HYDRODYNAMIC STUDIES ON TWO PHASE INVERSE FLUIDIZATION USING NON NEWTONIAN FLUID

HYDRODYNAMIC STUDIES ON TWO PHASE INVERSE FLUIDIZATION USING NON NEWTONIAN FLUID

This report has been submitted as a part of requirement for the fulfillment

of B.Tech in Chemical Engineering of West Bengal University of Technology

By

Atanu Kumar Paul - 071550106047Ravi Shankar Mukherjee - 071550106049

Souvik Nandy - 071550106051Swarnav Mitra - 071550106031

Tapas Sen - 071550106026Trishagni Sen - 071550106040

Under The Guidance Of

Dr. Bimal DasAssistant Professor, Department of Chemical

Engineering.

DEPARTMENT OF CHEMICAL ENGINEERING

DURGAPUR INSTITUTE OF ADVANCEDTECHNOLOGY & MANAGEMENT

RAJBANDH, DURGAPUR-12.

WEST BENGAL UNIVERSITY OF TECHNOLOGY.

Certificate from the Head of the Department

This is to certify that the following students -

Atanu Kumar Paul CH/07/56

Ravi Shankar Mukherjee CH/07/02

Souvik Nandy CH/07/05

Swarnav Mitra CH/07/21

Tapas Sen CH/07/52

Trishagni Sen CH/07/32

of B. Tech., 4th year (2011), in the department of Chemical Engineering from

Durgapur Institute of Advanced Technology & Management, Durgapur, West

Bengal, have successfully completed their project work allotted to them in

stipulated time.

It is hereby approved that the project done by them is a creditable study

carried out with all the details and precisions for the fulfillment of the purpose.

I wish them all the success in future.

______________________

Dr. Ananta Kumar Das

Head of the DepartmentChemical Engineering DepartmentTel: +919433828272Email: [email protected]


G.T. ROAD, RAJBANDHDUGRAPUR-713212Tel: 0343-2520712/713Website: www.diatm.rahul.ac.in

Place : Durgapur

Date :

Certificate from the Project Supervisor

This is to certify that the following students –

Atanu Kumar Paul CH/07/56

Ravi Shankar Mukherjee CH/07/02

Souvik Nandy CH/07/05

Swarnav Mitra CH/07/21

Tapas Sen CH/07/52

Trishagni Sen CH/07/32

of B. Tech., 4th year (2011), in the department of Chemical Engineering from

Durgapur Institute of Advanced Technology & Management, Durgapur, West

Bengal, have successfully completed their project work allotted to them in

stipulated time.

It is hereby approved that the project done by them is a creditable study

carried out with all the details and precisions for the fulfillment of the purpose.

I wish them all the success in future.

_____________________

Dr. Bimal Das

Assistant ProfessorChemical Engineering DepartmentTel: +919007977912Email: [email protected]


G.T. ROAD, RAJBANDHDUGRAPUR-713212Tel: 0343-2520712/713Website: www.diatm.rahul.ac.in

Place : Durgapur

Date :

ACKNOWLEDGEMENT

We take great pleasure in submitting our final year project report on

“HYDRODYNAMIC STUDIES ON TWO PHASE INVERSE FLUIDIZATION

USING NON NEWTONIAN FLUID”.

It was an immense pleasure doing the project work which helped us to learn new

things, & improve our technical skill. This work would not have been possible without

the help of many people. We would like to take this opportunity to express our deep

appreciation to all those who helped us.

It is our proud privilege to epitomize our deepest sense of gratitude & ineptness to our

project supervisor Dr. Bimal Das, Assistant Professor, Department of Chemical

Engineering, DIATM for his valuable guidance, keen & sustained interest, intuitive ideas

& persistent endeavour. His inspiring assistance enabled us to complete our work

smoothly & successfully.

We would also like to extend our sincere gratitude to Dr. Ananta Kumar Das,

Head of the Chemical Engineering Department for granting us the opportunity to

complete this project work on such an innovative topic and for his immense guidance and

support.

Special thanks go to all the Faculty Members and Technical Assistants of the

Chemical Engineering Department and to all the members of this and other groups.

Atanu Kumar Paul (CH/07/56) _____________________________

Ravi Shankar Mukherjee (CH/07/02) _____________________________

Souvik Nandy (CH/07/05) _____________________________

Swarnav Mitra (CH/07/21) _____________________________

Tapas Sen (CH/07/52) _____________________________

Trishagni Sen (CH/07/32) _____________________________

ABSTRACT

Inverse fluidization is a technique in which solid particles having lower density

than that of the liquid are kept in suspension by the downward flow of continuous liquid

phase. Inverse fluidization has several advantages such as high mass transfer rates due to

reduced film thickness resulting from rotation due to low inertia, minimum carry over of

coated microorganisms due to less solids attrition, efficient control of bio-film thickness

and ease of re-fluidization in case of power failure. These significant advantages found

many applications of inverse fluidized beds in biochemical processes like ferrous iron

oxidation and aerobic and anaerobic biological wastewater treatment like treatment of

wine distillery wastewater. Even though, the applications of the inverse fluidized bed

technique to industrial processes are fast growing, much information on hydrodynamics,

mass transfer and chemical reaction is not yet available. Two phase (liquid – solid)

inverse fluidized beds are used for anaerobic biological processes due to their high mass

transfer potential.

The studies on the hydrodynamics and mass transfer of two-phase inverse

fluidization were performed only in the last few decades one of the most important recent

applications of inverse fluidized beds is in the field of bioreactor engineering. Inverse

fluidization is used in biotechnology as the basics of a new type of bioreactor, the so

called inverse fluidized bed bioreactor are among the most efficient application for

aerobic and anaerobic wastewater treatment Penicillin Production and Phenol

degradation.

The inverse fluidization system gained significant importance during the last few

decades in the field of environmental, biochemical engineering, and oil water separation.

The hydrodynamics of the inverse fluidization have been studies by Karamanev

and Nikolov (1996), Ulaganathan and Krishnaiah (1996), Ramos et al. (1998), Banerjee

et al. (1999), Vijaya Lakshmi et al. (2000), and Renganathan and Krishnaiah (2003, 2004,

2007) using water-solid system. They proposed empirical correlations to predict the

minimum inverse fluidization velocity. Fan et al. (1982), Karamanev and Nikolov (1992),

Biswas and Ganguly (1997), Bendict (1998), Lee (2001), Renganathan and Krishnaiah

(2005) reported the bed expansion characteristics in two phase downward fluidization

and predicted their bed expansion data in terms of Richardson and Zaki equation.

It is very much essential to study on hydrodynamic characteristics such as

pressure drop and minimum inverse fluidization velocity for successful analysis, design

and operation of inverse fluidization bed.

Experiments will be carried out using four polyethylene particles having different

densities, different diameter and sphericity with different concentrated aqueous solutions

of SCMC as fluidizing liquid. Minimum fluidization velocity will be estimated from the

experimental data. An empirical correlation will be developed for the minimum

fluidization velocity as a function of physical and dynamic variables of the system.

Contents

Content Page no.

Acknowledgement

Abstract i

Contents iii

List of tables v

List of figures vi

Chapter - 1: Introduction 1-16

1.1 Literature review 1

1.2 Objective of the project 12

1.3 Minimum fluidization velocity 13

1.3.1 Different flow regimes 13

1.3.2 The bed expansion 14

Chapter - 2: Experimental setup and technique 17-25

2.1 Experimental setup 17

2.2 Rheological properties of scmc solution 18

2.3 Solid particles 21

2.4 Experimental technique and procedure 22

Chapter - 3: Results and discussions 26-54

3.1 Evaluation of minimum inverse fluidization velocity 26

3.1.1 From pressure drop data 26

3.1.2 From bed porosity 28

3.2 Effect of rheological properties on the minimum inverse

fluidization velocity 29

3.3 Effect of column diameter on the minimum inverse

Fluidization velocity 29

3.4 Effect of sphericity 30

3. 5 Analysis of the minimum inverse fluidization velocity 30

3.5.1 Yu et al. (1968) correlation 33

3.5.2 Ulaganathan and krishnaiah (1996) 33

3.5.3 Vijaya lakshmi et al. (2000) correlation 33

3.5.4 Banerjee et al. (1999) correlation 34

3.5.5 Empirical correlation for minimum inverse

Fluidization velocity 35

3.5.6 Comparison of the different method 36

Conclusions 55

Nomenclature 56

References 57

List of Tables

Sl No. Table No. Content Page No.

1 2.1 Dimensions of Experimental Setup 25

2 2.2 Rheological and physical properties of dilute

aqueous solution of SCMC

25

3 2.3 Physical properties of particles 25

4 3.1 Typical experimental values of minimum

inverse fluidization velocities obtained from

pressure drop graph and bed expansion graph

38

5 3.2 Correlations obtained from literature 41

6 3.3 Average Relative Error and Relative

Absolute Error for Reynolds number at

minimum inverse fluidization velocity

43

List of Figures

Sl No.

Figure No.

ContentPage No.

1 1.1 Inverse Fluidization and Normal Fluidization 16

2 2.1 Experimental set-up for the study of inverse fluidization 23

3 2.2 Rheogram of SCMC solution 24

4 3.1 Plot of pressure drop versus velocity 44

5 3.2 Plot of pressure drop versus velocity for sample LDPE-1 (SCMC concentration 0.2 kg/m3)

44


45


45


46


46


47


47


48

13 3.10 Plot of pressure drop versus velocity for sample HDPE (SCMC concentration 0.2 kg/m3)

48


49


49


50

17 3.14 Plot of pressure drop versus velocity for sample PP (SCMC concentration 0.2 kg/m3)

50


51


51


52

21 3.18 Variation of minimum inverse fluidization velocity with bed weight

52

22 3.19 Schematic diagram of variation of liquid velocity with bed porosity

53

23 3.20 Variation of minimum inverse fluidization velocity with concentration of SCMC

53

24 3.21 Dependence of Rem on Archimedes number based on minimum fluidization velocity for different correlation

54

25 3.22 Variation of the calculated Rem with the experimental Rem

54

Chapter-1 Introduction

Inverse Fluidization Using Non Newtonian Fluid



Fluidization where the liquid is a continuous phase is commonly conducted with

the upward flow of the liquid in liquid –solid phase or with an upward and the liquid in

gas- signed-solid system. Under these fluidization conditions, a solid of particles with a

density figure than that of the liquid is fluidization with an upward flow of the liquid

counter to the net gravitational force of the particles when the density of the particles is

smaller than that of the liquid and the liquid is the continuous phase, however,

fluidization can be achieved by a down ward flow of the liquid counter to the net

buoyancy face of the particles. Such a type of fluidization is termed inverse fluidization.

So the main difference between the classic and inverse fluidization is that the solid

particle density in the inverse fluidization bed is less than that of the density of the

continuous fluid and therefore the bed is fluidized by a down flow of the fluid. Schematic

illustration of both classic and inverse fluidized beds is shown in Fig.1.1.

The first studies on the application, hydrodynamics and mass transfer of two-

phase inverse fluidization were performed in last few years (Nikolov et at 1981, Gsn et at

1991). One of the most important recent application of inverse fluidized beds is in

thefield of bioreactor engineering. Inverse fluidization is used in biotechnology as the

basics of a new type of bioreactor, the so called inverse fluidized bed bioreactor are

among the most efficient application for aerobic and anaerobic wastewater treatment

(Jeris et at 1981, Jewell et at 1981) Penicillin Production (on et at 1988; Endo et at 1988)

and Phenol degradation (Holladay et at, 1978, Tang and Fan 1987).

Further advantages can be founding the reactor design. If the gas distribution is

fitted above the reactor bottom, a calming zone can thus be integrated in the lower

separate the sludge from the liquid. Furthermore the friction effects between the solid

particles would helps for a better control of biofilm size and to a stronger biofilm

attachment.


Inverse Fluidization Using Non Newtonian Fluid Page 2

However, the important problem of biofilm thickness control is the main reason

for the limited industrial application for these systems. However, this inverse fluidization

technique may be advantageously used in the field of environmental engineering as

biological reactor (Legile et al., 1988). In this case, the granular solid is used as a carrier

for the microorganisms involved in the reaction. From the hydrodynamic point of view,

this configuration enables many advantages over the classical three-phase processes. In

the field of biological wastewater treatment, for instance, this kind of reactor enables to

use the gas flow as only a fluidizing agent (biological waste water treatment plant

generally work under high liquid retention times and thus low liquid velocities compared

to the minimal fluidization velocity of the solid). This point is particularly important

because this does not require any extra energy cost in aerobic processes. Further

advantages can be found in the reactor design. If the gas distributor is fitted above the

reactor bottom, a calming zone can thus be integrated in the lower section and this can act

as a settler to separate the sludge from the liquid. Furthermore, the friction effects

between the solid particles would help for a better control of the biofilm size and to a

stronger biofilm attachment. Thus the control of the bio film thickness within a narrow

range is achieved in the inverse fluidized bed bio film reactor. Three-phase fluidized bed

bioreactors have the following advantages over other bioreactors, such as suspended-

growth and trickling-filter bioreactors, used in fermentation and aerobic wastewater

treatment:

Low Wash Out rate of microbes from the system.

No Clogging of biomass in the system.

High and variable biomass concentration and large solid-liquid contacting area.

Thus the large bio-film-liquid interfacial area, high interfacial velocities and good

mass transfer characteristics are the main advantages of this type of bioreactor. In

addition to the above, aerobic wastewater treatment fluidized bioreactors exhibit

minimum recycle requirements and minimum biomass recovery at high substrate loading.

A fluidized bed provides better solids and liquid mixing, better oxygen transfer, more

CO2 removal, more stable cell population and easier cell regeneration than a hollow fiber



reactor. The bio-reaction rates per unit volume of the reactor were up to 14 times higher

than those in the equivalent airlift bioreactor. The uncontrolled growth of the fixed

biomass changes the hydrodynamic characteristics of each bio particle (support particle

covered by bio-film) and the whole fluidized bed. It also affects the mass transfer of

substrate into the bio-film. As per the biofilm control is concerned, a better control is

obtained in case of fluidized bioreactors. Increasing bio film thickness reduces density

differences between the bio-particles and the liquid, thus causing entrainment of the bio-

particles into the draft tube. Inside the draft tube, extensive abrasion among the heavy

particles and the entrained light bio-particles removes excess bio-film providing a

delicate means to control bio-film thickness. It was found that this bioreactor is very

efficient when used for biological aerobic wastewater treatment both under laboratory

conditions and when scaled up (Nikolov and Karamanev, 1987; Nikolov et al., 1990).

Another important biotechnological process, ferrous iron oxidation by Thiobacillus

ferrooxidans, was also carried out with very high efficiency in an inverse fluidized bed

bio film reactor (Nikolov and Karamanev, 1987; Karamanev and Nikolov, 1988). The

bioreactor was successfully used for milk protein hydrolysis by Lactobacillus helveticus

(Dion et al., 1988). Moreover, this apparatus was found to be suitable as a laboratory tool

for bio film process research (Nikolov and Karamanev, 1990)



1.1 Literature review

Fan et al. (1981) were worked on hydrodynamic characteristics of inverse

fluidization in liquid-solid and gas-liquid-solid systems. The experimental data for bed

expansion in the liquid-solid system are correlated, both empirically and semi

empirically.

The flow characteristics of inverse fluidization free stylizing low density spherical

particles experimentally investigated by L.S. Fan et. al ( 1982 ) for both the liquid, solid

and gas-liquid solid systems. The experimental data for the bed expansion in the liquid-

solid system are correlated, both empirically and semi-empirically. In the gas-liquid-solid

system in which the gas and liquid flows are countercurrent, two modes of fluidization

are examined. They are fluidization with the liquid as a continuous phase and fluidization

with the gas as a continuous phase; the former characterizes the inverse gas-liquid-solid

fluidized bed, while the latter characterizes the turbulent contacting bed. A flow regime

diagram which portrays these of fluidization is presented. Correlation of the bed

expansion and gas hold-up proposed for the inverse gas-liquid-solid fluidization.

A new apparatus, the inverse fluidized bed biofilm reactor was described by L.

Nikolov et. al ( 1986 ). Introduction of the so called inverse fluidized bed, in with low

density particles covered by a biofilm are fluidized by down flow of the liquid, allows

control of the bio-film thickness and provides a high oxygen concentration in the reacting

liquid.

Characteristics of the reactor were should by carrying out two important

biotechnological process, aerobic wastewater treatment by a mixed bacterial culture and

ferrous iron oxidation by the bacteria Thiobacillus ferrooxidans. The bio-reaction rates

per unit per unit volume of the reactor were up to 14 times higher than those in the

equipment airlift bioreactor. The structure of the liquid flow was determined by a tracer

method.

Karamanev and Nikolov (1992) studied on bed expansion characteristics of

liquid-solid inverse fluidization. They used twelve different spheres with diameters from

1.31 to 7.24 mm and densities between 75 to 930 Kg/m3 and continuous phase was water.



The experimental data on the porosity was analyzed and found similar to Richardson and

Zaki (1954) model, i.e., the plot of versus U in the logarithmic scale was parallel to

those of Richardson and Zaki (1954), therefore the exponent, n were similar. However,

Umf at = 1 differed from that predicted from standard drag curve for NRe >130. This can

be explained by the fact that the drag curve of freely rising light spheres differs from that

of a falling particle. The values of Umf calculated using modified drag curve were in good

agreement with the experimental results. The difference between minimal fluidization

velocity obtained experimentally and that calculated from Ergun equation is explained by

the difference in mechanical inertia of the light and heavy particles. They also observed

that fluidized particles with densities between 100 and 200 kg/m3 have unusual expansion

characteristics – lower than the expected minimum and maximum fluidization velocities.

The experimental relation between Co & Ret for the case of Steady rising

particles was developed. The significant difference between the drag co-efficient of light

heavy particles was observed.

Experiments were conducted Krishnaiah,K. et al (1993) by to study the

hydrodynamics of inverse gas-liquid-solid fluidized beds using very light particles. The

experimental data for the minimum liquid velocity at the onset of fluidization are

correlated in terms of the physical properties of the fluids, particle characteristics and

system variables. A correlation for the friction factor is also proposed.

Nikov and Karamanev (1994) have reported mass transfer studies in liquid

inversed fluidized bed reactor. They found that the mass transfer rate is independent of

superficial velocity and strongly depends on particle density.

Ulaganathan and Krishnaiah (1995) studied the hydrodynamic characteristics of

two phase inverse fluidized bed reactor with 12.5 to 20 mm diameter in a 75 mm column.

They presented equations to predict the minimum fluidization velocity.

The volumetric effectiveness of IFFBR was studied by D.G. Karamanev et al (

1996 ) and compared with that of a chemostat shows the relation between the volumetric

glucose uptake rate in both IFFBR and chemostat. At high substrate conversion (over

80%), the fluidized bed bioreactor is 25 times more efficient than a chemostat without



cell recycle; this difference increases to 0.1 as the substrate conversion decreases to 20%.

There are the most efficient design would be IFBBR tank in se.

Hydrodynamic characteristics of inverse fluidization in which low density floating

particles are fluidize with downward flow of liquid, are experimentally investigated by

Ulaganthan, N et al (1996) . The experiments are carried out with low density particles

(<534kg/m3) which allow high liquid throughputs in the system. During the operation,

three regimen, namely, packed semi-fluidization and fully fluidization are encountered.

Empirical correlations are proposed to predict the pressure drop in each regime. A

Computational procedure is developed to simulate the variation of pressure drop with

liquid velocity.

Biswas S.K et al (1997) studied on the voidage – velocity lerationship in reverse

fluidization. They showed that there a linear relationship of the plot of ln(Uf/Upr) versus

lnЄ and also shows the effect of the quality of solid on the slop of such plot.

Buffiere and Moletta (1998) investigated some hydrodynamic characteristics of

three phase fluidized bed reactor. Using two types of particles having different

characteristics (ds = 4 mm and 0.175 mm; s = 920 and 690 Kg/m3, respectively) allowed

us to observe two different expansion mechanisms :

A pseudo-fluidized state promoted by density difference between the solid and

surrounding gas-liquid mixture.

A fluidized state due to the liquid circulation induced by the rise of bubbles.

A correlation for the liquid hold-up and bed porosity could be proposed by means of a

modified gas drift flux model.

Femin Bendict,R,J et al (1998) studied hydrodynamics characteristics (bed

expansion and pressure drop) of a different type of two phase inverse fluidized bed

reactor in which low density particles are fluidized with downward flow of liquid.

Experiments conducted by using 6mm diameter spherical particles of low-density

polyethylene (LDPE) and polypropylene (PP) with water and aqueous solutions of

Carboxy methyl cellulose (CMC). It was found that the minimum fluidization velocity,



Umf decreased with increase in CMC concentration and solid density. They proposed a

dimensionless correlation for the prediction of bed height at fully fluidized conditions.

Some hydrodynamic characteristics of inverse three-phase fluidized bed were

investigated Pierre Buffiere et al (1999). Using two types of particles having different

characteristics (ds = 4 mm, Ps = 920 kgm3, and ds = 0.175 mm and p1 = 690 kgm3

respectively allowed us to observe two different expansion mechanism: a pseudo-

fluidized state promoted by the density difference between the solid and the surrounding

gas-liquid mixture, and a fluidized state due to the liquid circulation induced by the rise

of the bubbles. Both contributed to the solid mixing and axial solid distribution in the

systematic holdup measurements were done on two reactor diameter and two types of gas

Spurger. A correlation for the liquid holdup and bed porosity could be proposed by

means of a modified gas drift flux definition. The latest was a function of gas velocity

only and gave a good accuracy among the range of solid amount, gas and liquid velocity

used.

Experimental data on the minimum inverse fluidization velocity, Umf was

obtained by R.Leyva Ramos et al ( 1999 ) in this work. The particles use were made of

low density polyethylene and polypropylene; the diameters and densities were in the

ranges of 0.17 to 0.91 cm and of 18 to 913 kg/m3 respectively. The experimental Umf was

values obtained in this study and Umf values reported in the literature were compare to the

values predicted from different correlations and it was found that the predicted values had

an average percent deviation above 20%. Due to this fact a new correlation was proposed

which had an average percent deviation of the order of 16.6%. It was shown that the Umf

increased with augmenting the particle diameter and with decreasing the particle density.

Suk Choi ,H. et al(1999) investigated the hydrodynamic characteristics of two

types of inverse fluidized bed reactors having different force for fluidization: aeration and

centrifugal force. They found the gas velocity at which the solid concentration is uniform

throughout the bed expansion decreases with increasing particle loads. For the application

of wastewater treatment, the inverse fluidized bed with aeration was found to be more

efficient than the second type of reactor



Benerjee, J.et al (1999) studied fluidization in a cylindrical column using water

as the fluid taking various kinds of low density polythene beads, having specific gravities

lighter than water. The minimum reverse fluidization velocities (for multi-component

systems only) have been determined from the conventional plots of bed pressure drop

versus superficial fluid velocity

Vijaya Lakshmi et al. (2000) studied the hydrodynamic characteristics of LDPE

and PP in a liquid solid inversed fluidized bed reactor as a function of particle diameter,

liquid viscosity and density. They proposed empirical equations for the minimum

fluidization velocity and friction factor.

Dong Hyun Lee (2001) studied the Hydrodynamic transition experiments for tow-

phase (liquid-solid), both upward and downward, liquid flow systems in a 127-mm

diameter column. The particles used were 3.2 mm polymer (1,280 kg/m3), 5.8-mm

polyethylene (910, 930, 946 kg/m3), 5.5-mm polystyrene (1,021 kg/m3) and 6.0 mm

glass (2,230 kg/m3)spheres, with water, aqueous glycerol solution and silicon oil as

liquids. Experiment shows that the dimensionless pressure gradient increases initially

with increasing liquid velocity, but decreases gradually with increasing liquid velocity

beyond minimum fluidization velocity due to bed expansion. The non-dimensionalied

pressure gradient using the liquid/solid mixture density increases with increasing liquid

velocity and then reaches a constant value close to unity beyond minimum fluidization

velocity.

Renganathan ,T et at (2001) used Monte Carlo simulation to predict bed

expansion in inverse fluidized bed, which is an important parameter for the design of the

equipment. The simulation is carried out of various liquid velocities and number of

particles for a particular particle diameter and density. They found that the void fraction

increases with the liquid velocity and is independent of the number of particles. Very

good agreement between simulated and experimental void fraction values in obtained

Delebarre ,A et al (2003) carried out two series of fluidization tests on two test

models with catalyst, alumina and sand particles to determine the bed mass influence on

the characteristics at the minimum of fluidization. They concluded that (i) measured



minimum velocities increased with the inventory whatever were the solid and the test rig

used; (ii) the measured bed porosity at minimum fluidization decreased with the increase

of the bed inventory, (iii) the definition of the minimum fluidization velocity by the

balance between weight and drag forces and some usual mathematical modeling attempts

were not able to describe the minimum fluidization increase with the bed inventory; (iv)

the addition of a complementary consolidation effect in the force balance was able to

match the obtained experimental results.

Renganathan, T. et al (2004) studied liquid phase residence time distribution in

2-phase inverse fluidized bed for the first time in the literature. They used a pulse tracer

technique and disconsolation method of analysis, RTD of the system, residence time,

Peclet number and dispersion coefficients are determined. They found the liquid phase

axial dispersion coefficient increases with increase in liquid velocity and Archimedes

number and is independent of static bed height. An empirical correlation has been

proposed for liquid phase axial dispersion coefficient in 2-phase I IFB.

Delebarre ,A et al (2003) carried out two series of fluidization tests on two test

models with catalyst, alumina and sand particles to determine the bed mass influence on

the characteristics at the minimum of fluidization. They concluded that (i) measured

minimum velocities increased with the inventory whatever were the solid and the test rig

used; (ii) the measured bed porosity at minimum fluidization decreased with the increase

of the bed inventory, (iii) the definition of the minimum fluidization velocity by the

balance between weight and drag forces and some usual mathematical modeling attempts

were not able to describe the minimum fluidization increase with the bed inventory; (iv)

the addition of a complementary consolidation effect in the force balance was able to

match the obtained experimental results.

Renganathan, T. et al (2004) studied liquid phase residence time distribution in

2-phase inverse fluidized bed for the first time in the literature. They used a pulse tracer

technique and disconsolation method of analysis, RTD of the system, residence time,

Peclet number and dispersion coefficients are determined. They found the liquid phase

axial dispersion coefficient increases with increase in liquid velocity and Archimedes



number and is independent of static bed height. An empirical correlation has been

proposed for liquid phase axial dispersion coefficient in 2-phase I IFB.

Formisani et al (2007) have investigater process of fluidization of mixtures of two

spherical solids differing only in density and addresses the relationship between bed

suspension and component segregation. Fluidization properties of density-segregating

mixtures is that based on the definition of the initial and final fluidization velocity of the

binary bed.Such an alternative approach provides an effective representation of the actual

behaviour of these systems, as it correctly accounts for all the variables which affect their

phenomenology of fluidization. data for bed expansion are taken for making

dimensionless empirical or semi-empirical correlation

Jenaa et. al(2008) have studied the hydrodynamic characteristics, viz. the pressure

drop, bed expansion and phase holdup profile of a concurrent three-phase fluidized bed

with an antenna-type air sparger have been determined. Correlations for minimum liquid

fluidization velocity, bed voidage and gas holdup have been developed. The bed voidage

is found to increase with the increase of both liquid and gas velocities. The gas holdup

increases with gas Froude number, but decreases with liquid Reynolds number. The gas

holdup is a strong function of the Froude number. The experimental values have been

found to agree with the correlations.

Sowmeyan and Swaminathan (2008) also studied on Effluent treatment process in

molasses-based distillery industries. Among the different methods available, they found

that “An Inverse Anaerobic Fluidization” to be a better choice for treating effluent from

molasses-based distillery industries using an inverse anaerobic fluidized-bed reactor

(IAFBR). This technology has been widely applied as an effective step in removing 80–

85% of the COD in the effluent stream.

Sowmeyan and. Swaminathan (2008) reported on the physical characteristics of

carrier material (perlite), biomass growth on the carrier material and the biogas

production during an apparent steady state period in an inverse anaerobic fluidized bed

reactor (IAFBR) for treating high strength organic wastewater. Before starting up the



reactor, physical properties of the carrier material were determined. 1 mm diameter

perlite.

Sokoł et al (2009) investigated on the biological wastewater treatment in the

inverse fluidised bed reactor (IFBR) in which polypropylene particles of density 910

kg/m3 were fluidised by an upward flow of gas. Measurements of chemical oxygen

demand (COD) versus residence time t were performed for various ratios of settled bed

volume to reactor volume (Vb/VR) and air velocities ug. The largest COD removal was

attained when the reactor was operated at the ratio (Vb/VR)m = 0.55 and an air velocity

ugm = 0.024 m/s. Under these conditions, the value of COD was practically at steady

state for times greater than 30 h. Thus, these values of (Vb/VR)m, ugm and t can be

considered as the optimal operating parameters for a reactor when used in treatment of

industrial wastewaters. A decrease in COD from 36,650 to 1950 mg/l, i.e. a 95% COD

reduction, was achieved when the reactor was optimally controlled at (Vb/VR)m = 0.55,

ugm = 0.024 m/s and t = 30 h. The pH was controlled in the range 6.5–7.0 and the

temperature was maintained at 28–30 ◦C. The biomass loading was successfully

controlled in an IFBR with support particles whose matrix particle density was smaller

than that of liquid. The steady-state biomass loading depended on the ratio (Vb/VR) and

an air velocity ug. In the culture conducted after switching fromthe batch to the

continuous operation, the steady-state biomass loading was attained after approximately

2-week operation. In the cultures conducted after change in (Vb/VR) at a set ug, the

steady-state mass of cells grown on the particles was achieved after about 6-day

operation. For a set ratio (Vb/VR), the biomass loading depended on ug. With change in

ug at a set (Vb/VR), the new steady-state biomass loading occurred after the culturing for

about 2 days.

Wang et. al. (2010) studied the Removal of emulsified oil from water by inverse

fuidization of hydrophobic aerogels. Different size ranges of surface-treated hydrophobic

silica aerogels (Nanogel®) were fuidized by a downward flow of an oil-in-water

emulsion in an inverse fuidization mode. Surface areas, pore size distributions, and pore

diameters were investigated by using BET and contact angle is measured by a



goniometer. The hydrodynamics characteristics of the Nanogel granules of different size

ranges were studied by measuring the pressure drop and bed expansion as a function of

superficial water velocity. The density of the Nanogel granules was calculated from the

plateau pressure drop after the bed was fully fluidized. The oil removal efficiency of a

dilute (1000 ppm COD or lower), stabilized (using the emulsifer Tween 80) oil-in-water

emulsion and the capacity of the Nanogel granules in the inverse fluidized bed were also

studied. A model was developed to predict the inverse fluidized bed experimental results

based on equilibrium and kinetic batch measurements of the Nanogel granules and the

stabilized oil-in-water emulsion. The results showed that the major factors which affect

the oil removal efficiency and capacity are the size of the nanogel granules, bed height,

fluid superficial velocity and the proportion of emulsifier in the oil-in-water emulsion.

Das et. al. (2010) investigated Inverse fluidization using non-Newtonian liquids.

Experiments had been carried out to determine the minimum inverse fluidization velocity

using single and binary systems of four different solids of polymeric origin, and four

different non-Newtonian liquids in two different columns. Empirical correlations had

been developed to predict the minimum inverse fluidization velocity as a function of

physical and dynamic variables of the system. Statistical analysis of the correlation

suggested that is of acceptable accuracy with correlation coefficient more than 0.99.

1.2 Objective of the project

The main aim of this project work –

1. To investigate the hydrodynamic behavior of the two phase (liquid – solid)

inverse fluidized bed using non-Newtonian liquid.

2. To develop empirical correlation to predict the minimum fluidization velocity

from system parameter & also to compare the experiment minimum fluidization

velocity with the different correlation obtained from literature.

3. To develop empirical mathematical correlation to predict bed expansion as a

function of system variables.



1.3 Minimum Fluidization Velocity

Theoretically, umf should be same for both up flow and inverse fluidization for the

following reason. The Ergun equation is based on the main assumption that the drag force

of the fluid moving with a superficial velocity umf is equal to the weight of the particles in

the bed:

olpo

g

1 (1)

In the bed containing light particles, the weight force should be replaced by the buoyancy

force:

oplo

g

1 (2)

Since Equations (1) & (2) are identical, the minimum fluidization velocities in both up

flow and inverse fluidized beds should be equal when parameters of the liquid phase,

particle diameters and the absolute values of lp are equal. In fact it has been

experimentally established (Karamanov and Nikolov, 1992) that an inverse fluidized bed

consisting of low-density particles has smaller umf compared to that of an up flow

fluidized bed (and that predicted by the Ergun Equation) for Remf > 50-70. This

difference is negligible when Remf is less than the critical one.

1.3.1 Different flow regimes

Static bed regime

At low superficial liquid velocity, the liquid moving down does not disturb the bed but

just percolates. The voidage of bed and the height remain constant.



Partially fluidized bed regime

When uf is increased further, the liquid gains enough energy and overcomes the inertial

force of the solid particles and hence the static bed partially becomes dynamic. Only then

lower end of the bed tends to be fluidized and the upper half remains static.

Completely fluidized bed regime

This regime starts when the superficial liquid velocity equals or exceeds the minimum

fluidization velocity. The force exerted by the liquid velocity overcomes the inertial force

of all the particles in the column and thus the bed fluidizes. All the particles are in motion

during the completely fluidized bed regime.

1.3.2 The Bed Expansion

The different models for the correlation of bed expansion with the superficial

velocity can be classified into three main groups ( Fan et al., 1982). The first group is

based on correlations giving the dependence between U / Ui and . The Richardson &

Zaki model (1954) is most popular in this group. In the second group of models the drag

function for multi particle system is used. It is usually given as a function of Re and Ar.

The models of Ramamurthy and Subbaraju (1973) and Riba and Couderc (1977) are

typical for this group. The third group of models is based on the dependence between

and the main variables of the fluidized bed as in the Wen and Yu (1966) correlation.

Among all these correlations, the Richardson and Zaki model is probably the most

popular one due to its simplicity and good agreement with the experimental data.

The drag coefficient CD is determined from the standard Drag curve the

dependence ln CD – ln Ret (Den, 1980). The standard drag curve is based on experimental

data with settling heavy spherical particles in a fluid when P >l. There is no

information available regarding the validity of the standard drag curve in the case of

freely rising light spheres with P < l. The free rise of spherical particles with densities

smaller than that of the fluid is believed to obey the laws of free settling since the same

forces are applied to the particle but in the opposite directions.



Additional experiments are necessary for determination of this dependence.

Nevertheless, in many publications, including one of the best monographs on particle-

fluid interactions. The assumption was made that the drag curves of free falling and rising

solid spheres are identical. This assumption was not however confirmed by the

experimental data.

Striking Features of Inverse Fluidized bed

Several specific characteristics of the two-phase inverse fluidized bed usually not

observed in “Classic” up flow fluidization must be underlined. The liquid entering the

fluidized bed often carries gas bubbles. When a bubble enters an up flow fluidized bed, it

leaves the bed rapidly because the direction of its free rise is the same as the direction of

the liquid flow and therefore it does not change significantly the hydrodynamic state of

the bed. In inverse fluidized bed, these directions are opposite to each other and the

bubble entering the bed with the liquid phase usually remains in it, provided it is not too

small. In the later case, the bubble moves downwards together with the liquid.

Consequently, since gas bubbles accumulate in the inverse fluidized bed, they affect the

hydrodynamic measurements. It is very important therefore to eliminate the gas bubbles

from the liquid entering the bed. The solid particles used in the up flow fluidized beds are

usually non-porous materials like glass, metals, sand, plastic beads, etc. Each of these

materials has a certain constant density.



Normal Fluidization Particles heavier than flowing liquid

(Anti-gravity flow)

Fluidized Bed

(Upward Bed Expansion)

Liquid Stream Outlet

Liquid Stream Inlet

Dire

ctio

nof

Bed

Expa

nsio

n

Inverse Fluidization Particles lighter than flowing liquid

(Gravitational flow)

Liquid Stream Outlet

Liquid Stream Inlet

Fluidized Bed

(Downward Bed Expansion)

Figure : 1.1 Inverse Fluidization and Normal Fluidization

Chapter-2 Experimental setup and technique




This chapter deals with the description of the experimental setup and technique

used for the experiment.

2.1 Experimental Setup

The schematic diagram of the experimental setup is shown in Fig. 2.1. The

experimental apparatus consisted of a liquid storage tank, centrifugal pump, test section,

control and measuring system for flow rate and pressure drop and other accessories.

Thick transparent Perspex tubes with internal diameters of 72 x 10-3 m and 47 X 10-3 m.

are used for the experiment. The experimental setup consisted of three section, liquid

distribution section, test section and liquid discharge section. The entire test section is

vertically mountain to prevent vibration. The upper part is the liquid distribution section

filled with the glass marbles in the size range of 1-3 cm in diameter for uniform

distribution of liquid in the column. This marbles is supported and enclose by 16 mesh

stainless steel grid. An air vent is also provided at the top of the column. The middle

portion of the column is the test section. It consisted wire mesh at the top and connected

with bottom of the discharge section. Pressure trappings are provided to measure

pressure drop of the column. Simple U-tube and inclined manometers containing carbon

tetrachloride beneath water are used for the measurement for pressure difference across

the column. There is an entry port for loading the solid in the test section. A scale is

fitted on the outer surface of the column to measure the bed height. The dimension of the

columns is shown in Table 2.1.

Bottom section is the discharge section connected by means of a flange. The

discharge section consisted of a gate valve of 2.54 cm in diameter.

A rectangular tank (0.45 m3) is used for storage of liquid. The liquid is kept at

constant temperature by recirculation of tap water through a cupper coils. The liquid is

circulated from the tank by means of a centrifugal pump to the test section. Its flow rate

is controlled by a by pass valve and measure by rotameter RL1 and RL2 [Transducer and

Controls Pvt. Ltd., Hyderabad, India, accuracy 2%]. The liquid discharge from the test

section is returned to the tank by another centrifugal pump. The liquid flow rate is also

measure by collecting the liquid in certain interval of time at the discharge point.



Four different dilute solution of sodium salt of carboxy methyl cellulose (SCMC)

are used as experimental liquid. The physical properties of the experimental liquids are

measured by standard methods.

2.2 Rheological properties of SCMC solutions

Four aqueous solutions of sodium salt of carboxy methyl cellulose (SCMC) [Loba

Cheme Pvt.Ltd., Mumbai, India] of approximate concentrations 0.2 kg/m3, 0.4 kg/m3, 0.6

kg/m3 and 0.8 kg/m3, are used as the non-Newtonian liquids. The tests liquid are prepared

by dissolving the required amount of SCMC in tap water and stirring until a

homogeneous solution is obtained. It is kept at least 12 hrs. for aging and initially a trace

amount of formalin is added to prevent biological degradation. Contents of the tank are

kept at a constant temperature (280C ± 20C) by circulating water through the copper coil.

The properties of the non-Newtonian liquids are measured by standard techniques, i.e.,

viscosity is measured by pipeline viscometer, surface tension by Dünouy tensiometer and

density by specific gravity bottle.

The SCMC solution is a time independent pseudo plastic fluid and the Ostwald

de-Waele model or the power-law model describes its rheological behavior as,/n

duK

dr

(2.1)

Where, K and n are the constants for the particular fluid with n/ < 1. The constant K is

known as the consistency index of the fluid; the higher the value of K, the more viscous

is the fluid. The constant n is called the flow behavior index and is a measure of the

degree of departure from the Newtonian behavior. The more the departure of n from

unity, the more pronounced will be the non-Newtonian properties. In the case of non-

Newtonian fluids the establishment of what constitutes a suitable viscosity in analytical

terms, is a matter, upon which there is no general agreement. A number of viscosities

have been defined such as apparent viscosity, μap, effective viscosity, μeff, and limiting

viscosity, μα. In the present analysis the term effective viscosity, μeff, has been used

throughout for calculation. It is defined as the ratio of the shear stress at the wall to the



average shear rate at the boundary and for pipe flow, on the basis of Poiseuille’s

Equation, and is given by

(2.2)

In order to develop an expression for the effective

viscosity, μeff, for pseudoplastic fluids in pipe flow, let us consider the general equation,

(2.3)

where τ is shear stress at any radial position. For a fluid flowing through a pipe, a force

balance on a cylindrical fluid element of radius r gives,

2

r p

L

(2.4)

And that the wall, τW can be written as

2W

R p

L

(2.5)

And therefore

W

r

R

(2.6)

The volumetric flow rate for pipe flow is given by,

0

2R

Q rVdr (2.7)

Which on integration by parts, and applying the condition at r = R, Vl = 0, and

substitution of Eq. (2.7) leads to

23 3

0

1 W

W

Qf d

R

(2.8)

Since for the pseudo plastic fluids

48 8

Weff

l l

D pLV V

D D

( )ldVf

dr



1

nf

K

(2.9)

/

1

23 3

0

2 1 W nl

W

VQf d

R D K

(2.10)

Which on integration gives

/

1/

/

2

3 1

nl WV n

D n K

(2.11)

On rearranging,//

/

/

2 3 1nn

lW

V nK

D n

(2.12)

or

///

/

8 3 1

4

nn

lW

V nK

D n

(2.13)

Now as per the definition of μE, we have // 1 /

/

8 3 1

8 / 4

nn

W leff

l

V nK

V D D n

(2.14)

or/ /1 1 1 '8n n n

eff lV D K (2.15)

Where

//

/

3 1

4

nn

K Kn

(2.16)

Therefore, the value of μeff can be evaluated provided K and n are known.

In Eq. (2.14) it is clear that if a logarithmic plot is made between w and 8 /lV D , a linear

relation will result, the slope and intercept should of which are the values on n/ and K/

respectively.

A horizontal steel tube of 0.635 cm internal diameter is used as the pipeline viscometer

with pressure tapping at a distance of 1.85 m. Measurements on pressure drop are made

in the fully developed flow region of non-Newtonian liquids, in the laminar flow

condition. The developed flow region is ensured by providing the necessary and



sufficient straight entry length, i.e., more than 50 pipe diameter length of the tube. The

inlet end of the tube is well rounded to ensure smooth and parallel flow at the entrance.

From the data on pressure drop and flow rate, the values of w and 8 /lV D are

calculated for four different SCMC solutions. The rheogram are shown in Fig. 2.2 and

represent typical flow curves for pseudoplastic behavior in the shear rate range 32 – 950

s-1.

The values of n/, K/ and other physical properties of the liquids are shown in Table 2.2.

2.3 Solid particles

Four different particles having different diameters, shapes and densities made of

polymeric materials are used for the experiments. The representative diameters for the

non spherical particle are the equivalent diameter based on volume. Fifty random

samples are taken and its dimensions are measured by slide calipers and then average

volume is measured. The particles are spherical, cylindrical and cubical in shape. The

sphericity of these particles are measured by using the following equation

6 ps

p p

v

d S (2.17)

The diameters, density and sphericity for the binary system are measured by using the

following equations (Ganguly, 1994),

1

1

ni

Mi pi

xd

d

, (2.18)

1

n

M i ii

x

(2.19)

and, 1

n

M i sii

x

(2.20)

respectively. The physical properties of the single component solid particles are given in

Table 2.3.



2.4 Experimental Technique and Procedure

In actual experiments, a predetermined quantity of solids is admitted into the

column through the inlet port fitted at the side of the column which is subsequently

closed by a rubber cork. The fluid (aqueous SCMC solution) is fed into the column by

starting the centrifugal pump. The flow is increased to some extent till the bed of solids

starts expanding downwards. The pump is stopped to allow the solids float and

accumulate under the top strainer to form a fixed bed height which is called the initial

bed height. Finally the flow rate is increased gradually, causing the bed height to increase

in downward direction. The pressure drop, at each flow rate, has been recorded by the

manometer. The liquid flow rate is measured by collecting the liquid in certain interval of

time at the discharge point. Bed height is measured by the scale fitted on the surface of

the column. Each experiment has been repeated three times to confirm the reproducibility

of the data. The bed weight varies from 200 – 1000 gm for single component systems.

For binary mixtures, the weight has been kept at 500 gm, varying the mass fractions of

the components from 0.2 to 0.8. For all the experiments, however, actual bed pressure

drop, aP , has been determined by subtracting the blank pressure drop, blP , from the

observed pressure drop, oP , for the same fluid velocity, fu .

Hence,

a o blP P P



Figure : 2.1 Experimental set-up for the study of inverse fluidization

C: Main Experimental Column; D: Liquid Distribution Section; L: Liquid Collecting

Tank; P1: Pump pumping liquid to the column; P2: Pump recycling liquid to the main

tank; R: Rotameter; T: Main Liquid Collecting Tank; V1: Valve controlling liquid flow to

column; V2: Valve in the By-pass line.

L

TV

V

RD

C

P

P



10 100 1000

1

10

100

Symbol SCMC Conc.

Kg/m3

0.2 0.4 0.6 0.8

Fig. 2.2 Rheogram of the SCMC solution

Wal

l she

ar s

tres

s; DP

a/4L,

N/m

2

Shear rate; 8V/D, S-1



Table : 2.1 Dimensions of experimental setup

Table: 2.2 Rheological and physical properties of dilute aqueous solution of SCMC

Concentration

kg/m3

Flow behavior index

n/

Consistency index

K/

Nsn´/m2

Density

l

kg/m3

0.2 0.9013 0.0142 1001.69

0.4 0.7443 0.1222 1002.13

0.6 0.6605 0.3416 1002.87

0.8 0.6015 0.7112 1003.83

Table : 2.3 Physical properties of particles

Particle

Used

Average

diameter

dp

m

True

particle

density

ρp

kg/m3

Bulk

particle

density

ρb

kg/m3

Shape Spheri

city

p

Length/Dia

meter

LDPE 1 5.6410-3 915 0.906 Spherical 1 -

LDPE 2 4.1810-3 919 0.904 Cylindrical 0.873 0.943

HDPE 4.7910-3 944 0.913 Cylindrical 0.904 1.190

PP 3.1310-3 900 0.854 disc 0.777 -

Internal Diameter

of the Column

m

Wall Thickness

m

Total

Column

Height

m

Distance between

two Pressure

Tapings

m

72 x 10-3 3 x 10-3 1.50 1.11

Chapter-3 Results and discussions




This chapter deals with the determination of the minimum inverse fluidization

velocity and its analysis.

3. Results and Discussions

3. 1 Evaluation of minimum inverse fluidization velocity

3.1.1 From pressure drop data

When a liquid is passed through a bed of particles, with the gradual and continual

increase in the superficial velocity of the liquid, a point is reached whereby the bed just

begins to loosen, though the majority of the particles are still in contact with each other.

This velocity is called the minimum fluidization velocity. The minimum fluidization

velocity is an important hydrodynamic parameter involved in the design of this type of

system. Richardson (1971) pointed out that the transition from fixed bed to fluidized bed

conditions depends on number of mechanical details like original bed structure, design of

distributor, etc. and it always occurs gradually over as range of conditions thereby

making it difficult to identify precisely for normal fluidization. In case of inverse

fluidization it is defined as the lowest superficial velocity at which the downward weight

of the particles the drag force due to downward flow of the liquid just counters the

upward buoyancy force of the solid particles, i.e., the net upward force is equal to the net

downward force. Richardson (1971) comment is also true for the inverse fluidization. The

minimum fluidization velocity is measured by visual observations of the bed as well as

by the intersection of ΔPa - uf plots in fixed and fluidized bed regimes. As expected, the

pressure drop across the bed remains essentially constant once the fluidization has begun.

Actual bed pressure drop, aP , has been measured for a particular liquid velocity, fu , by

subtracting the blank pressure drop, blP , due to liquid flow at identical liquid velocity,

fu , from the observed pressure drop, aP , with solids present. Hence,

a ob blP P P (3.1)

The determining the minimum fluidization velocity, um, involves the use of data

on the variation in bed pressure drop across a bed of particulate solids with fluid velocity.



The trend in variation of the bed pressure drop with the superficial liquid velocity is

shown in Fig. 3.1. The transition point from the fixed bed to the fluidized bed is marked

by the onset of constant pressure. This is also the point at which the increasing trend in

the bed pressure drop (ΔPa) of a packed bed terminates. For an ideal case, liquid flow

reversal in the fluidized bed condition does not change the magnitude of ΔPa. However,

the value of ΔPa is smaller when the bed starts settling during flow reversal compared to

previous values obtained at the same velocity in the increasing flow direction. The

pressure drop method is the most popular means of determining um experimentally.

For liquid – solid inverse fluidization it is determined from the plot (Fig. 3.1) of

pressure drop versus the liquid velocity for the inverse fluidized bed system. From this

plot it is shows that as the velocity increases, the pressure drops increases (A→B) and

ultimately reaches a constant pressure drop zone (B→C). This A→B zone is static bed

zone. As increasing flow rate of the liquid pressure drop increases. The B→C zone is the

fluidized bed zone. The point (B) of intersection of the increasing part of the curve and

the constant region represents the minimum fluidization velocity. Further increasing the

liquid flow rate the particle of the bed starts to elutriate from the column. This C→ D

zone is referred as elutriation zone. In the elutriation zone the pressure drop falls off with

superficial velocity due to continual depletion of the solids in the column. The point (C)

of intersection of the constant region and the decreasing part of the curve represents the

minimum elutriation velocity.

The plots of aP versus fu for different systems are shown in Figs. 3.2 – 3.17. It

is clear from the plots that for the single component system there is a sharp transition

between fixed and fluidized bed where for binary system the transition is very gradual in

nature. The minimum inverse fluidization velocity, mu , is obtained from the point of

intersection of the fixed and fluidized bed lines. It is observed from the plots that

minimum inverse fluidization is independent of bed weight (Fig. 3.18)

Figs. 3.2 – 3.17 shows the pressure drop, aP , versus the liquid velocity, fu , at

constant bed weight but different bed compositions. It is clear from the plot that as the

amount of heavier particles increases the pressure drop also increases and the transition



from fixed to fluidized bed is not sharp but gradual. The value of the minimum inverse

fluidization, mu , is determined by the intersection of two tangents showing the beginning

of fluidization, minimum fluidization and total fluidization velocities. The slow and

gradual change is attributed to the fact that in binary system there is change of

segregation with the smaller particles getting fluidized first, followed by larger particles

which fluidize later. In this plot two factors affecting the minimum inverse fluidization

velocity namely the particle density and size. The HDPE has higher density and larger

diameter than that of PP.

3.1.2 From bed porosity

Another way of determination of the minimum inverse fluidization velocity is

from the porosity of the bed. The determination of bed voidage, ε, for any bed height, Hfl,

is carried out as follows,

fl

s

H

H1 (3.2)

and as a special case the voidage at static bed height, εm , is determined by replacing the

term Hfl in Eq. (3.2) by Hm , Thus

1 1s sm

fl m

H H

H H

(3.3)

Where Ls represents the static bed height at zero voidage and obtained as

2

4

ps

p t

WH

d

(3.4)

The minimum inverse fluidization velocity is determined from the plot bed porosity, ε,

vs. liquid velocity, uf, on a log-log plot as shown in Fig. 3.19. From the intersection point

of packed bed region and fluidized region (point B in Fig. 3.19) the minimum inverse

fluidization velocity can be determined. Fig. 3.19 show the typical plot of bed porosity

versus the liquid velocity for single system. It is observed that for binary component

system gradual transition from packed bed to fluidized bed occurs. Typical experimental



data of minimum inverse fluidization velocities obtained from both the procedure. The

minimum inverse fluidization velocity obtained from both the processes is practically

same.

3.2 Effect of rheological properties on the minimum inverse fluidization

velocity

The variations of minimum inverse fluidization velocity with different SCMC

solution concentrations are shown in Figs. 3.2 – 3.17. It is observed that the inverse

fluidization velocity, ,mu decreases with an increase in SCMC concentration, i.e.,

pseudoplasticity of the liquid for the both single and binary system. The observed

decrease in the minimum inverse fluidization velocity, mu is due to the decrease in

Archimedes number with increase in viscous force resulting from increase in viscosity of

liquid phase, i.e., as pseudoplasticity increases with increase in SCMC concentration

(Fig. 3.21). It is clear from the plots that the minimum inverse fluidization velocity, um,

for mixture is more than that of single sized particle due to change in mixture diameter

and density as well as sphericity. Similar results are also obtained for normal fluidization

(Fan et al., 1985) and for inverse fluidization (Bendict et al., 1998 and Vijaya Lakshmi et

al., 2000). It is also observed that the minimum inverse fluidization velocity, um, decrease

with the pseudoplasticity of the liquid.

3. 3 Effect of column diameter on the minimum inverse fluidization velocity

It is clear from the plot that with decrease in column diameter the inverse

fluidization velocity practically constant. In smaller diameter column the initial bed

height is more than that of the higher column diameter for certain amount of solid. There

is a possibility of the wall effect in the smaller diameter tube. The wall-effect becomes

prominent for low values of dt/dM. According to Wicke and Hedden (1952) if the ratio

dt/dM ≥ 10 the wall effect is negligible for the case of normal fluidization. For the present

study, this ratio is higher than that to cause any wall-effect. Happel and Byrne (1954)

attempted to correlate hindered settling velocity with dt/dM ratio, and observed that with



decrease in this ratio, the hindered settling velocity decreases, which means greater

floatability of the particles with a consequential increase in the value of the minimum

inverse fluidization velocity, um. Clift et al. (1978) pointed out that rising a particles

generate secondary motion, including rocking, zigzag or spiral movement, producing

thereby an increase in the effective drag coefficient. According to Clift et al. (1978), the

difference increases as the ratio ρs/ρf decreases, but becomes negligible for Rep < 1000.

Chhabra (2001) pointed out that for normal fluidization using non-Newtonian liquids if

dM/dt ≤ 0.32 then the wall effect is negligible. In the present case dM/dt ≤ 0.12, hence, the

wall effect is negligible and the minimum inverse fluidization velocity is independent of

the diameter of the tube.

3. 4 Effect of Sphericity

The effect of surface irregularity of the solids has been shown earlier by Pittyjohn

and Christiansen (1948) in free fall settling velocity in the sense that lower the sphericity

(i.e. more irregularity of the surface), lower will be the settling velocity or higher will be

the value of particle rise velocity, upr. Hence, higher fluid velocity will be required to

cause the particles to be fluidized in the downward direction (higher value of Rem). Such

dependence is also reflected by the negative exponent of φM in Eq. (3.24).

3. 5 Analysis of the minimum inverse fluidization velocity

For inverse fluidization with the z-coordinate taken as positive in the upward

direction, i.e., in the direction opposite to that of the liquid flow, and with the hydrostatic

head of liquid corrected for the frictional pressure gradient, the overall pressure variation

in the vertical direction coordinated for the frictional pressure gradient is given by

lf fsl

dP dPg

dz dz

(3.5)

The frictional pressure gradient in solid - liquid inverse fluidized beds is given by

,

p lf sl

dPg

dz

(3.6)



Substituting Eq. (3.6) into Eq. (3.5) and rearranging,

11 1p

fsll l

dP

g dz

(3.7)

In the case of a fixed bed, fsl

dP

dz

, can be expressed by the Ergun (1952) equation

applied to the liquid-solid interaction as follows:

22

2 2 2 2

150 1 1.75 1f fs f l f

fsl f p p f s p

u udP

dz d d

(3.8)

Substituting Eq. (3.8) into Eq. (3.5)

22

2 2 2 2

150 1 1.75 1f feff f l fl

sl f p p f p p

u udPg

dz d d

(3.9)

Transforming the above equation

22

2 2 2 2

150 1 1.75 11

f feff f l fsl

l f p p l f p p

dPu udz

g d g d g

(3.10)

The frictional pressure gradient at the minimum fluidization condition equal to the net

difference between gravitational and buoyancy forces per unit area. With the assumptions

of bed voidage, particle properties and the superficial velocity are all uniform over the

entire bed height, Eq. (3.7) - (3.10) can be applied if the bed height is measured and it is

assumed that voidages, particle properties and the superficial liquid velocity are all

uniform over the bed height so that the pressure gradient is also uniform over that height

interval.

22

2 2 2 2

150 1 1.75 1f feff f l fl p

sl f p p f p p

u udPg

dz d d

(3.11)

At the point of minimum inverse fluidization velocity, the above equation become

2 2

2 2 2 2

150 1 1.75 1eff mm m l mm l p

sl m p p m p p

u udPg

dz d d

(3.12)



From this equation minimum inverse fluidization velocity can be calculated. For low

Reynold’s no equation becomes

2 2 2

150 1 eff mm

m p ppl

ug

d

(3.13)

or,

2 2 2

150 1

m p p

meff m

plg du

(3.14)

The minimum fluidization velocities in both up flow and inverse fluidized beds

should be equal when parameters of the liquid phase, particle diameters and the absolute

values of p l are equal. In fact it has been experimentally established (Karamanov

and Nikolov, 1992) that an inverse fluidized bed consisting of low-density particles has

smaller um compared to that of an up flow fluidized bed (and that predicted by the Ergun

Equation) for Rem > 50 - 70. This difference is negligible when Rem is less than the

critical one.

Eq. (3.12) can be rearranged as

3150 1Re Re 0

1.75 1.75m m

m m mp

Ar

(3.15)

Wen and Yu (1966) produced an empirical correlation for um with a form similar

to Eq. (3.15). They reduced the above equation to the more generalized form as

1

22 1Rem mC C Ar C (3.16)

The Eq. (3.16) is valid for spheres in the range 0.01 < Rem < 1000, where C1 and C2 are

33.7 and 0.0408 respectively whereas Richardson (1971) correlation C1 and C2 are 25.7

and 0.0366 respectively and Grace (1982) correlation is based on the C1 and C2 are 27.2

and 0.0408 respectively. Fig. 3.21 show the variation of the Rem and Arm single sized

particles. The large deviation observed is due to non-Newtonian characteristics of the

liquid.



3. 5.1 Yu et al. (1968) correlation

Yu et al. (1968) empirically modified the Richardson – Zaki (1954) correlation

for predicting the minimum normal fluidization velocity using velocity – porosity

behavior for non- Newtonian liquid flow. They used aqueous solutions of Polyox in 100

mm diameter column, with particle size ranges from 2.5 – 9 mm. They obtained the

following expression which gives reasonable agreement between the experiment and

prediction in the range of 0.81 ≤ n ≤ 1,

2

2 1

9 3 112.5 Re

nn

m nm mn

m

nAr

(3.17)

Fig. 3.22 show the large deviation with the experimental data.

3. 5.2 Ulaganathan and Krishnaiah (1996)

Ulaganathan and Krishnaiah (1996) studied the hydrodynamic characteristics of

two-phase inverse fluidized bed with 12.5 to 20 mm diameter particle size in a 75.3 mm

diameter column. The experiments are carried out with low density particles (< 534

kg/m3) which allow high liquid throughputs in the system. During the operation, three

regimes, namely, packed, semi-fluidization and fully fluidization are encountered.

Empirical correlation is proposed to predict the minimum inverse fluidization velocity as

0.383 0.2022.93 10 /m m l p lu Ar (3.18)

A computational procedure is also developed to simulate the variation of pressure

drop with liquid velocity. Fig. 3.22 show the large deviation with the experimental data

as this expression is valid for inverse fluidization system using water.

3. 5.3 Vijaya Lakshmi et al. (2000) correlation

Hydrodynamic study of inverse fluidization experiments are carried out by Vijaya

Lakshmi et al. (2000) using low-density polyethylene and polypropylene along with

water and different concentration of aqueous solutions of carboxy methyl cellulose

(CMC) as non- Newtonian liquid. The experimental column they used, is made-up of

perspex with dimensions of 94 mm internal diameter with a maximum height of 1800



mm and a wall thickness of 3 mm. Spherical low density polyethylene (LDPE) and

polypropylene (PP) particles of 4, 6 and 8 mm diameters are used along with water and

different concentrations of aqueous solutions of CMC as liquid. They proposed empirical

equations for the prediction of the friction factor and the minimum inverse fluidization

velocity for water and non-Newtonian liquid system separately. Minimum inverse

fluidization velocities are determined from the bed expansion and pressure drop data.

They observed that minimum inverse fluidization is independent of solid loading and

increased with an increased in particles diameter, decreases with the solid density and

pseudoplasticity of non-Newtonian liquid. They proposed the following correlation to

predict the minimum inverse fluidization velocity for non-Newtonian solution

0.041 -6mRe =1.139 10 Arm (3.19)

for 0.00875 < um < 0.0175

and 2 < dP < 8 mm.

Figs 3.21 and 3.22 show unacceptable deviation with experimental data.

3. 5.4 Banerjee et al. (1999) correlation

Banerjee et al. (1999) investigated the inverse fluidized bed using various kinds of

low density polythene beds and different shaped (spherical, cylindrical and disc) with

water as the liquid phase. The minimum inverse fluidization velocities for uni-, and

multi-component systems, as well as the beginning of fluidization and total inverse

fluidization velocities are determined from the conventional plots of bed pressure drop

versus superficial liquid velocity. They proposed three empirical correlations to three

velocities namely, minimum inverse fluidization velocity, beginning of fluidization

velocity and total inverse fluidization velocity. The proposed correlation to predict

inverse fluidization velocity as

-6 1.513m mRe = 7.68 10 Ar (3.20)

Unacceptable deviation is observed with experiment as shown in Figs 3.21 and 3.22, as

they use spheriricity, φs = 1 for cases and water as liquid.



3.5.5 Empirical correlation for minimum inverse fluidization velocity

The minimum fluidization velocity, um, in liquid-solid inverse fluidized beds is a

function of physical and dynamic variables of the system. The following factors affect the

minimum inverse fluidization velocity,

1. Physical properties of the liquid : viscosity, eff , density, l

2. Physical properties of the solid : density, M and sphericity, M

3. Acceleration due to gravity : g

Hence, the minimum inverse velocity can be expressed as,

, , , , ,m M l M eff Mu F d g (3.21)

The use of dimensional analysis the above functional relationship can be reduced to the

following functional relationship (combining the variables),

Re ( , )m m MF Ar (3.22)

On the basis of Eq. (3.22), the multiple linear regression analysis using the

experimental data of single and binary system yielded the following correlation,

0.5490 1.8570Re 1.2790m m MAr (3.23)

The values of Rem as predicted by Eq. (3.23) have been plotted against the experimental

values as shown in Fig. 3.22. For single sized particles M = p , ρM = ρp, and dM = dp.

The ranges of variable in Eq. (3.23) are shown in Table 3.2.

Statistical Analysis of the correlation

The following statistical parameters have been calculated to test the significance

of the correlation. Sum of the squares of deviation removed by regression,

' 2 1192.66C

Residual sum of the squares of deviation, ' 21 19.05994F

Sum of the squares of deviation, ' 21 1211.72F

Correlation coefficient, 0.992104r

Variance of estimate, 2 21̂ 4.813115 10S F



Degrees of freedom = 396

Variation of regression coefficients,

2 2 51 11 1

2 2 22 22 1

2 2 33 33 1

ˆ 1.319458 10

ˆ 3.725638 10

ˆ 2.610195 10

S y C S F

S y C S F

S y C S F

The ‘t’ value for 0.05 probability level and 396 degrees of freedom as obtained from

statistical table is 1.98 (Volk, 1958). Therefore, 95% confidence ranges on the regression

coefficients are,

21 1 1

22 2 2

23 3 3

1.98 0.5490 0.0072

1.98 1.8570 0.3821

1.98 1.0227 0.1011

y y S y

y y S y

y y S y

Significance of the correlation by F test

For checking the significance of the correlation the Null hypothesis is used, i.e., it

is assumed that the correlation is not significant. The F value for the regression equation

is, 8285.795F . The value for 396 degrees of freedom at 0.01-probability level

obtained from statistical table is, 0.01 3,396 3.83F . Since 0.01 3,396F F= , the Null

hypothesis may be rejected and it may be concluded that the correlation, i.e., Eq. (3.23) is

highly significant at 99% confidence level.

3. 5.6 Comparison of the different method

The comparison is carried out with the existing equations available in the

literature. The condition for the minimum fluidization velocity is that the pressure drop

across the bed is equal to the net buoyant force per unit area. The phenomena at the

minimum fluidization condition the classical and inverse fluidized bed is same

(Renganathan and Krishnaiah, 2003) so the equation for minimum fluidization velocity in

classical fluidized beds is to be valid in the case of inverse fluidized bed. Renganathan

and Krishnaiah (2003) observed that the Wen and Yu (1966) is valid in both classical and

inverse fluidized bed. Similarly Yu et al. (1968) have been tired in the present case to



compare it validity. Table 3.3 presents the average absolute error and average relative

error for the Reynolds number at minimum inverse fluidization velocity by different

correlations as mentioned. The average absolute error and average relative error are

defined as

Average relative error

exp

exp

Re Re1100

Re

m m cal

m

RE XN

% (3.24)

Average absolute error

exp

1Re Rem m cal

AEN

(3.25)

It may be seen that the average relative error for the present correlation is

minimum and the discrepancy with the first correlation is the non-Newtonian nature of

the liquid used in the present study. Wen and Yu (1966), Richarson (1971), Grace (1982)

correlations are valid for Newtonian liquid flow and normal fluidization system. Yu et al.

(1968) is valid for normal fluidization using non-Newtonian liquids. 21.83% average

relative error observed with the experimental data. The other correlation are all for

inverse fluidization system using either Newtonian or non-Newtonian liquid system.

Ulaganathan and Krishnaiah (1996) correlation is valid only for spherical sized particles

and water as working fluid. Banerjee et al. (1999) correlation uses spherical, cylindrical

and disc type particles assuming sphericity is unity and water as working fluid. Vijaya

Lakshmi et al. (2000) uses spherical particle and non – Newtonian liquids for their

experiments. Table 3.2 clearly indicates that the Eq. (3.24) gives the best result.



Table 3.1 Typical experimental values of minimum inverse fluidization velocities

obtained from pressure drop graph and bed expansion graph

Sl No.

Column

diameter

m

SCMC

conc.

kg/m3

SolidSolid

weight

gm.

Minimum inverse

fluidization velocity from

pressure drop graph um

(m/s)

1 0.072 0.2 LDPE 1 200 0.00693

2 0.072 0.2 LDPE 1 400 0.006834

3 0.072 0.2 LDPE 1 600 0.006957

4 0.072 0.2 LDPE 1 800 0.006934

5 0.072 0.2 LDPE 1 1000 0.006854

6 0.072 0.4 LDPE 1 200 0.005701

7 0.072 0.4 LDPE 1 400 0.005612

8 0.072 0.4 LDPE 1 600 0.005545

9 0.072 0.4 LDPE 1 800 0.005692

10 0.072 0.4 LDPE 1 1000 0.005588

11 0.072 0.6 LDPE 1 200 0.004528

12 0.072 0.6 LDPE 1 400 0.004952

13 0.072 0.6 LDPE 1 600 0.004873

14 0.072 0.6 LDPE 1 800 0.004847

15 0.072 0.6 LDPE 1 1000 0.004658

16 0.072 0.8 LDPE 1 200 0.003391

17 0.072 0.8 LDPE 1 400 0.003411

18 0.072 0.8 LDPE 1 600 0.003321

19 0.072 0.8 LDPE 1 800 0.003589

20 0.072 0.8 LDPE 1 1000 0.003706

21 0.072 0.2 LDPE 2 400 0.005344

22 0.072 0.2 LDPE 2 600 0.005585



23 0.072 0.2 LDPE 2 800 0.005467

24 0.072 0.2 LDPE 2 1000 0.005348

25 0.072 0.4 LDPE 2 200 0.004663

26 0.072 0.4 LDPE 2 400 0.004469

27 0.072 0.4 LDPE 2 600 0.004505

28 0.072 0.4 LDPE 2 800 0.004897

29 0.072 0.4 LDPE 2 1000 0.004537

30 0.072 0.6 LDPE 2 200 0.003653

31 0.072 0.6 LDPE 2 400 0.003903

32 0.072 0.6 LDPE 2 600 0.003592

33 0.072 0.6 LDPE 2 800 0.003809

34 0.072 0.6 LDPE 2 1000 0.003603

35 0.072 0.8 LDPE 2 200 0.002911

36 0.072 0.8 LDPE 2 400 0.002982

37 0.072 0.8 LDPE 2 600 0.002939

38 0.072 0.8 LDPE 2 800 0.003038

39 0.072 0.8 LDPE 2 1000 0.002828

40 0.072 0.2 HDPE 200 0.006972

41 0.072 0.2 HDPE 400 0.006984

42 0.072 0.2 HDPE 600 0.006858

43 0.072 0.2 HDPE 800 0.006842

44 0.072 0.2 HDPE 1000 0.006821

45 0.072 0.4 HDPE 200 0.005282

46 0.072 0.4 HDPE 400 0.005102

47 0.072 0.4 HDPE 600 0.005187

48 0.072 0.4 HDPE 800 0.005272

49 0.072 0.4 HDPE 1000 0.005527

50 0.072 0.6 HDPE 200 0.003891

51 0.072 0.6 HDPE 400 0.00394



52 0.072 0.6 HDPE 600 0.003851

53 0.072 0.6 HDPE 800 0.003893

54 0.072 0.6 HDPE 1000 0.004653

55 0.072 0.8 HDPE 200 0.00244

56 0.072 0.8 HDPE 400 0.002523

57 0.072 0.8 HDPE 600 0.002711

58 0.072 0.8 HDPE 800 0.002635

59 0.072 0.8 HDPE 1000 0.002453

60 0.072 0.2 PP 200 0.006416

61 0.072 0.2 PP 400 0.006679

62 0.072 0.2 PP 600 0.006316

63 0.072 0.2 PP 800 0.006567

64 0.072 0.2 PP 1000 0.006483

65 0.072 0.4 PP 200 0.005096

66 0.072 0.4 PP 400 0.005166

67 0.072 0.4 PP 600 0.005139

68 0.072 0.4 PP 800 0.005049

69 0.072 0.4 PP 1000 0.004901

70 0.072 0.6 PP 200 0.003814

71 0.072 0.6 PP 400 0.003828

72 0.072 0.6 PP 600 0.003734

73 0.072 0.6 PP 800 0.003997

74 0.072 0.6 PP 1000 0.003795

75 0.072 0.8 PP 200 0.002568

76 0.072 0.8 PP 400 0.002631

77 0.072 0.8 PP 600 0.00265

78 0.072 0.8 PP 800 0.002807

79 0.072 0.8 PP 1000 0.003706



Table 3.2. Correlations obtained from literature

Sl.

NoCorrelation Equations System Range

i

Wen and

Yu (1966)

Correlation 7.330408.07.33Re 2 Arm

Solid-water

Classical

fluidization

Non-spherical

solid

5.08x10-5 ≤

dP ≤ 5.004

m

0.01 < Rem

< 1000

ii

Yu et

(1968)

correlation

2

2 1

9 3 112.5 Re

nn

m nm mn

m

nAr

Solid- non-

Newtonian

solution

Classical

fluidization

Non-spherical

solid

2.5x10-3 ≤

dP ≤ 9.0x

10-3m

0.81 ≤ n ≤

1

iii

Recharson

(1971)

correlation 7.250366.07.25Re 2 Arm

Solid-water

Classical

fluidization

Non-spherical

solid

0.01 < Rem

< 1000

iv

Grace

(1982)

correlation 2.270408.02.27Re 2 Arm

Solid-water

Classical

fluidization

Non-spherical

solid

0.01 < Rem

< 1000



v

Ulaganatha

n and

Krishnaiah

(1996)

correlation

0.383 0.2022.93 10 /m l p lu Ar

Solid-water

Solid – LDPE,

inverse

fluidization,

spherical

particles

106 < Arm <

7x107

0.4 <

/l p l

< 0.9

vi

Banerjee

et. al,

(1999)

Correlation

-6 1.513m mRe = 7.68 10 Ar

Solid-water

Solid – LDPE,

spherical,

inverse

fluidization ,

cylindrical and

disc shaped

particles

1.774 x104

≤ Arm ≥

2.651 x104

vii

Vijaya

Lakshmi

et. al

(2000)

Correlatio

n

-6 0.041m mRe = 1.139 10 Ar

Solid-non-

Newtonian

CMC solution,

inverse

fluidization,

Solid -

LDPE, PP,

Spherical

particles

0.002 < dP

< 00.008 m

0.00875 <

um <

0.0175 m/s



Table 3.3 Average Relative Error and Relative Absolute Error for Reynolds number at

minimum inverse fluidization velocity

Sl.

No.

Correlation Avg. Relative

Error

%

Relative

Absolute error

iWen and Yu (1966) Correlation 96.0461 0.7473

ii Yu et (1968) correlation 21.8324 0.7498

iii Recharson (1971) correlation 96.1420 0.7346

iv Grace (1982) correlation96.0129 0.7316

vUlaganathan and Krishnaiah (1996)

correlation76.1921

0.4942

viBanerjee et. al, (1999) Correlation 98.9713 0.7872

viiVijaya Lakshmi et. al (2000) Correlation 80.3342 0.9999

vii Eq. (3.23) 2.6221 0.0209



Pre

ssu

re d

rop

, N/m

2

Velocity, m/sFigure : 3.1 Plot of pressure drop vs velocity

0.00 0.01 0.02 0.03 0.04 0.05 0.06240

260

280

300

320

340

360

380

400

420

440

460

Pre

ssur

e d

rop,

N/m

2

Liquid velocity, uf , m/s

Figure : 3.2 Variation pressure drop across the bed with liquid velocity

Column Diameter : 0.072 mSolid : LDPE-1

SCMC Conc. : 0.2 kg/m3

Symbol Bed weight, gm 200

400 600 800 1000



0.00 0.01 0.02 0.03 0.04 0.05 0.06

250

300

350

400

450




400 600 800 1000

Pre

ssur

e d

rop,

N/m

2



0.00 0.01 0.02 0.03 0.04 0.05 0.06 0.07

250

300

350

400

450

500




400 600 800 1000

Pre

ssu

re d

rop

, N/m

2





0.00 0.01 0.02 0.03 0.04 0.05 0.06

250

300

350

400

450

500




400 600 800 1000

Pre

ssu

re d

rop

, N/m

2



0.00 0.01 0.02 0.03 0.04 0.05 0.06250

300

350

400

450

500

Pre

ssur

e d

rop,

N/m

2






600 800 1000



0.00 0.01 0.02 0.03 0.04 0.05 0.06240

260

280

300

320

340

360

380

400

420

440

460

480




400 600 800 1000

Pre

ssu

re d

rop

, N/m

2



0.00 0.01 0.02 0.03 0.04 0.05 0.06240

260

280

300

320

340

360

380

400

420

440

460

480




400 600 800 1000

Pre

ssur

e dr

op, N

/m2





0.00 0.01 0.02 0.03 0.04 0.05 0.06240

260

280

300

320

340

360

380

400

420

440

460

480

500




400 600 800 1000

Pre

ssur

e dr

op,

N/m

2



0.00 0.01 0.02 0.03 0.04 0.05 0.06 0.07240

260

280

300

320

340

360

380

400

420

440

460

480

500

520

Column Diameter : 0.072 mSolid : HDPE



400 600 800 1000

Pre

ssu

re d

rop

, N/m

2





0.00 0.01 0.02 0.03 0.04 0.05 0.06 0.07240

260

280

300

320

340

360

380

400

420

440

460

480

500

520

540




400 600 800 1000

Pre

ssu

re d

rop

, N/m

2



0.00 0.01 0.02 0.03 0.04 0.05 0.06240

260

280

300

320

340

360

380

400

420

440

460

480

500

520

540




400 600 800 1000

Pre

ssur

e dr

op, N

/m2





0.00 0.01 0.02 0.03 0.04 0.05 0.06240

260

280

300

320

340

360

380

400

420

440

460

480

500

520

540




400 600 800 1000

Pre

ssur

e d

rop,

N/m

2



0.00 0.01 0.02 0.03 0.04 0.05 0.06240

260

280

300

320

340

360

380

400

420

440

460

480

500

Column Diameter : 0.072 mSolid : PP



400 600 800 1000

Pre

ssu

re d

rop

, N/m

2





0.00 0.01 0.02 0.03 0.04 0.05 0.06240

260

280

300

320

340

360

380

400

420

440

460

480

500




400 600 800 1000

Pre

ssu

re d

rop

, N/m

2



0.00 0.01 0.02 0.03 0.04 0.05 0.06240

260

280

300

320

340

360

380

400

420

440

460

480

500

520




400 600 800 1000

Pre

ssu

re d

rop

, N/m

2





0.00 0.01 0.02 0.03 0.04 0.05 0.06240

260

280

300

320

340

360

380

400

420

440

460

480

500

520




400 600 800 1000

Pre

ssu

re d

rop

, N/m

2



Figure : 3.18 Variation of minimum inverse fluidization velocity with bed weight

200 400 600 800 1000 1200

0.002

0.004

0.006

0.008

0.010

0.012

0.014Solid : LDPE-1Column diameter : 0.072 m Symbol SCMC solution Conc.

kg/m3

0.2 0.4 0.6 0.8

Min

imum

inve

rse

fluid

izat

ion

velo

city

, u m

, m

/s

Bed weight, gm.



Figure : 3.19 Schematic diagram of variation of liquid velocity with bed porosity

Figure : 3.20 Variation of minimum inverse fluidization velocity with concentration of SCMC

-0.45 -0.40 -0.35 -0.30 -0.25 -0.20 -0.15 -0.10

-2.8

-2.6

-2.4

-2.2

-2.0

-1.8

-1.6

-1.4

B

log

u f

log

0.0 0.2 0.4 0.6 0.8 1.0

0.000

0.002

0.004

0.006

0.008

Concentration of SCMC solution, kg/m 3

Min

imum

inve

rse

fluid

izat

ion

velo

city

,um,

m/s

Column dia : 0.072 mSymbol Sample

LDPE - 1 LDPE - 2 HDPE PP



Figure : 3.21 Dependence of Rem on Archimedes number based on minimum

fluidization velocity for different correlation

Figure : 3.22 Variation of the calculated Rem with the experimental Rem

1E-6 1E-5 1E-4 1E-3 0.01 0.1 1 10 100

0.01

0.1

1

10

100

1000

Single component system Experimental; Wen and Yu (1966); Richardson (1971) Grace (1982); Banerjee et al. (1999); Vijaya Lakshmi et al. (2000) Ulaganathan and Krishnaiah (1996); Yu et al (1968); Calculated From Eq. (3.23) using

m=

s,

m=

pand d

m=d

p

Mod

ified

Arc

him

edes

num

ber,

Ar m

Reynolds number at minimum inverse fluidization velocity, Rem

1E-3 0.01 0.1 1 10

1E-3

0.01

0.1

1

10

Cal

cula

ted

Re m

Experimental Rem

single component system Binary component system


CONCLUSIONS

The hydrodynamics Characteristics of the two phase inverse fluidization bed were

experimentally investigated. The experiments were carried out for four particles of

spherical and non spherical polyethylene and polypropylene and with four different

aqueous solutions of SCMS solution as non-Newtonian liquid. For two phase inverse

fluidization system, the pressure drop increases initially with increasing liquid velocity,

beyond um, it remains almost constant. The um is independent of bed weight. Empirical

correlation has been developed to determine the minimum inverse fluidization velocity as

a function of physical and dynamic variables of the system and compared with existing

correlations. The comparison shows that the developed correlation gives satisfactory

results than that of different correlations obtained from literature.


NOMENCLATURE

Ar = Archimedes No. defined by dP3g(p -l )l/l

2 when p > l and by dP3g

(l -p )l/l2

CD = Particle Drag Coefficient.

D = Particle Diameter.

dP = Average Particle Diameter.

D = Column Diameter.

f = Drag Function for Multi particle system.

g = Acceleration due to Gravity.

Ga = Gallelio Number defined by gdp3 f

2/l2.

L = Distance between two pressure tapings in the column.

N = Exponent in Richardson and Zaki Correlation.

Rem = Particle Reynold’s Number at Minimum Fluidization Condition

U = Superficial Liquid Velocity.

Ui = The extrapolated value of U as approaches 1.

Umf = Minimum Fluidization Velocity.

Ut = Terminal Velocity of the solid particle.

Greek Letters

P = Pressure Drop across the Bed.

= Bed Porosity.o = Porosity of a Fixed Bed of Particles.

l = Liquid Viscosity.

l = Liquid Density.

P = Particle Density


REFERENCE

Biswas, S. K., U. P.Ganguly, A preliminary Study on the Voidage – Velocity

Relationship in Reverse Fluidization, Ind. Chem. Eng., 39 303-306 (1997).

Fan, L. S., K. Muroyama, S. H. Chern, Hydrodynamic Characteristics of Inverse

Fluidization in Liquid – Solid and Gas – Liquid – Solid Systems, Chem. Eng. J., 24 143-

150 (1981).

Bendict, F., G. Kumarsan, M. Velan, Bed expansion and pressure drop studies in a liquid-

solid inverse fluidized bed reactor, Bioprocess Eng., 19 137-142 (1998).

Howley, M. A., J. G. Benjamin, A comparison of one-dimensional traveling waves in

inverse and normal fluidized beds, Physica D: Nonlinear Phenomena, 201 177-198

(2005).

Karamanev, D. G., L. N. Nikolov, Bed Expansion of liquid – solid inverse fluidization,

AIChE J,, 38 1916-1922 (1992).

Karamanev, D. G., L. N. Nikolov, Influence of some physicochemical parameters on

bacterial activity of biofilm : Ferrous iron oxidation by Thiobacillus ferrooxidans,

Biotechnol. Bioengg., 31(4) 295-299 (1988).

Li, J., T. Nakazato, K. Kato, Effect of cohesive powders on the elutriation of particles

from a fluid bed, Chem. Eng. Sci 59, 2777-2782, (2004).

Oh, D. K., C. K. Hyun, J. H. Kim, Y. H. Park, Production of penicillin in a fluidized-bed

bioreactor: Control of cell growth and penicillin production by phosphate limitation,

Biotechnol. Bioengg., 32(4) 569-573 (1988).

Ramos, R.L., L.S. Fan, L.Lopez, Velocidad minima de fluidizacion en lecho fluidizado

invertido liquido-solido, Avances en Ingenicria Quimica, 7 148-155 (1999).


Renganathan, T., K. Krishnaiah, Liquid phase mixing in 2-phase liquid-solid inverse

fluidized bed, Chem. Eng. J,. 98 213-218 (2004).

Renganathan, T., K. Krishnaiah, Voidage characteristics and prediction of bed expansion

in liquid–solid inverse fluidized bed, Chem. Eng. Sci,. 60, 2545-2555, (2005).

Renganathan, T., K. Krishnaiah, Spatio-temporal evolution of void fraction in liquid–

solid inverse fluidized bed, Chem. Eng. Sci., 62, 328-338 (2007).

Sowmeyan, R. and G Swaminathan, Evaluation of inverse anaerobic fluidized bed reactor

for treating high strength organic wastewater, Bioresource Technology, 99 (9), 3877-

3880, (2008).

Sowmeyan, R. and G. Swaminathan, Effluent treatment process in molasses-based

distillery industries: A review, Journal of Hazardous Materials, 1, 453-462 (2008).

Sok´oł , W. and W. Korpal, "Aerobic treatment of wastewaters in the inverse fluidised

bed biofilm reactor", Chem. Engg. J., l 118 , 199–205 (2006).

Ulganathan, N., K. Krishnaiah, Hydrodynamic characteristics of two-phase inverse

fluidised bed, Bioprocess Eng,. 15 159-164 (1996).

Vijaya Lakshmi, A.C., M. Balamurugan, , M. Sivakumar, , T.N Samuel, M. Velan,

Minimum fluidization velocity and friction factor in a liquid-solid inverse fluidized bed

reactor, Bioprocess Eng.,. 22 461-466 (2000).

Wang D., T. Silbaugh, R. Pfeffer, Y.S. Lin, Removal of emulsified oil from water by

inverse fluidization of hydrophobic aerogels, Powder Technology J., 203 298–309 (2010)

Das, B., U. P. Ganguly, S. K. Das, Inverse fluidization using non-Newtonian liquids,

Chem. Engg. J., 49 1169–1175 (2010).

HYDRODYNAMIC STUDIES ON TWO PHASE INVERSE FLUIDIZATION USING NON NEWTONIAN FLUID

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