temperature (1150 � 950°C) or strain rate (10 � 0.1/s), or

increasing Nb content (0 � 0.03 wt%). Recrystallisation was the dominant softening

mechanism for deformation at temperatures of 1050°C and above, apart from some tests at 0.05

strain which showed only recovery. Deformation at 950°C led to recrystallisation in the

C1Mn1 steel but mostly recovery in the Nb steels.

o The retardation of softening in the Nb steels compared to the CMn steel was attributed to Nb

solute drag at deformation temperatures of 1050°C and above. At 950°C, as well as solute drag,

an additional contribution due to precipitation could be identified in the softening curves.

193

o No strong effect of initial austenite grain size on the recrystallisation kinetics was found in the

Mn1Nb or Mn2Nb steels. This contradicts other published data but no explanation for these

results could be found.

o No significant effect of increasing the C content from 0.1 to 0.2 wt% was found on the

softening kinetics in the absence of precipitation.

o Double-hit torsion tests showed that the softening kinetics were retarded by Al addition, which

was related to different mechanisms depending on the temperature and Al content. At 1%Al

content the softening delay was due to Al solute drag effect at all the temperatures investigated.

Increasing the Al content to 2%, at high temperatures the retardation was also due to solute

drag, but at temperatures below 1000ºC, γ→α phase transformation occurred concurrently with

softening, leading to a higher retardation effect.

o Double-hit torsion tests were performed at 950-1050°C on the Si steels at strains of 0.2-0.7. At

0.7 strain, dynamic recrystallisation was initiated in the steels without Nb additions.

o No clear effect of increasing Si content from 1wt% to 2wt% was observed on the softening

kinetics. Comparison for one condition with a steel grade containing 0%Si revealed that Si

retards recrystallisation. A saturation effect of Si on SRX kinetics was observed. Addition of

Nb in combination with Si showed an increasing retardation effect, with incomplete softening

occurring at higher Nb levels and lower temperatures.

o The round robin tests on steel C2Mn1Nb3 showed slightly faster recrystallisation kinetics were

obtained from stress relaxation tests compared with double hit compression tests on the

Gleeble machine. This is in agreement with previous work.

o The round robin tests on steel C1Mn1Nb7 using torsion machines revealed important

differences in flow stress mainly attributed to differences in temperature measurements and the

adopted temperature control criterion but also to differences in the strain hardening behaviour.

o An additional comparison between softening data from torsion tests using an external database

to the project data was made, which showed only small differences in softening with AM

results.

o Further work would be required to resolve the discrepancies between the torsion test results.

Alternatively, it could be argued that the building of a common database with contributions

from different torsion machines may not be a reliable approach for constructing or fitting a

single predictive model.

Task 3.3: Solute drag effect on dynamic recrystallisation kinetics

o A series of single hit hot torsion tests were performed to study the effect of Si and Mn on the

critical and peak strains for dynamic recrystallisation. Strain rates between 0.1 and 1.0/s and

temperatures from 950 to 1050°C were applied. The second derivative method was used to

analyse the data.

Task 3.4: Grain growth kinetics

o A matrix of tests was performed on steels C1Mn1, C1Mn1Nb1 and C1Mn1Nb3 to investigate

the austenite grain growth kinetics for hold times of up to 900s after deformation at

temperatures between 1150 – 950°C.

o No significant grain growth was observed in any of the tests. This was consistent with previous

results for Nb microalloyed steels but was contrary to experience for the C1Mn1 steel.

Task 3.5: Strain induced precipitation effects

o Double-hit torsion tests were carried out with the C2Mn2Al1Nb3, C2Mn2Al2Nb3 and

C2Mn2Al2Nb7 steels in the 1065-900ºC temperature range in order to investigate the effect of

Nb(C,N) strain-induced precipitation on the softening kinetics.

o At temperatures lower than 1065ºC the softening obtained for these steels was significantly

delayed and did not complete in the range of interpass times investigated. A stop in the

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softening curves (plateau) was detected, and in some of the cases, after a certain holding time,

the softening levels increased again.

o Similar interrupted torsion tests were performed on the C2Si0Mn2Nb3 and C2Si2Mn2Nb3

steels to evaluate the influence of Si on Nb precipitation. Hold times of up to 10000s were

investigated as well as a sample quenched before applying the deformation to define the initial

precipitation state of the austenite.

Task 3.6: Determination of critical temperatures for recrystallisation

o The critical recrystallisation temperatures (RLT, RST and Tnr) have been determined using

multipass torsion tests for steels C1Mn1Nb3 and C2Mn1Nb3, the Si series and Al series of

steels.

o In the C1Mn1Nb3 and C2Mn1Nb3 steels, decreasing the interpass time from 30 to 10 seconds

led to an increase in both Tnr and RLT. Decreasing the applied strain per pass from 0.3 to 0.1

led to incomplete softening between passes throughout the entire schedule.

o Increasing the C content from 0.1 to 0.2 wt% slightly increased both the Tnr and RLT

temperatures and decreased the Ar3 temperature.

o In the 2wt%Al steels, some of the specimens broke during the test due to low ductility and as a

result the tests could not be completed.

o 1 or 2% Al addition resulted in an increase of the recrystallisation critical temperatures.

However, the increase depended strongly on the Al content; while 1%Al leads to a slight

increment in the non-recrystallisation temperature (Tnr) of ∼30ºC, 2%Al addition results in a

significantly larger increase, from ∼120 to 200ºC.

o For the 1%Al steel, the Tnr was further increased by 100-120ºC with 0.03%Nb addition.

However, the Tnr was almost unaffected by 0.03%Nb or 0.07%Nb addition to the 2%Al steel.

o Increasing the Si content from 1 to 2 wt% did not affect the recrystallisation regimes. Addition

of Nb to the Si steels significantly raised the RST thus reducing the width of the partial

recrystallisation regime.

WP4: Microstructure analysis

Task 4.1: Quantification of recrystallised fraction

o In the initial stages of softening, the recrystallised fraction in the Al steels measured

metallographically was lower than the softening determined mechanically, while at longer

interpass times the two values converged. However, due to the similar size of the initial and the

recrystallised grain sizes the results obtained could only be considered as an approximation.

o A new methodology for quantifying the recrystallised fraction has been developed and applied

at AM in this project based on the application of software developed for the reconstruction of

austenite microstructures from EBSD maps of martensitic structures and the use of a criterion

for distinguishing recrystallised and non-recrystallised grains based on the mean misorientation

angle in the reconstructed austenite grains.

o The first steps toward validation of this methodology for recrystallised fraction determination

have been made with encouraging results revealed by the comparison of the calculated values

with those of softening fraction derived from double hit torsion tests. Further work is required

to consolidate the application of this methodology including: increasing indexation rates in

original maps, increasing the number of maps and/or reconstructed grains for statistical

validation and further evolving the proposed criterion for identifying recrystallised grains.

Task 4.2: Quantification of austenite grain structure and distribution

o The austenite grain size was refined by deformation and recrystallisation in all the Mn1Nb

steels, the grain size being smaller for larger strains and lower temperatures. No strong effect

of Nb content on the recrystallised austenite grain size was observed.

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o A comparison of austenite grain size measurement techniques, including ASTM, MLI, image

analysis and EBSD, showed that there was good agreement between grain sizes measured on

reheated samples, but discrepancies between the techniques when applied to recrystallised

austenite grains.

o Thermodynamic calculations carried out with the Thermo-Calc software to investigate the

effect of Al on the microstructures of the steels indicated that Al is a strong ferrite stabiliser

element. 1%Al addition (C2Mn2Al1 steel) raises the Ae3 temperature from 780ºC to 900ºC,

while 2%Al addition results in a further increase of up to 1030ºC.

o The initial austenite grain sizes measured before the torsion tests on the Al steels were in the

56 to 104 µm range, and a slight grain refinement effect due to Al and Nb addition was

observed.

o In the 2%Al steels, a small amount of ferrite was present in the soaked specimens. As this was

less than 5% it was not considered to affect the softening behaviour of the steels investigated.

o For the 2%Al steels (C2Mn2Al2, C2Mn2Al2Nb3 and C2Mn2Al2Nb7), at temperatures below

1000ºC γ�α phase transformation was found to be concurrent with static softening increase,

leading to the high softening retardation observed for the 2%Al steels at the lowest

temperatures.

o The recrystallised microstructure was characterised in the cases in which the softening was not

affected by phase transformation. No significant effect of temperature on the recrystallised

grain size was observed, while decreasing the applied strain led in all cases to an increase in

the austenite grain size.

o In the 2%Al steels evidence of γ�α phase transformation was observed in the microstructures

of specimens interrupt quenched during multipass torsion tests at temperatures close to the Tnr.

The high Tnr increment observed for these steels was attributed to the onset of transformation.

Task 4.3: Quantification of precipitates

o Carbon extraction replicas showed that only in steel C2Mn2Al2Nb7 were a significant amount

of non-dissolved precipitates found after the soaking treatment before the torsion tests, in good

agreement with the predictions of solubility product equations in the literature.

o At 1000ºC very few precipitates were found in the martensite and the ferrite in steels

C2Mn2Al2Nb3 and C2Mn2Al2Nb7. At lower temperatures a significant number of strain-

induced precipitates were found both at the plateau onset and finish times. Precipitates were

found both in the ferrite and martensite phases, although they were coarser and more abundant

in the ferrite. The martensite precipitate size decreased significantly with decreasing the

deformation temperature.

o The C2Mn2Al1Nb3 steel also showed limited amount of strain-induced precipitation at

1000ºC. At lower temperatures, 900 and 925ºC, a significantly higher amount of Nb

precipitates were observed. Comparison with the C2Mn1Nb3 steel after deformation at 900

and 925ºC indicated that strain induced precipitation kinetics were slightly delayed in the Al

containing steel.

o To investigate the strain-induced precipitation evolution during the multipass torsion tests, the

precipitation state of AlNb steels quenched two passes below the Tnr was characterised. For the

C2Mn2Al2Nb3 steel and tip=100 s the precipitates found were scarce. For the C2Mn2Al2Nb7

steel and tip=30 s, a significantly larger amount of precipitates were found in the ferrite and

martensite phases, although their size, ∼100 nm in both cases, was relatively coarse. For the

C2Mn2Al1Nb3 steel and tip=30 s, a very small number of precipitates were found, suggesting

that solute drag could be the main mechanism leading to strain-accumulation in this case.

o The matrix dissolution technique was applied to analyse precipitates in torsion samples

quenched directly after deformation for steels C2Mn2Nb3 and C2Mn2Si2Nb3, C1Mn1Nb7 and

C1Mn2Nb7. It was found that increasing the Si content decreased the growth rate of the

precipitates.

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WP5: Modelling and construction of processing maps

Task 5.1: Assessment of current model capabilities

o The areas for improvement within the current models of the partners were assessed in the early

stages of the project.

o The main areas identified in the Tata model included the recrystallisation kinetics for CMn

steels, the recrystallisation kinetics at strains of 0.1 or below and the recrystallised austenite

grain size.

o The main areas identified in the CRM model, StripCam were inclusion of a Nb precipitation

model, and verification of the solid solution effect of Nb on the static recrystallisation kinetics.

o The CEIT model required the addition of the effect of Al on the static recrystallisation kinetics.

Task 5.2: Modelling of static recrystallisation kinetics

o Improvements have been made to the coefficients used in the Tata static recrystallisation

equations based on the experimental results from WP3. A weaker effect of strain and initial

austenite grain size on the time for 50% recrystallisation was found in the current results

compared with the existing equation, but the effect of strain rate was similar. The new t50

equation can be applied to both CMn and Nb microalloyed steels and extends to lower strain

deformations.

o The activation energy for recrystallisation was found to be a function of Nb content and

smaller than in the current model, but consistent with other published data. The Solute

Retardation Parameter (SRP) for Nb derived from the t50 data was in good agreement with

other published values.

o An average Avrami exponent n of 1.09 was obtained for the Nb steels, slightly higher than in

the current model.

o An equation for the recrystallisation start time has been determined, and found to be a function

of temperature, strain and Nb content. The behaviour is similar to published work, and shows

the importance of nucleation kinetics to the overall recrystallisation behaviour.

o The retarding effect of Al in solid solution on the static softening has been quantified in terms

of the SRP, excluding the cases in which γ�α or strain-induced precipitation took place. The

value obtained has been implemented in a semi-empirical equation developed in previous work

at CEIT for the prediction of the times for 50% softening (t0.5). The equation gives a good fit

for the C2Mn2 and all the Al and AlNb steels investigated.

o The relative Softening Retardation Parameters derived for Nb, Al and Si in the project were

consistent with previous results in the literature, with Nb>>Al>Si.

o A physical model has been applied to analyse the effect of Al in solid solution in the static

softening kinetics in those cases where recovery and recrystallisation softening mechanisms

take place. An expression for the grain boundary mobility of the C2Mn2 steel has been derived

and the effect of Al in solid solution on the recrystallisation kinetics quantified by means of the

Cahn model. The results suggest that Al affects the recovery kinetics as well as retarding

recrystallisation.

o The StripCam model has been improved by adding a criterion that defines the start of

precipitation (5% Nb precipitated) and thus the retardation of the static recrystallisation

kinetics. The t50 equation was modified to incorporate a temperature dependent effect of Nb in

solid solution, in the same way as the CEIT model, which significantly improved the

predictions of the model when compared against t50 measurements from the project partners.

Good agreement with the predictions of the CEIT model was also obtained. No effect of Si was

added to the equation as none was determined in the experimental work in Task 3.2.

Task 5.3: Modelling of dynamic recrystallisation kinetics

o The dynamic recrystallisation peak stress increased with decreasing temperature, increasing

strain rate and increasing Si content. The effect of strain rate on the saturation stress was

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slightly higher than in the existing StripCam equation. Increasing Nb content led to an increase

in the activation energy but increasing Si had the opposite effect.

o The influence of strain rate on the critical strain was found to be consistent with the StripCam

equation. Si addition was found to increase the critical strain for dynamic recrystallisation.

Task 5.4: Modelling of austenite grain size

o Improvements have been made to the coefficients used in the statically recrystallised austenite

grain size equation of Tata. A weaker dependence of recrystallised grain size on austenite grain

size and strain rate was found compared with the current model, but the effect of strain was

identical. No dependence of recrystallised grain size on deformation temperature was found,

unlike the current model but consistent with other models in the literature.

o Analysis of the grain growth data did not produce consistent results with which to improve the

grain growth equation. Exponents derived in previous Tata work have been applied and

produced reasonable predictions for the current data.

o The recrystallised austenite grain size in the Al steels has been compared with different models

found in the literature. A good fit was obtained with the equation proposed by Fernandez et. al.

for microalloyed steels.

Task 5.5: Modelling of recrystallisation-precipitation interactions

o The new Tata model predicted the correct trends in recrystallisation critical temperatures

(RLT, RST, Tnr) with strain and interpass time but the RLT was too low compared with the

temperature derived from torsion test results.

o Better prediction of the softened fraction derived from the torsion data, including partial

recrystallisation at all temperatures at 0.1 strain, was obtained by using the (higher) strain

exponent from the CEIT model in the t50 equation.

o Due to the occurrence of γ�α transformation after deformation in the 2wt% Al steels, only

the results for the C2Mn2Al1Nb3 and C2Mn1Nb3 steels were analysed to investigate the effect

of Al on the strain-induced precipitation kinetics.

o The replica analysis carried out suggested that strain-induced precipitation onset was retarded

for C2Mn2Al1Nb3 compared to the C2Mn1Nb3 steel. This could be due to the higher Al or

Mn content in the C2Mn2Al1Nb3, or to the absence of free N, which is expected to be pinned

in the form of AlN in this steel. Due to the limited data available this effect was not quantified.

Task 5.6: Construction of processing regime maps

o The recrystallisation critical temperatures (Tnr, RLT, RST and Ar3) obtained from the multipass

torsion tests were plotted in form of processing maps in order to compare the potential for

strain accumulation of the different steels.

o In steels C1Mn1Nb3 and C2Mn1Nb3, the increase in C from 0.1 to 0.2 wt% widened the

temperature range over which strain accumulation with no recrystallisation can occur.

o The calculated maps using the new Tata model showed a much wider range of temperatures at

which complete recrystallisation occurred and a narrower range for partial recrystallisation.

o Better prediction of the processing regimes derived from the torsion tests was obtained by

using the strain exponent from the CEIT model in the t50 equation.

o The processing maps indicated that strain accumulation potential was slightly increased by

1%Al addition to the C2Mn2 steel, and further enhanced by 0.03%Nb addition. The 2%Al

steels also showed a high potential for strain accumulation similar to that obtained for the

C2Mn2Al1Nb3 steel; however, due to the loss of ductility observed for these steels this is not

expected to be of practical applicability.

o Processing maps predicting the grain size and the accumulated strain have been constructed for

plate and strip rolling conditions using the CEIT model for different steel compositions.

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o In the plate rolling simulations, the results indicated that the final austenite grain size tended to

decrease with increasing the End Hold Temperature and thicker final gauges. This seems to be

related with the configuration of the hot rolling schedules. At EHT higher than 900ºC, the

finest final austenite grain sizes were obtained for the C2Mn2Al1Nb3 steel, while the

C2Mn2Al1 steel resulted in the coarsest microstructure. This is related to the strain

accumulation potential of the three steels.

o In the strip simulations, as the final gauge decreased finer grain sizes and higher accumulated

strain levels were obtained. This can be directly related to the larger strain applied in order to

obtain thinner final gauges. Finally, finer microstructures were obtained in the C1Mn1Nb7

steel rather than C1Mn1Nb3, as a result of the higher potential for strain accumulation due to

enhanced solute drag effect and strain-induced precipitation for the 0.07%Nb steel. The results

obtained for the C2Mn2Al1Nb3 and C1Mn1Nb7 steels were very similar.

WP6: Application and validation

Task 6.1: Design of validation tests

o Several sets of validation tests were defined:

o Multi-hit Gleeble uniaxial compression tests, to validate the recrystallisation kinetics

equations

o Multi-hit Gleeble uniaxial compression tests, quenched out after different passes or hold

times, to validate the recrystallised austenite grain size and grain growth equations

o Multi-pass torsion simulations of complete industrial plate and hot strip mill schedules,

to validate the fraction softened between passes

o Laboratory plate mill rolling trials, to validate the predicted processing regime maps for

recrystallised fraction and austenite grain size

o Pilot hot strip mill rolling trials, to validate the predicted processing regime maps for

recrystallised fraction and austenite grain size

Task 6.3: Multipass validation tests

o The fraction softened in the multi-hit Gleeble tests on a Nb microalloyed plate steel was

accurately predicted by the new Tata model for two different pass strains and interpass times

typical of plate rolling.

o The multi-hit austenite grain size Gleeble validation tests showed good agreement with the

predictions of the new Tata model at three temperatures and two applied strains.

o The multi-pass torsion simulations of industrial plate schedules indicated that complete

recrystallisation was not occurring during the roughing passes. The new Tata model produced

reasonable predictions of the fraction softened in these simulations, which were further

improved by using the strain exponent from the CEIT model in the t50 equation.

o Plate rolling torsion simulations were carried out with the C2Mn2Al1Nb3 and C2Mn2Al1

steels for End Hold Temperatures of 900 and 1000ºC and final gauges of 50 and 30mm. In

good agreement with the processing maps, refined microstructures were obtained for the

highest EHT simulations. For C2Mn2Al1Nb3, good agreement between the microstructural

measurements and the model predictions were obtained, whereas in the case of the C2Mn2Al1

steel the model tended to predict coarser grain sizes than the experimental results.

o Strip hot rolling torsion simulations were carried out with the C2Mn2Al1Nb3 steel, for the

same Finish Rolling Temperature, 900ºC, and two different gauges, 6 and 3 mm. The

predictions of the model showed very good agreement with the experimental grain size and

softening results.

Task 6.4: Pilot rolling trials

o Validation trials were performed on the Tata pilot plate rolling mill using industrial slab

material from a Nb microalloyed plate grade. Six plates were rolled using different rolling

schedules, with samples quenched out at intermediate and final passes to study the austenite

grain size evolution.

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o Good agreement was obtained between the measured and predicted austenite grain sizes in the

plates. The difference in austenite grain structure between plates rolled to 40mm with an end

hold temperature of 1000°C (recrystallised grains) and 950°C (pancaked grains) was correctly

predicted by the model.

o Validation trials were performed on the CRM pilot strip mill using a laboratory cast of steel

C2Mn2Al1Nb3. Four strips were rolled to different FRT and final gauges, with samples

quenched out 5s after the final pass for microstructure examination.

o Good agreement was obtained between the measured and predicted austenite grain sizes in the

strips. In the strip with the lowest FRT, ferrite was observed in the microstructures that could

not be predicted by the model.

Task 6.5: Validation against pilot mill and industrial mill data

o Comparison of measured laboratory and industrial plate mill loads with the predictions of a hot

rolling model incorporating the new recrystallisation equations showed that the model was

accurate during passes where complete or partial recrystallisation occurred, but predicted too

much strain accumulation once recrystallisation had stopped due to precipitation of Nb(C,N).

o The temperature range at which rolling forces started to increase due to strain accumulation

was successfully predicted using StripCam for the pilot strip mill validation trials.

2.5 Exploitation and impact of the research results

2.5.1 Application of the project results

The improved model developed by Tata Steel within this project will be incorporated into hot rolling

models used for offline simulation of the Tata plate mills, to predict the microstructure evolution and

final mechanical properties. The models are applied when designing new or modified steel chemistries

and rolling schedules before any trials are carried out. They are also used in an advisory capacity

before taking on commercial orders outside of mainstream production. ArcelorMittal will utilise their

models for product development of hot rolled strip grades. CRM and CEIT will apply their models both

for their own research activities and in collaborations with steel production partners.

The common formulation of the recrystallisation equations used in the Tata, CRM and CEIT models,

and indeed many other models presented in the literature, means that the new parameters, such as for

the effect of Al, can be incorporated into each model relatively easily. A number of publications have

already been presented at conferences and in journals and more are planned after the completion of the

project. This will transfer some of the knowledge developed within the project to a wider audience

within the steel and metallurgical community.

2.5.2 List of publications and conference presentations

• Z. Aretxabaleta, B. Pereda, S.V. Parker, B. López, "Static Softening Behaviour in High

Aluminum Steels", Procs. of the International Conference on Processing and Manufacturing of

Advanced Materials, Thermec’2011, August 1-5, 2011, Quebec, Canada. Published in

Materials Science Forum, Vols. 706-709, (2012), 2764-2769.

• Z. Aretxabaleta, B. Pereda, S.V. Parker, B. López, "Influence of Nb on the Critical

Temperatures during Multipass Deformation of High Al Steels", 4th International Conference

in Thermomechanical Processing of Steels, TMP2012, 10-12 September 2012, Sheffield, UK.

• Z. Aretxabaleta, B. Pereda, B. López, "Cinéticas de ablandamiento de aceros con alto

contenido en Al", XII Congreso Nacional de Materiales, Alicante, 30 Mayo – 1 Junio, 2012.

• Z. Aretxabaleta, B. Pereda, S.V. Parker, B. López, “Softening Kinetics in High Al-Nb

Microalloyed Steels”, The 7th International Conference on Physical and Numerical Simulation

of Materials Processing, Oulu, Finland, June 2013, accepted for publication.

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3. List of Figures

Figure 1: Project work packages and interactions Figure 2: Programme Gantt chart indicating project progress (shaded cells) against original plan (black) Figure 3: Schematic diagram of the thermomechanical treatments applied in the Gleeble static

recrystallisation tests. Figure 4: Initial austenite grain size tests at CRM Figure 5: Interrupted torsion test technique - Double hit tests Figure 6: Thermal cycle for the initial microstructure characterisation at CEIT Figure 7: Thermomechanical cycle applied in the double-hit torsion tests at CEIT Figure 8: Single hit hot torsion test for DRX study Figure 9: Single hit hot torsion test for Nb precipitation analysis at CRM Figure 10: Multi-pass deformation test to determine critical temperatures Figure 11: Thermomechanical cycle applied in the multipass deformation tests. Figure 12: Schematic illustration of method for analysing stress relaxation curves (after [3,4]). Figure 13: Stress relaxation curves for Tata steels deformed at 1050°C showing effect of strain Figure 14: Avrami recrystallisation curves for Tata steels deformed at 1050°C showing effect of strain Figure 15: “Normalised” softening curves for Tata steels deformed at 1050°C showing effect of strain Figure 16: Avrami recrystallisation curves for Tata steels deformed at 1150°C showing effect of strain Figure 17: “Normalised” softening curves for Tata steels deformed at 1150°C showing effect of strain Figure 18: “Normalised” softening curves for Tata steels deformed at 950°C showing effect of strain Figure 19: Avrami recrystallisation curves for Tata steels deformed at fixed strain showing effect of

temperature Figure 20: Avrami recrystallisation curves for Tata steels deformed at 1050°C showing effect of Nb

content and strain Figure 21: “Normalised” softening curves for Tata steels deformed by 0.35 and 0.1 strain at three

temperatures, strain rate 1/s, 100µm initial austenite grain size. Figure 22: “Normalised” softening curves for Tata steels deformed by 0.35 and 0.1 strain at 1050°C

and 950°C, indicating effect of solute drag and precipitation. Figure 23: Avrami recrystallisation curves for Tata steels deformed 0.2 strain at 1050°C, strain rate 1/s,

effect of different initial austenite grain sizes. Figure 24: Avrami recrystallisation curves for Tata steels deformed 0.2 strain at 1050°C, effect of

strain rate Figure 25: Avrami recrystallisation curves for Tata steels deformed 0.2 strain at 1050°C, showing

effect of Nb content at different strain rates Figure 26: Flow curves for Tata steels deformed 0.2 strain at 1050°C, effect of strain rate Figure 27: Definition of the stresses used in the 2% offset method for the determination of the

fractional softening. Figure 28: Round robin test results on steel C2Mn1Nb3 deformed to 0.35 strain at 1050°C using Tata

Gleeble in uniaxial compression. Figure 29: C2Mn2Si1 steel grade - Stress-Strain curves - variation of inter-pass time (IPT) Figure 30: Comparison of fractional softening between back extrapolation and 2% offset method Figure 31: Deformation temperature effect on measured SRX kinetics in Si steels Figure 32: Effect of silicon/niobium on measured SRX kinetics Figure 33: Deformation intensity effect on measured SRX kinetics Figure 34: Effect of Si on static recrystallisation kinetics Figure 35: Effect of Si on t50 and normalised t50 Figure 36: Stress-strain curves obtained for the C2Mn2Al1 steel deformed at 925ºC at different

interpass times. Figure 37: Fractional softening obtained for the Al steels at different deformation temperatures. Figure 38: Fractional softening obtained for the Al steels after applying different strains. Figure 39: Fractional softening obtained for the C2Mn2, C2Mn2Al1 and C2Mn2Al2 steels at different

temperatures Figure 40: Softening curves for C1Mn2 Figure 41: Softening curves for C1Mn2Nb3 Figure 42: Softening curves for C1Mn1Nb7

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Figure 43: Softening curves for C1Mn2Nb7 Figure 44: Sample Dimensions and Temperature control for torsion tests at AM, CEIT and CRM

Figure 45: Comparative Flow curves AM and CEIT for C1Mn1Nb7 – 1050°C – ε=0.35 – ε=1/s Figure 46: Evolution of stress and strain rate with strain for AM tests (tip=1s) Figure 47: Stress evolution comparison of experimental and model predicted results

Figure 48: Comparative Flow curves AM/CEIT and CRM for C1Mn1Nb7 – 1050°C – ε=0.35 – ε=1/s

Figure 49: Softening curves for C1Mn1Nb7 – 1050°C – ε=0.35 – ε=1/s – Comparative Results by

Torsion AM and Torsion CEIT

Figure 50: Softening curves for C1Mn1Nb7 – 1050°C – ε=0.35 – ε=1/s – Comparative Results by

Torsion AM, Torsion CEIT, Torsion CRM Figure 51: Comparison of softening curves for CMn steels C15Mn2 and C1Mn2 from NSC and AM

(T=850°C, ε=0.5) Figure 52: Overall results of softening kinetics from round robin exercise on steel C2Mn1Nb3 Figure 53: DRX study - analysis of flow stress experimental curves Figure 54: Effect of temperature and strain rate on peak stress for DRX in Si steels Figure 55: Flow curves describing DRX behavior for Nb7 steels Figure 56: Determination of critical stress and strain for DRX Figure 57: Relationship between critical and peak strain (n=0.856)

Figure 58: Evolution of εp values with Zener-Hollomon parameter for C1Mn1Nb7 and C1Mn2Nb7 Figure 59: Stress strain curves - Multipass hot torsion test on C2Mn2Si2Nb3 steel Figure 60: Fractional softening experimental data obtained for the Al steels at different deformation

temperatures. Figure 61: Fractional softening obtained for the AlNb steels at different temperatures. Figure 62: Multipass torsion test results on C2Mn2Al2Nb3 steel, tip=100 s, ε per pass=0.3. Figure 63: Mean flow stress plots from multipass torsion tests on steels C1Mn1Nb3 and C2Mn1Nb3 Figure 64: Fractional softening plots from multipass torsion tests on steels C1Mn1Nb3 and C2Mn1Nb3 Figure 65: Fractional softening plots from multipass torsion tests on CRM Si steels . Figure 66: Mean Flow Stress (MFS) plotted against temperature at different interpass times for the

C2Mn2, C2Mn2Al and C2Mn2AlNb steels. Figure 67: Mean Flow Stress (MFS) plotted against temperature at the same Figure 68: Anisothermal fractional softening plotted against temperature for the C2Mn2, C2Mn2Al and

C2Mn2AlNb steels at different interpass times. Figure 69: Anisothermal fractional softening plotted against temperature for the different Al steels at

the same deformation conditions. Figure 70: Tnr and Ar3 temperatures obtained for the different steels. Figure 71: Section of torsion specimen for metallographic study. Sub-surface section (0.9R), where R

is the radius of the specimen.

Figure 72: Softening curve determined for the C2Mn2Al1 steel deformed at TDEF=1065ºC, ε=0.35. The

times at which quenching treatments were performed are also indicated. Figure 73: Microstructures obtained for the C2Mn2Al1 steel in the soaked condition (a) and after

deformation at 1065ºC and holding for different times. The recrystallised fraction determined by

quantitative metallography is also indicated. Figure 74: Mechanical fractional softening data together with the metallographic measurements of

recrystallised fraction. C2Mn2Al1, TDEF=1065ºC, ε=0.35. Figure 75: Chemical Etching revealing austenite grain boundaries from quenched torsion samples Figure 76: Comparison of Optical Micrographs and EBSD reconstructed maps for C1Mn2Nb3 –

1100°C – ε 0.35 Figure 77: Application of Mean Local Misorientation Criterion for estimating recrystallised fraction in

C1Mn2Nb3 – 1100°C – ε 0.35 Figure 78: Comparison of Softening results by DH test with Recrystallization results derived from

EBSD Reconstruction using mean misorientation angle criterion for C1Mn2Nb3 – 1100°C – ε 0.35

Figure 79: Maps for determining XReX on C1Mn2Nb3 – 1050°C – ε 0.35 – D°127µm Figure 80: Application of Mean Local Misorientation Criterion for estimating recrystallised fraction in

C1Mn2Nb3 – 1050°C – ε 0.35

Figure 81: Reconstructed maps for C1Mn2Nb3– 950°C – ε 0.35 – D°128µm and calculated XReX

202

Figure 82: Comparison of softening results by DH test with XReX results derived from EBSD

Reconstruction using adjusted mean misorientation angle criterion for C1Mn2Nb3 – ε 0.35 deformed at

1050 and 950°C Figure 83: Calculated plastic equivalent strain distributions in Gleeble uniaxial compression samples

for 6 different applied strains, using Finite Element modelling Figure 84: Effect of strain and strain rate on statically recrystallised austenite grain size at three

deformation temperatures Figure 85: Example micrographs of Nb steel samples quenched to measure initial austenite grain size Figure 86: Example micrographs of Nb steel samples quenched to measure recrystallised austenite

grain size Figure 87: Measured austenite grain size as a function of holding time, temperature and strain Figure 88: Steel C1Mn1, reheated at 1200°C for 15 minutes Figure 89: Histograms of ECD initial austenite grain size distribution and cumulative frequency for

C1Mn1 steel (a) before and (b) after deformation tests. Figure 90: Thermal path GS1 - Large austenite grain size Figure 91: Thermal path GS2 Figure 92: Initial austenite grain size – Si steel grades Figure 93: Equilibrium ferrite and austenite mole fraction calculated by Thermo-Calc for the C2Mn2,

C2Mn2Al1 and C2Mn2Al2 steels as a function of temperature (TCFE6 database). Figure 94: Phase diagrams calculated by the Thermo-Calc software for the Al steels (TCFE6 database).

The AlN phase is not plotted for simplicity. Figure 95: Microstructure of the different Al steels after soaking at 1250ºC. Figure 96: Micrographs obtained for the C2Mn2Al2 steel at different temperatures and holding times. Figure 97: Micrographs obtained for the C2Mn2Al2Nb3 steel deformed at 925ºC and water quenched

after a holding time of 672 s. Figure 98: Recrystallised microstructures obtained for the different steels after deformation at 1065ºC,

ε=0.35. Figure 99: Micrographs obtained for the C2Mn2Al2Nb steels quenched two passes below the Tnr. Figure 100: Micrographs obtained for the C2Mn2Al2 and C2Mn2Al2Nb3 steels quenched at the Ar3 . Figure 101: Initial Grain Sizes for C1Mn2 and C1Mn2Nb3 Figure 102: Initial grain size distribution in terms of Linear Intercept for C1Mn2 and C1Mn2Nb3 Figure 103: Initial Grain Sizes for C1Mn2Nb7 and C1Mn2Nb7 Figure 104: Initial grain size distribution in terms of Linear Intercept for C1Mn1Nb7 and C1Mn2Nb7 Figure 105: Comparison of grain size measurements from Optical Micrographs and EBSD

reconstructions in C1Mn2Nb3 – 1100°C – ε 0.35 Figure 106: EBSD reconstructed maps, mean recrystallised grain size in terms of area based average

and recrystallised grain size distribution in terms of Area Based Probability for C1Mn2Nb3 – ε 0.35 Figure 107: Precipitation kinetics of C2Mn2Nb3 and C2Mn2Si2Nb3 steels after a deformation of 0.2

applied at 1000°C Figure 108: Coarse Nb precipitates, EDS analysis and precipitate size distribution measured from the

C2Mn2Al2Nb7 specimen quenched after soaking at 1250ºC. Figure 109: Quenching treatments carried out in order to study the NbC strain-induced precipitation

during softening for the C2Mn2Al2Nb steels. Figure 110: Examples of precipitates from specimens quenched after deformation at 1000ºC, t=576s,

for C2Mn2Al2Nb steels Figure 111: Precipitates found in the C2Mn2Al2Nb martensite regions after deformation at 965ºC Figure 112: Precipitates found in the C2Mn2Al2Nb martensite and ferrite regions after deformation at

925ºC at the time for the plateau onset (t=672s). Figure 113: Example of precipitates in ferrite, extracted from the C2Mn2Al2Nb3 and C2Mn2Al2Nb7

steels after deformation at 925ºC and a holding time of 5760 s. Figure 114: Precipitate average sizes measured in martensite for all the quenched AlNb steel

specimens. Figure 115: Softening curves and quenching treatments for C2Mn2Al1Nb3 and C2Mn1Nb3 steels Figure 116: Precipitation state evolution for the C2Mn2Al1Nb3 steel at 925ºC. Figure 117: Precipitation state evolution for the C2Mn1Nb3 steel at 925ºC.

203

Figure 118: Precipitation state evolution for the C2Mn2Al1Nb3 and C2Mn1Nb3 steels after

deformation at 900ºC. Figure 119: Measured versus calculated results for static recrystallisation tests using original Tata

model Figure 120: Logarithmic plot of measured t50 against strain for a strain rate of 1/s, 100µm initial grain

size Figure 121: Logarithmic plot of t50 against strain rate for strain of 0.2, 100µm initial austenite grain

size and 1050°C temperature Figure 122: Logarithmic plot of t50 against initial austenite grain size for strain rate of 1/s, 0.2 strain

and temperature 1050°C. Figure 123: Logarithmic plot of t50 against inverse temperature for strain of 0.2, 100µm initial austenite

grain size and strain rate 1/s

Figure 124: Normalised τ0.5 determined for the Nb steels at three strains Figure 125: Avrami n-values determined from measured recrystallisation curves Figure 126: Measured versus calculated times for 50% and 95% static recrystallisation in static

recrystallisation tests using new Tata model Figure 127: Measured versus calculated times for 50% static recrystallisation using critical strain

adjustment in new Tata model Figure 128: Solubility product predicted with Palmiere and Choquet equations Figure 129: “A” coefficient using Choquet solubility product Figure 130: “B” coefficient using Choquet solubility product Figure 131: Calculated StripCam SRX kinetics, comparing original (dashed lines) and new models

(solid lines) Figure 132: Comparison between new and old StripCam model and experimental t50 values for Si steels Figure 133: Comparison between model and experimental results for t50% SRX Figure 134: Optimisation of Qss

x parameter for different steel grades

Figure 135: Retardation effect on normalised t50 due to the presence of Nb in Si steels Figure 136: New Nb effect in CRM model considering a Nb correction from experimental t0.5SRX data Figure 137: Detailed comparison between calculated and experimental t0.5SRX using new StripCam

model Figure 138: Effect of deformation on t0.5SRX for Si steels Figure 139: Normalised t0.5 calculated using equation (27) for the different steels. Figure 140: Comparison of experimental t0.5 and the t0.5 values given by equation (28) for the steels

investigated. Figure 141: Comparison between t0.5 experimental data and predictions of equation (30). Figure 142: (a) Comparison between the model predictions and experimental softening data and (b)

softening and recrystallisation model predictions for the C2Mn2 steel at 925 and 1065ºC. Figure 143: Comparison between the experimental softening/recrystallisation data and the model

(D=7Dbulk) predictions at different temperatures and strains for the C2Mn2Al steels Figure 144: Comparison between the experimental softening data and the predictions of the modified

model (D=5Dbulk, K2 = 1x10-8) at different deformation conditions for the C2Mn1Al steels Figure 145: Example Fraction Softened plot versus Log Time Figure 146: Recovery curves fitted to low strain test results Figure 147: Example plot of Relaxation Stress versus Log Time Figure 148: Example plots of Fraction Softening Plots for C1Mn1Nb1 Steel including Fitted Creep and

Recovery Lines Figure 149: Determination of Recrystallisation Start Times for C1Mn1 Steel Figure 150: Recrystallisation Start Times, t0, as a function of Strain for each Temperature Figure 151: Recrystallisation Start Time Ratio and Solute Retardation Parameter as a function of Nb

content Figure 152: Comparing Relative Recrystallisation Start Times with the results from Yamamoto [69] Figure 153: Influence of strain rate and temperature on peak stress Figure 154: "n" exponent of ZH parameter Figure 155: “A” coefficient of ZH parameter Figure 156: Activation energy and strain rate exponent of saturation stress for Si steels Figure 157: Nb effect on activation energy of saturation stress of Si steels

204

Figure 158: Strain rate exponent of critical strain equation for Si steels Figure 159: Logarithmic plot of drex against strain for strain rate of 1/s, ~100µm austenite grain size Figure 160: Logarithmic plot of drex against strain rate for constant strain of 0.2, ~100µm austenite

grain size and temperature Figure 161: Logarithmic plot of drex against initial grain size for strain rate of 1/s, 0.2 strain and 1050°C

deformation temperature Figure 162: Logarithmic plot of drex against initial grain size for strain rate of 1/s, 0.2 strain and 1050°C

deformation temperature including additional Tata data Figure 163: Logarithmic plot of drex against inverse temperature for constant strain, strain rate of 1/s,

~100µm austenite grain size Figure 164: Comparison between measured and predicted statically recrystallised austenite grain size,

all data, using original and new equations. Figure 165: Comparison between original and new Tata recrystallised austenite grain size equations

and experimental data Figure 166: Recrystallised grain sizes obtained for the project steels. Figure 167: Predictions of equations found in the bibliography for calculating the statically

recrystallised grain size plotted against the experimental data obtained in this work. Figure 168: Measured and predicted austenite grain size after grain growth as a function of holding

time, temperature and strain Figure 169: Analysis of austenite grain growth data as a function of holding time, m = 4.5 Figure 170: Measured and predicted austenite grain size after grain growth as a function of holding

time, temperature and strain using new values of m. Figure 171: Measured and predicted fractional softening for multipass torsion tests using Tata model Figure 172: Measured softening curves and precipitate sizes for C2Mn1Nb3 and C2Mn2Al1Nb3 steels. Figure 173: (a) Nb precipitated (%) measured for the C2Mn2Al1Nb3 by electrolytic dissolution and

ICP and (b) precipitate volume fraction evolution normalised by the equilibrium precipitate volume

fraction. Figure 174: Strain-induced precipitation start times determined experimentally by chemical extraction

and estimated from the softening curves plateaux and CEIT model predictions for both conditions. Figure 175: Processing regime maps derived from multipass torsion tests on C1Mn1Nb3 and

C2Mn1Nb3 steels. Figure 176: Processing regime maps calculated using Tata model, corresponding to multipass torsion

tests Figure 177: Processing regime maps – Si steel grades without niobium Figure 178: Processing regime maps – Si steel grades with niobium

Figure 179: Plots representing the different recrystallisation, strain accumulation and γ�α phase

transformation regimes for the Al steels as a function of interpass time. Figure 180: Grain size and strain accumulated after the lass past processing maps obtained employing

the CEIT model for the plate hot rolling simulations. Figure 181: Final austenite grain size, accumulated strain and recrystallised fraction processing maps

obtained employing the CEIT model for strip hot rolling simulations. Figure 182: Example industrial plate rolling schedules used for validation torsion tests Figure 183: Processing regime maps for laboratory plate rolling mill at Tata Steel, using a 0.11C

0.034Nb steel, calculated using the Tata metallurgical model showing target validation trials. Figure 184: Recrystallised fractions and austenite grain sizes for laboratory plate rolling schedules,

using a 0.11C 0.034Nb steel and two end hold temperatures, calculated using Tata metallurgical model Figure 185: Processing Maps for C2Mn2Al1Nb3 under selected conditions of laboratory hot rolling

derived from application of CEIT predictive model Figure 186: Measured flow stress curves from multi-hit validation tests on steel 6AM2 Figure 187: Mean flow stress versus inverse temperature plots to determine Tnr from multi-hit tests on

steel 6AM2 Figure 188: Measured and predicted fraction softened as a function of temperature for multi-hit

validation tests on steel 6AM2 Figure 189: Normalised fraction softened plots for multi-hit validation tests on steel 6AM2 Figure 190: Measured and predicted austenite grain size for multi-hit validation tests on industrial steel

205

Figure 191: Measured and predicted fractional softening for multipass torsion tests based on industrial

plate rolling schedules Figure 192: Stress-strain curves obtained in the plate rolling torsion simulations Figure 193: Anisothermal experimental softening results and CEIT model predictions for the plate

rolling simulations. Figure 194: Microstructures obtained after the plate rolling torsion simulations carried out with the

C2Mn2Al1Nb3 and C2Mn2Al1 steels. Figure 195: Grain size predictions obtained for the C2Mn2Al1 steel (1000ºC-50 mm plate schedule)

and experimental measurements. Figure 196: Stress-strain curves obtained in the strip rolling simulations carried out with the C2Al1Nb3

steel. Figure 197: Anisothermal experimental softening results and CEIT model predictions for the strip

rolling simulations. Figure 198: Final austenite microstructures obtained after strip rolling simulations on C2Mn2Al1Nb3. Figure 199: Tata laboratory plate mill rolling schedules for two End Hold Temperatures. Arrows

indicate passes at which samples were quenched for microstructural examination. Figure 200: Optical micrographs of Tata laboratory validation plate samples after quenching Figure 201: Austenitic microstructure of grade C2Mn2Al1Nb3 after last validation rolling pass Figure 202: Measured and predicted mill stand loads for Tata pilot plate rolling trials Figure 203: Applied strain and calculated total accumulated strain per pass for Tata pilot plate rolling

trials Figure 204: Measured and predicted mill stand forces for typical industrial plate mill rolling schedules Figure 205: Evolution of material mean flow stress during pilot rolling trials

206

4. List of Tables

Table 1: Nominal compositions of project steels (wt%) Table 2: Allocation of steels studied between the project partners Table 3: Measured cast compositions of project steels (wt%) Table 4: Parameters for initial thermomechanical tests performed by all partners Table 5: Austenitising conditions and corresponding measured austenite grain sizes in Tata steels. Table 6: Matrix of static recrystallisation test conditions for Tata steels Table 7: Test programme - SRX study at CRM

Table 8: Deformation conditions employed in the double-hit torsion tests on Al steels ( 11 −= sε& ). Table 9: Quenching treatments carried out for microstructural analysis and strain-induced precipitation

study on Al steels. Table 10: Double-hit torsion tests and quenching treatments carried out on C2Mn1Nb3 to study the

effect of Al on strain-induced precipitation. Table 11: Selected Conditions for Thermomechanical Testing Table 12: Initial austenite grain size measurements (Mean Linear Intercept) for MnNb steels Table 13: Matrix of tests - DRX study at CRM Table 14: Matrix of tests - Critical recrystallisation temperatures of Si steels

Table 15: Deformation conditions employed in the multipass torsion tests ( 11 −= sε& ). Table 16: Quenching treatments carried out in order to investigate the microstructural evolution of the

steels investigated during the multipass torsion tests. Table 17: t50 and n values determined from fitting Avrami curves to softened fraction data: effect of

strain and temperature at strain rate of 1/s and 100µm initial austenite grain size Table 18: t50 and n values determined from fitting Avrami curves to softened fraction data: effect of

strain rate at 0.2 strain, 1050°C and 100µm initial austenite grain size. Table 19: Avrami exponent and t50 - Fitting of KJMA model to Si steels Table 20: Softening parameters for C1Mn2 Table 21: Softening parameters for C1Mn2Nb3 Table 22: Softening parameters for C1Mn1Nb7 Table 23: Softening parameters for C1Mn2Nb7 Table 24: Calculation of softening fraction using 2% offset Method – Comparison AM/CEIT Table 25: Calculation of softening fraction using 2% Offset Method – Comparison CRM Table 26: Softening parameters for C1Mn1Nb7 as obtained by AM, CEIT and CRM Table 27: Softening parameters for CMn steels by AM and NSC derived from torsion testing Table 28: Initial austenite grain size in steel C2Mn1Nb3 measured at each partner Table 29: Avrami n-values and t50 times derived from all round robin tests at each partner Table 30: Results - DRX study on Si steels Table 31: Critical Parameters for Dynamic Recrystallisation for C1Mn1Nb7 and C1Mn2Nb7 Table 32: Grain growth tests performed on steels C1Mn1, C1Mn1Nb1 and C1Mn1Nb3 Table 33: Torsion Single Hit tests performed for precipitation studies on MnNb steels Table 34: Critical temperatures from multipass torsion tests on steels C1Mn1Nb3 and C2Mn1Nb3 Table 35: Critical recrystallisation temperatures determined from multipass torsion tests on Si steels Table 36: Critical temperatures determined from the multipass torsion tests carried out on Al steels Table 37: Measured austenite grain sizes after static recrystallisation tests from an initial austenite

grain size of ~100µm. Grey cells indicate tests where recovery/partial recrystallisation occurred. Table 38: Comparison of grain size measurement techniques Table 39: Initial austenite grain sizes in Si steels Table 40: Mean equivalent diameters and ferrite volume fractions determined for the studied steels at

different conditions.

Table 41: Ferrite fraction (fα) and fractional softening measured at different conditions for the

C2Mn2Al2 steels. Table 42: Recrystallised grain sizes measured for the different Al steels.

Table 43: Precipitate mean sizes (Dmean) and ferrite volume fractions (fα) at different deformation

temperatures for the C2Mn2Al2Nb steels.

207

Table 44: Precipitate mean sizes (Dmean) and amount of Nb precipitated in the C2Mn1Nb3 and

C2Mn2Al1Nb3 steels. Table 45: Torsion Single Hit tests performed for precipitation studies Table 46: Main equations for recrystallisation and precipitation kinetics Table 47: Calculated dissolution temperatures (°C) of Nb(C,N) precipitates in project steels Table 48: Summary of new coefficents for t50 equation in Tata model Table 49: Average SRP values calculated at each temperature for the Nb steels Table 50: Time for 50% fractional softening (t0.5) and Avrami n exponents determined from the

softening curves of the Al steels. Table 51. SRP values for the Al steels calculated following equation (29). Table 52: Calculated grain boundary mobilities for the C2Mn2 steel and the ratio between mobility for

a pure material calculated by equation (41) and these values. Table 53: Al bulk diffusion coefficient and atomic radius data employed. Table 54: Stress Relaxation Parameters in Creep Regime Table 55: t0 Ratio of Steels Relative to C1Mn1 and corresponding Table 56: Coefficients used to describe peak stress as a function of ZH parameter in Si steels Table 57: Summary of new coefficents for drex equation in Tata model Table 58: Summary of coefficents for grain growth equation (60) [8] Table 59: Reference Industrial Hot Rolling Schedule for Processing Regime Maps in Strip Rolling Table 60: Conditions for multi-hit Gleeble validation tests on steel 6AM2 Table 61: Tests carried out in order to simulate plate and strip hot rolling schedules. Table 62: Pilot Strip Hot Rolling Schedules for validating Processing Regime Maps Table 63: Matrix of grain size validation tests performed on plate steel 6AM2 Table 64: Comparison of the experimental grain size measurements and the predictions of the CEIT

model for the plate rolling torsion simulations. Table 65: Comparison of the experimental grain size measurements and the predictions of the CEIT

model for the strip rolling simulations carried out. Table 66: Comparison of the values of Sv determined from experimental grain size measurements and

the predictions of the CEIT model for the plate rolling torsion simulations. Table 67: Summary of validation laboratory plate rolling trials at Tata Steel on slab 6AM2 Table 68: Estimated prior austenite grain sizes in laboratory validation plates Table 69: Discontinuous pilot rolling conditions – Strip validation trials Table 70: Summary of predicted values from processing regime maps according to pilot strip rolling

validation conditions

208

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210

82. M.Caruso, B.Pohu, A.Schmitz, S.Godet, Proceedings of “TMP2012: 4th International

Conference on Thermomechanical Processing of Steels”, Sheffield, UK, IOM Comms. Ltd.,

10-12th September 2012

6. List of acronyms and abbreviations

Ar1 Austenite-ferrite transformation finish temperature

Ar3 Austenite-ferrite transformation start temperature

DH Double hit

DRX Dynamic recrystallisation

EBSD Electron BackScattered Diffraction

EHT End Hold Temperature

FRT Finish Rolling Temperature

MFS Mean flow stress

RLT Recrystallisation limit temperature

RST Recrystallisation stop temperature

SH Single hit

SRX Static recrystallisation

t50 Time for 50% recrystallisation

t95 Time for 95% recrystallisation

TEM Transmission electron microscope

Tnr Temperature of no recrystallisation

211

European Commission EUR 26212 — Development of microstructure-based tools for alloy and rolling process design

(Microtools) Luxembourg: Publications Office of the European Union 2013 — 211 pp. — 21 × 29.7 cm ISBN 978-92-79-33613-3doi:10.2777/4415

213

EUROPEAN COMMISSION Directorate-General for Research and Innovation Directorate G — Industrial Technologies Unit G.5 — Research Fund for Coal and Steel

E-mail: rtd-steel-coal@ec.europa.eu RTD-PUBLICATIONS@ec.europa.eu

Contact: RFCS Publications

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Development ofmicrostructure-based tools for alloy

and rolling process design

(Microtools)

doi:10.2777/4415

Developm

ent of microstructure-based tools for alloy and rolling process design (M

icrotools)EU

EUR 26212

KI-NA-26212-EN

-N

Project Microtools developed tools to construct processing regime maps combining temperature-time-deformation history with enhanced knowledge of the metallurgical mechanisms during hot rolling, to design improved rolling schedules and chemistries. The dependence of the austenite recrystallisation and precipitation kinetics on the elements Mn, Si, Al and Nb at levels relevant to plate and advanced high strength strip steels was studied using thermomechanical testing and detailed metallography and integrated into equations for use in hot rolling models. The softening retardation potential of the alloying elements investigated was found to decrease in the order Nb>>Al>Si. A new methodology for quantifying the recrystallised austenite fraction using EBSD maps and austenite grain reconstruction software was developed. Processing regime maps were constructed for representative plate and hot rolled strip rolling schedules from which pilot rolling trials were designed and performed to successfully validate the new models.

Studies and reports

Research and Innovation EUR 26212 EN