CFD of Fluidized Bed Considerations v1.2.key - CPFD Software

Applying the Fundamentals

Considerations for Simulating Fluidized Beds

Ray Cocco, Casey LaMarche, S.B. Reddy Karri, Ben Freireich

CPFD-Software User Group MeetingApril 9th, 2018


Abo

ut P

SRI


FCC Fluidized Bed Regenerator

Barracuda®Barracuda®


FCC Fluidized

Bed Regenerator

Barracuda®

Barracuda®


Status of CFD Modeling of Fluidized Beds

• Today’s CFD (CPFD) models are• Capturing macro-scaled hydrodynamics• Simulating large-scale, commercial equipment

• CFD models used for fluidized bed simulations are at the point that other factors need to be strongly considered• Accurate boundary conditions• Actual particle properties• Relevant drag model• Actual steady state

Steady State ???

Steady State ???


Accurate Boundary Conditions

• In the world of fluidized bed, it is unlikely your boundary condition is uniform

• Boundary conditions either need to• Reflect the actual non uniform spacial and temporal of

boundary in the fluidized bed, or• Be position such that the boundary condition has a

minimal effect on the solution

Barracuda®


Case Study: How Does Aeration Help Standpipe Flow

OutletOutlet

Angle

d Tra

nsiti

on

Pressure Taps

Aeration Taps

4’ (1.2 m) ID x 70’ (21 m) Standpipe

30’ (9.1 m) ID Fluidized Bed

400% Open Area Cone

Slide Valve

10’ (3 m) ID Mixing Pot

5’ (1.5 m) ID Riser

Pout = 101 KPa

Even though we only cared about the standpipe, the whole loop was simulated

UOP RxCat

PSRI Experimental Data


Effects of Aeration as Visualized with

Isovolumes With

100

% A

erat

ion

With

out A

erat

ion

Barracuda®

Solids volume fractions < 0.05


Symmetric Asymmetric

Fluidized Bed

Outlets

Vert

ical

Sta

ndpi

pe

Cone Inlet

Ris

er

Mixing Pot

Ang

led

Stan

dpip

e

Slide Valve @ 25%

Barracuda®

Outlets

Barracuda®

Symmetric vs. Asymmetric

Aeration


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0 20000 40000 60000 800000

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30

40

Pressure Drop, Pa

Height,m

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40

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100

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140

Pressure Drop, psi

Height,ft

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Asymmetric‡‡‡‡

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0 2 4 6 8 10 120

20

40

60

80

100

120

140

Pressure Drop, psi

Height,ft

Symmetric vs. Asymmetric Aeration


Case Study: How Do Vent Holes Improve Stripping

Catalyst Catalyst

Steam Steam

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Ê Without Vents

‡ With Vents

0 5 10 15 2010

20

30

40

50

Solids Flux from Circulation, lbmêft2-sBedDensity,lbmêft3

0.5 ft/sec Superficial Gas VelocityFCC eCat

2-ft Dia x 9-ft Tall Stripper6 Disk and Donut Trays


• Isovolumes indicate regions where solids volume fraction exceeds 0.3

• Color indicates axial particle velocity

• Highest solids volume fraction near disk and donuts

• Highest particle velocity is between the disk and donuts

Without Holes With “Holes”

Barracuda®

2-ft (0.6-m) Diameter

Mechanism Behind Flooding

Solids Flux of 9.2 lb/ft2-s (46 kg/m2-s)Gas Superficial Velocity of 0.5 ft/sec (0.15 m/sec)

Isovolumes for >0.3 Solids Volume Fractions


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Á

···

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·

0 100 200 300 400 500 600 7000

2

4

6

8

DPêL, kgêm^3

Height,meters

Ê 0.15 ftêsec & 45 kgêm2-sec CFD‡ 0.3 mêsec & 45 kgêm2-sec CFDÁ 0.15 mêsec & 52 kgêm2-sec Expermental· 0.3 mêsec & 46 kgêm2-sec Expermental

Bed Density Validation

Comparing bed densities at similar superficial gas velocities and at near flooding conditions

Flooding in the Experimental unit corresponded to a solids flux of 14 lbm/ft2-sec (68 kg/m2-sec) but in the CFD simulations it was at 9.2 lbm/ft2-sec

(45 kg/m2-sec).

2-ft (0.6-m) Diameter


A Better Way: Barracuda’s New BC Options

• Pressure Boundary Condition (BC) • Allows gas and entrained particles to exit

• Flow BC on cyclone dipleg face • Returns entrained particles via BC Connector • For cases with non-zero solids flux, this BC is also used to return bottom exit particles to the system • Interstitial gas also enters the domain

• Local injection BCs at gas distributor nozzles

• Flow BC at bottom of vessel • Only present for cases with non-zero solids flux • Particle out flow with “Particle Exit Control” • Desired solids flux is specified

Subway grating baffles are included in the

geometry as real CAD elements, and captured

by the computational mesh.

Simulation Boundary Conditions


Ug = 1.0 ft/s

With BC Flux

Control


Relevant Particle Properties

Particles are rarely perfectly round, smooth or mono dispersed

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0.0 0.2 0.4 0.6 0.8 1.0 1.2

200

300

400

500

600

700

800

Superficial Gas Velocity, m/sec

BedDensity,kg/m3

12% Fines

8% Fines

6% Fines

4% Fines

PSRI Data of FCC Catalyst in a 0.9-m Diameter Fluidized Bed

PSRI Experimental Data


Effects of Particle Size

0"

50"

100"

150"

200"

250"

1" 2" 3" 4"

dP#m

ean,#kg/m

3#

sampling#point#

mean#across#en5re#bed#

exptl"

sim"

0"

5"

10"

15"

20"

25"

1" 2" 3" 4"

dP#stde

v,#kg/m

3#

sampling#point#

Stdev#across#en5re#bed#

exptl"

sim"

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10"

20"

30"

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50"

1" 2" 3" 4"

dP#m

ean,#kg/m

3#

sampling#point#

mean#across#61#cm#

exptl"

sim"

0"

5"

10"

15"

20"

25"

30"

1" 2" 3" 4"

dP#stde

v,#kg/m

3#

sampling#point#

Stdev#across#61#cm#

exptl"

sim"

0.0"

1.0"

2.0"

3.0"

4.0"

5.0"

6.0"

0" 200" 400" 600" 800" 1000"

H,#m

#

dP/dL,#kg/m3#

mono"

exptl"

0.0#

1.0#

2.0#

3.0#

4.0#

5.0#

6.0#

0# 200# 400# 600# 800# 1000#

H,#m

#

dP/dL,#kg/m3#

exptl#

PB#

rev#PB#

175#180#185#190#195#200#205#210#215#220#

1# 2# 3# 4#

dP#m

ean,#kg/m

3#

sampling#point#

mean#across#en7re#bed#

exptl#

sim#

0#

5#

10#

15#

20#

25#

30#

1# 2# 3# 4#

dP#stde

v,#kg/m

3#

sampling#point#

Stdev#across#en7re#bed#

exptl#

sim#

0#

10#

20#

30#

40#

50#

1# 2# 3# 4#

dP#m

ean,#kg/m

3#

sampling#point#

mean#across#61#cm#

exptl#

sim#

0#

5#

10#

15#

20#

25#

30#

1# 2# 3# 4#

dP#stde

v,#kg/m

3#

sampling#point#

Stdev#across#61#cm#

exptl#

sim#

DQMOM


Gas Bypassing in Fluidized Beds

4

3

2

1

0Max

Bed

Hei

ght w

/o B

ypas

sing

, m

1412108642% Fines (< 44 µm)

0.3 meters Column DiaLight FCC Powder

Ug = 0.46 m/sec Ug = 0.61 m/sec


PSDs Matter with CFD

Simulations of Fluidized Beds

3% Fines, No Flux 9% Fines, No Flux 3% Fines with Flux 9% Fines with Flux

SolidsVolumeFraction

2 ft/sec (0.6 m/sec) Superficial Gas Velocity

Barracuda™


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0 50 100 150 2000

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4

6

8

dp, um

Diffwt%

9 wt%

3 wt%

Reported dp50, μm % Fines, (< 44 μm)

3 wt% 80.4 μm 2.7%

8 wt% 81.0 μm 8.6%

• Significant difference in hydrodynamics due to fines level, not median particle size.

• Fines are the driver for moving gas in and out of the emulsion phase• Higher mobility in dense bed• Higher surface to volume

ratio• There may be a lot more

fines in your particles than you think• 9 wt% = 33 num%

• If using one representative particle size, which one do you use?

Fines Matter!

3% Fines with Flux 9% Fines with Flux

SolidsVolumeFraction

Barracuda™


Effect of Drag on Fluidized Bed Simulations

• Drag dominates in fluidized beds and yet our drag laws are limited

Esmaili and Mahinpey (2011) Adv Eng Software

Experimental Data Various drag model predictions


Effects of Drag with

Fluidized Bed Simulations

Wen Yu x 0.63

Case 3 Case 5 Case 6 Case 7

Wen Yu x 0.8 Wen Yu x 1 Wen Yu x 1.5


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● CFD○ Data

0 200 400 600 8000

1

2

3

4

5

6

ΔL/lg, kg/m3

HeightAboveGrid,m

Bed Density (Ave from 34.9997 to 39.9997 Seconds)

Bed Density at High Velocity for Wen & Yu Drag

Model

Wen & Yu x 0.63Case 3B

Case 5B

Case 6B

Case 7B

Wen & Yu x 1

Wen & Yu x 0.8 Wen & Yu x 1.5

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0 200 400 600 8000

1

2

3

4

5

6

ΔL/lg, kg/m3

HeightAboveGrid,m


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0 200 400 600 8000

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2

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6

ΔL/lg, kg/m3

HeightAboveGrid,m

Bed Density (Ave from 35. to 40. Seconds)

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0 100 200 300 400 500 600 7000

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6

ΔL/lg, kg/m3

HeightAboveGrid,m


3-ft (0.9-m) Bed Diameter0.75 ft/sec (0.23 m/sec) Superficial Gas Velocity

BC at Sparger Exit


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0 200 400 600 8000

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2

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5

6

ΔL/lg, kg/m3

HeightAboveGrid,m


Bed Density at High Velocity for

EMMS Drag Model

Wen & Yu x 0.63Case 3B

Case 8B

EMMS x 1

Case 9B

EMMS x 0.5Case 10B

EMMS x 1.5

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ΔL/lg, kg/m3

HeightAboveGrid,m


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● CFD○ Data

0 200 400 600 8000

1

2

3

4

5

6

ΔL/lg, kg/m3

HeightAboveGrid,m


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0 100 200 300 400 500 600 7000

1

2

3

4

5

6

ΔL/lg, kg/m3

HeightAboveGrid,m


3-ft (0.9-m) Bed Diameter0.75 ft/sec (0.23 m/sec) Superficial Gas Velocity

BC at Sparger Exit


Well Established Drag Law Limits

Confident in single particle and packed bed drag laws, but not at intermediate Re and 𝜙 which is relevant to fluidized bed simulations

0 0.2 0.4 0.6100

102

104

106

Re

0 0.2 0.4 0.6100

102

104

106

Re

Carman-Kozeny Fd(Loading → Loading, Re → 0)

Single Particle Drag Fd(loading → 0, Re) Ergun Fd(loading → loadingmax, Re)

Fluidized Beds


Uncertainty in Drag Coefficient, CD

Uncertainty in CD measurements high at low Re

Fd(loading, Re) = C,D,single(Re) loadingn

What Do We Do?


Uncertainty in Drag Coefficient, CD

Uncertainty in CD measurements high at low Re

Fd(loading, Re) = C,D,single(Re) loadingn

Range of interest

What Do We Do?


Parameter Estimation using Umf/Umb Data

Wen Yu x 0.8Wen Yu x 1

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0.005 0.010 0.015 0.020 0.025 0.030 0.0350

10

20

30

40

50

60

16.16.517.17.518.18.519.19.520.

Superficial Gas Velocity, ftêsec

BedDensity,lbêft2

BedHeight,in

PSRI Umf/Umb Test Unit

We are basically fitting the drag model to the Umf/Umb data


It’s Not Just About Bed Density

• Column dimensions• 3 ft (0.9-m) diameter• 20 ft (6.1-m) tall

• 4 ft (1.2-m) static bed height• Entrainment rate determined from rate of fill in

primary cyclone dipleg• Heavy FCC catalyst• 70 micron dp50

• 1500 kg/m3 density○

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○

0.5 0.6 0.7 0.8 0.9 1.00.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7


EntrainmentFlux,kg

/m2-sec

Experimental Data

Particle Entrainment

For Geldart Group A Particles, Drag Models Over Predict the Entrainment Rates


Entrainment Fluxes

�� /�� /��-��

PSRI Cluster Size + Entrainment Flux

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●

△△▽ ▽

▽ ▽

▲

▲ ▲▲

★

★

★

★★

0.5 0.6 0.7 0.8 0.9 1.0 1.1

0.5

1

5

10


EntrainmentFlux,kg

/m2-sec

● Data

△ CPFD 0.8 Wen Yu

▽ CPFD 1.0 Wen Yu

▲ PSRI Drag

★ PSRI Correlation


Its Not Just CFD

Entrainment rate calculations based on FCC catalyst powder with 9% fines in a 3-meters ID x 12-meters tall fluidized bed with a bed height of 6 meters and superficial gas velocity of 1 m/sec at

room temperature

Stojkovski, V., Kostic’, Z., Thermal Science, 7 (2003) 43-58.Zenz, P.A., Weil, N.A., AIChE J., 4 (1958) 472-479.Lin, L, Sears, J.T., Wen, C.Y., Powder Technology, 27 (1980) 105-115.

M. Colakyan, N. Catipovic, G. Jovanovic, T.J. Fitzgerald, AIChE Symp. Ser. 77 (1981) 66.Colakyan, M., Levenspiel, O., Powder Technology, 38 (1984), pp. 223-232

Geldart, D., Cullinan, J., Georghiades, S., Gilvray, D., Pope, D.J., Trans. Inst. Chem. Eng., 57 (1979) 269-277.


This is a Fines Problem

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0.2 0.4 0.6 0.8 1.0 1.2 1.40

2

4

6

8

Superficial Gas Velocity, mêsec

EntrainmentFlux,kgêm

2 -sec

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0.6 0.8 1.0 1.2 1.40.0

0.5

1.0

1.5

2.0

2.5

3.0

Superficial Gas Velocity, mêsec

EntrainmentFlux,kgêm

2 -sec

Geldart Group B Cokeρp=1600 kg/m3

dp50 (Initial) =150 μmColumn Dia. = 0.3 mStatic Bed Height (Initial) = 0.76 m

With Baffles

Without Baffles

With Baffles

Without Baffles

Geldart Group A FCC Catalyst Powderρp=1490 kg/m3

dp50 (Initial) =90 μmColumn Dia. = 0.15 mStatic Bed Height (Initial) = 0.76 mBaffles at 0.5 and 0.76 m


Particle Drag and

Entrainment

Fluid FlowFluid Flow

�� /�� /�� /�� /�-��

Fluid Flow

dp = 50 microns dp = 100 microns dp,cluster = 100 micronsdp = 30 microns

0 50 100 150 200 250

100

200

500

1000

2000

Particle Size, microns

DragForce,N

eCat in a Bubbling Fluidized Bed


FCC Catalyst Particle Clusters in Freeboard

• 30% of the material in the freeboard was observed as clusters

• Average cluster size was equivalent to 11 particles of dp50 size

Phantom V7.1 @ 4000 fps, 20 μs exposure (NETL)

FCC powder with dp50 of 72 microns in 6-in (15-cm) ID

fluidized bed with superficial gas velocity of 1 ft/sec (0.3 m/

sec)


FCC Catalyst Particle Clusters in Freeboard

• 30% of the material in the freeboard was observed as clusters

• Average cluster size was equivalent to 11 particles of dp50 size

Phantom V7.1 @ 4000 fps, 20 μs exposure (NETL)

FCC powder with dp50 of 72 microns in 6-in (15-cm) ID

fluidized bed with superficial gas velocity of 1 ft/sec (0.3 m/

sec)

←200 μm Diameter


FCC Catalyst Clusters in the Fluidized Bed

• Cluster observed near bubble region

• Can not distinguished if clusters are in the emulsion phase or not

Phantom V7.1 @ 4000 fps, 20 μs exposure (NETL)FCC powder with dp50 of 72 microns in 6-in (15-cm) ID fluidized bed with superficial gas

velocity of 1 ft/sec (0.3 m/sec)

←50 μm Diameter


FCC Catalyst Clusters in the Fluidized Bed

• Cluster observed near bubble region

• Can not distinguished if clusters are in the emulsion phase or not

Phantom V7.1 @ 4000 fps, 20 μs exposure (NETL)FCC powder with dp50 of 72 microns in 6-in (15-cm) ID fluidized bed with superficial gas

velocity of 1 ft/sec (0.3 m/sec)

←50 μm Diameter←50 μm Diameter


Surface Morphology Driven

Royer, J.R., Evans, D.J., Oyarte, L., Guo, Q., Kapit, E., Möbius, M.E., Waitukaitis, S.R., Jaeger, H.M., High-Speed Tracking of Rupture and Clustering in Freely Falling Granular Streams, Nature 459 (2009) 1110-1113.

Glass Beads Copper Powder


Surface Roughness Matters

• The addition of Aerosil®, to roughen the surface, reduced the clustering of the glass particles

• Static interaction may have higher levels of attraction but in dynamics environments that may not be sufficient

• Particle momentum plays a role in particle clustering

Clean Glass Glass with Aerosil™


Electronic and Ionic Exchange

• \

V. Lee, S.R. Waitukaitis, M.Z. Miskin, H.M. Jaeger, Direct observation of particle interactions and clustering in charged granular streams, Nat Phys. 11 (2015) 733–737.

Large Particles

Small Particles

80% of the larger particles were positively charged while 95% of the smaller particles where negatively charged

S.R. Waitukaitis, V. Lee, J.M. Pierson, S.L. Forman, H.M. Jaeger, Size-Dependent Same-Material Tribocharging in Insulating Grains, Physical Review Letters. 112 (2014) 218001–5


Electronic and Ionic Exchange

S.R. Waitukaitis, V. Lee, J.M. Pierson, S.L. Forman, H.M. Jaeger, Size-Dependent Same-Material Tribocharging in Insulating Grains, Physical Review Letters. 112 (2014) 218001–5

Thermoluminescence Measurements

σ~1x10-4 um-2

Surface charge density, σ, is 5X lower than needed to explain the particle

mobility in the drop tube. Ionic exchange, such as OH-, may be

responsible with the glass beads

No Excitation

12 hrs Visible

12 hrs UV


Hydroxyl Ion and Clustering

• Pence et al. (1994) and McCarty et al. (2008) have noted the importance of water, and with it OH- ions, on the surface of particles for contact charging.

• Unless one prepares surfaces under ultra-high vacuum conditions, thin water layers are generally unavoidable.

• Indeed, even in a vacuum at 10-6 Torr, a molecularly thin layer of water adsorbs in one second, which is the definition of a Langmuir.

• On a zeolite, water is present on the surface at temperature exceeding 700°C


Particle Clusters in Freefall

Lee, V., Waitukaitis, S.R., Miskin, M.Z., Jaeger, H,M., Direct observations of particle interactions and clustering in charged granular streams, Nature Physics, 11, (2015) 733-737.


Momentum Exchange is Important Too

Near Capture Repulsion Rotational to Translational

Lee, V., Waitukaitis, S.R., Miskin, M.Z., Jaeger, H,M., Direct observations of particle interactions and clustering in charged granular streams, Nature Physics, 11, (2015) 733-737.


Hypothesis on Particle Clustering

+

-OH-

H+

OH-

H+

OH-H+

Long Range Attraction

Collision

Short Range Attraction

Collision and Collisional Cooling

Short Range Attraction

Clustering

+

-OH-

H+


Collision

Rotational Momentum ➔Translational Momentum

Clustering Unlikely+

-



Sub-grid Drag Models: Filtered

Filtered drag models based on simulations using homogenous drag models (mostly Wen and Yu)

Ultra-fine mesh simulations

Filtering regions

∆* ∆*

Developed filtered drag model


Heterogeneous (Sub-grid or Filtered) Models

Course mesh[1] Ultrafine mesh

Agrawal et al. (2001) J Fluid Mech

Homogenous drag: ultra-fine mesh required to resolve solids gradients of

instabilities

experimental data

sub-grid drag

homogenous drag

Sub-grid drag model improves upon (course-grid) homogenous drag model which over-predicts drag

Wang et al. (2010) Chem Eng Sci

However, clustering may not start with the drag


Sub-grid Drag Models: EMMSFlow separated into three phases

(phase c)

(phase d)

(phase cl)

Drag determined on each phase separately

Total power (F·u), minimized to close all unknowns introduced


Sub-grid Drag Models: EMMS

Drag force computed within each phase based on homogenous Wen and Yu drag model

Flow separated into three phases

Wen and Yu drag for each phase

(phase c)

(phase d)

(phase cl)

Drag determined on each phase separately

Total power (F·u), minimized to close all unknowns introduced


Sub-grid Drag Model Experimental Validation: EMMS

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Yang et al. (2003)Shah et al. (2011) (low flux)Shah et al. (2011) (high flux)Shah et al. (2011)Wang (2010)Lu et al. (2011) (group A)Lu et al. (2011) (group B)Hong et al. (2016)Chen et al. (2016)Qui et al. (2017)Song et al. (2016)Li et al. (2012)Qui et al. (2015)

For Entrainment, the drag needs to be fitted to the entrainment rate data



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Entrainment Fluxes

�� /�� /��-��

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PSRI Cluster Size + Entrainment Flux CFD Fitted to a Cluster Size

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△△▽ ▽

▽ ▽

▲

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★

★

★

★★

0.5 0.6 0.7 0.8 0.9 1.0 1.1

0.5

1

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10


EntrainmentFlux,kg

/m2-sec

Dp Correction

● Data

△ CPFD 0.8 Wen Yu

▽ CPFD 1.0 Wen Yu

▲ PSRI Drag

★ PSRI Correlation

Fitting Cluster Size


Concluding Remarks

• Boundary conditions need to be realistic or have a minimal dependance on the solution

• Particle properties need to go beyond the median particles size and particle density

• PSD, Shape, Adsorbate, Roughness!• Drag models are dragging down the capabilities of today’s CFD models for

fluidized bed simulations• All CFD models are limited for Geldart Group A and AC materials due to

particle clustering• This is not an issue for larger particles where clustering is unlike to happen

• With such limitations, calibration with experimental data is recommended• For fluidized beds, fitting drag to Umf/Umb and bed density data is a good start

CFD of Fluidized Bed Considerations v1.2.key - CPFD Software

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