Polydispersity Model Development & Validation:

Report on Findings

NETL 2011 Workshop on Multiphase Flow Science

16 August 2011

Pittsburgh, PA

Ray Cocco

John Findlay

Roy Hays

SB Reddy Karri

Ted Knowlton

Jia-Wei Chew

Aaron Murray

Christine Hrenya

Sofiane Benyahia

Larry Shadle

Project Goals & 2006 Technology Roadmap

Theme: Particle Size Distribution (PSD)

1. Continuum Theory for the Solid Phase

2. Improved Gas-Particle Drag Laws

3. Gas-Phase Instabilities: Turbulence Models

4. Data Collection and Model Validation

5. Project Management

Theory and Model

Development

Physical and

Computational

Experiments

Communication,

Collaboration, and

Education

Relevant Tracks in 2006

Technology Roadmap

Project Scope: Work Breakdown Structure

Development, Verification, and Validation of Multiphase Models for Polydisperse Flows

Theory

Development

Data

Collection

Model

Validation

Program

ManagementDeliverables

1. Solid-Phase

Continuum

Theory

2. Gas-Solid

Drag

3. Gas-Phase

Turbulence

Simulations

Experiments

4.1 DEM (solids)

4.2 Eulerian-DEM

(gas-solid)

4.3 Low-velocity

fluidized bed

4.4 Cluster Probe

Development

1.1 Kinetic Theory

1.2 DQMOM

1.3 Incorporation of

KT and DQMOM

into MFIX

1.4 KT extension

to multiphase

2.1 LBM/DTIBM:

zero-mean vel.

2.2 LBM/DTIBM:

non-zero rel. vel.

2.3 LBM/DTIBM:

freely evolving

3.1 Polydisperse DNS

3.2 Multiphase Turb. Model

4.5 High-velocity

fluidized bed (PSRI)

4.6.1 Compare with

DEM data (4.1) and

low-velocity bed (4.3)

4.6.2 Liaison to NETL

riser data

4.6.3 Compare with high-

velocity data from

Eulerian-DEM (4.2),

PSRI (4.5), and

NETL (4.6.2)

5.1 Develop

Management PlanMonthly email updates

Quarterly reports

Annual reports

Final report

Approach

Scope

Cost Estimates

Schedule

Risk

Constraints

Assumptions

Communication

New theory into MFIX

Project Web Site:

http://www.psriextra.com/AR_

Polydispersity_Open/AR_Polydispersity_Open/Welcome.html

Experimental Setups

Colorado Bubbling Bed / “Dilute” CFB

PSRI “Dense” CFB

Particles

Colorado: sand

PSRI: glass beads and HDPE pellets

• Group B

• monodisperse, binary & continuous PSD’s

HDPE

dave= 650 μm

ρp = 900 kg/m3

Glass

dave = 170 μm

ρp = 2500 kg/m3

Experimental Measurements

Bubbling Bed (Colorado)

• Axial segregation:

vacuum slice, sieve, and weigh

• Bubble frequency, velocity & size:

optical dual-fiber probe

CFB (Colorado & PSRI)

• Species flux: extraction probe

• Cluster freq., duration, & appear. prob.: optical fiber probe

Comprehensive set of polydisperse data…

1. Chew, J. W., D. M. Parker, R. A. Cocco and C. M. Hrenya, “Cluster characteristics of continuous size

distributions and binary mixtures of Group B particles in dilute riser flow,” Chemical Engineering Journal,

submitted.

2. Chew, J. W., R. Hays, J. G. Findlay, T. M. Knowlton, S. B. R. Karri, R. A. Cocco and C. M. Hrenya,

“Cluster characteristics of Geldart Group B particles in a pilot-scale CFB riser. I. Monodisperse systems,”

Chemical Engineering Science, submitted.

3. Chew, J. W., R. Hays, J. G. Findlay, T. M. Knowlton, S. B. R. Karri, R. A. Cocco and C. M. Hrenya,

“Cluster characteristics of Geldart Group B particles in a pilot-scale CFB riser. II. Polydisperse systems,”

Chemical Engineering Science, submitted.

4. Chew, J.W., D. M. Parker, and C. M. Hrenya, “Elutriation and species segregation characteristics of

polydisperse mixtures of Group B particles in a dilute CFB riser,” AIChE Journal, submitted.

5. Chew, J. W., R. Hays, J. G. Findlay, T. M. Knowlton, S. B. R. Karri, R. A. Cocco and C. M. Hrenya,

“Reverse Core-Annular Flow of Geldart Group B Particles in Risers,” Powder Technology, submitted.

6. Chew, J. W., R. Hays, J. G. Findlay, T. M. Knowlton, S. B. R. Karri, R. A. Cocco and C. M. Hrenya,

“Impact of material property and operating conditions on mass flux profiles of monodisperse and

polydisperse Group B particles in a CFB riser,” Powder Technology, in press.

7. Chew, J. W., R. Hays, J. G. Findlay, T. M. Knowlton, S. B. R. Karri, R. A. Cocco and C. M. Hrenya,

“Species segregation of binary mixtures and a continuous size distribution of Group B particles in riser

flow,” Chemical Engineering Science, in press.

8. Chew, J. W. and C. M. Hrenya, “Link between bubbling and segregation patterns in gas-fluidized beds with

continuous size distributions,” AIChE Journal, in press.

9. Chew, J. W., J. Wolz, and C. M. Hrenya, “Axial segregation in bubbling gas-fluidized beds with Gaussian

and lognormal Distributions of Geldart group B particles,” AIChE Journal, 56, 3049-3061 (2010).

Bubbling Bed: Segregation and Bubbling

scont= 1 perfect segregationscont= 0 perfect mixing

• As distribution width , segregation then (binary: monotonic )

• As distribution width , all bubble characteristics

• Explanation: segregation level tied to thickness of bubble-less layer

lognormal PSD lognormal PSD

CFB: Axial Segregation

h /

HBinary Mixture Continuous PSD

Binary: As height , % of massive at some locations

Continuous: As height , % of massive at all locations

CFB: Cluster Frequency

• Axial position has large influence on profile

• Binary composition and continuous PSD width have impact at high h/H

CFB: ElutriationB

ina

ry M

ixtu

reC

on

tin

uou

sP

SD

Trends of binary and continuous appear similar, but x-axes are different…

elutriation

fines comp.

CFB: Elutriation w/ same x-axes

mass % of fine mass % of fine mass % of fine

Bin

ary

Mix

ture

Con

tin

uo

us

PS

D

• Elutriation trends of binary and continuous PSD’s are in stark contrast

• Explanation: as continuous width (mass % of fines ), dfine and elutriation easier

dsm increases

Aside: How well do kinetic theories predict continuous PSD‟s?

Basic Idea: How to accurately represent a continuous PSD using the

transport coefficients for „s‟ discrete species.

d1 d2

d1 d2 d3

d1 dn…

Fre

quency

s=2

σ1=? σ2=?

φ 1=? φ 2=?Q1: What method do we choose to find σ‟s

and φi‟s for given φ?

A1: moment-based methods=3

σ1=? σ2=? σ3=?

φ 1=? φ 2=? φ 3=?Q2: What value of „s‟ is required for

„accurate‟ representation of

continuous PSD?

A2: “collapsing” of transport coefficients

from new kinetic theory

(Garzo, Hrenya & Dufty, PRE, 2007)

Preliminary Answer…

Distributions investigated

• Lognormal ( /dave = 90%)

• NETL coal

• NASA lunar simulant (OB-1)

Comparison with MD data of

Dahl et al (Powder Tech, 2003)

• Simple shear flow

• Discrete approximation with 3

particles (s=3) provides similar

accuracy as monodisperse theory

Summary

• Binary and continuous PSD’s display different

qualitative trends

­ bubbling bed: axial segregation

­ CFB: axial segregation, elutriation

• Preliminary work indicates discrete kinetic theory can

approximate well a continuous PSD with a fairly small

number of size species