CHEMICAL REACTION ENGINEERING LABORATORY CARPT Calibration Issues Poster 1 Bad Reconstruction...

CHEMICAL REACTION ENGINEERING LABORATORY

CARPT Calibration IssuesCARPT Calibration IssuesPoster 1

Bad Reconstruction

Calibration CurveCountsDis

tan

ce (

cms)

dE/d vs

0

0.2

0.4

0.6

0.8

1

1.2

1.4

0 100 200 300 400 500 600 700 800 900 1000

in mV

dE/d

det_9

Det_A

Det_K

Det_L

Det_M

Det_N

Det_O

Det_P

Det_Q

Det_R

Photo PeakCompton 0.89

Mev1.12 Mev

Full Spectrum

-8 -6 -4 -2 0 2 4 6 8-8

-6

-4

-2

0

2

4

6

8

r in cms

r in

cm

s

comparison of reconstructed vs actual calibration points in the entire column

2 Approach

Good Reconstruction

Proposed Solution to HPBCR

Acquire Photopeak

GoodCalibration Curve


Gas Liquid Studies in Stirred Tank ReactorGas Liquid Studies in Stirred Tank Reactor

• New techniques in CT implementation result in better reconstruction!!! How ???

• Cross sectional gas holdup distributions (at different axial planes) in a Stirred Tank Reactor (for the first time!!)

• Detailed local fluid dynamic information in gas-liquid flows in stirred tank (for first time!!)

N=100 rpm, QG=7.5 lit/min, Z=10.0 cms

2.3mm

1.0mm

0.8mm

250 m

150 m

Poster 2

Next Presentation

Poster II:Effect of Nozzle Orientation of the Cross Sparger Poster II:Effect of Nozzle Orientation of the Cross Sparger and Pressure on Bubble Columnand Pressure on Bubble Column HydrodynamicsHydrodynamics


Peter SpickaPeter Spicka• research associate research associate

at CREL since 2001at CREL since 2001• bubble columns, bubble columns,

trickle bedstrickle beds• CT & CARPT CT & CARPT

experimental experimental studies and CFD studies and CFD simulationssimulationsPoster I: Review of CARPT/CT Experimental Database Poster I: Review of CARPT/CT Experimental Database

for Bubble Columns Operating in the Churn-for Bubble Columns Operating in the Churn-Turbulent RegimeTurbulent Regime

Contributors: Jinwen Chen, Abdenour Kemoun, Sailesh Kumar, Shadi Saberi, Sujatha Degaleesan, Puneet

Gupta, Booncheng Ong, Shantanu Roy, Qingi H. Wang

Review of CARPT/CT Experimental Database for Bubble Columns Operating in the Churn-Turbulent Regime

-60.0

-40.0

-20.0

0.0

20.0

40.0

60.0

0.0 0.2 0.4 0.6 0.8 1.0r/R

Axi

ally

Ave

rag

ed A

xia

l Ve

loci

ty,

cm/s

Air-Water

Air-Drakeoil

Ug=10 cm/s

DOE project (1995-2002)DOE project (1995-2002)

Participants: Air Products, Ohio State University, Sandia National Laboratories and Washington University

Objectives:1. effect of specific variables on observed flow

patterns in bubble columns2. engineering type models for flow and mixing

in bubble columns3. data for gas hold-up, velocity and turbulence

profiles for validation of CFD codes

Different effects studied:• gas superficial velocity, liquid

properties, pressure• column diameter, internals, gas

distributor and solids concentration

Scale up of bubble columns:• correlations for liquid centerline

velocity, gas holdup, holdup and liquid velocity radial profiles and eddy diffusivities

Effect of Nozzle Orientation of the Cross Sparger and Pressure on Bubble Column Hydrodynamics

Experiment• 6” I.D. stainless steel column• cross-sparger, two nozzle

orientations: facing upward and downward

• Air-water system• Pressure: 1 bar and 4 bars• UG= 5 cm/s (only CT) and 20

cm/s

Nozzle orientation of the sparger

• important design issue since it may affect the length of the flow development region (Schollenberger et al., 2000)

• sparse information in the available literature

Goals• to quantitatively determine the variation of gas hold-up, liquid recirculation and

mixing due to variations in nozzle orientation and pressure • to compare the exp. data with 1-D recirculation model due to Kumar (1992)

-10

1r/R

2

4

6

8

x/D

0.400.360.320.280.240.200.160.120.080.040.00

Gas Holdup

U

z[c

m/s

]

0 0.2 0.4 0.6 0.8 1-60

-40

-20

0

20

40

60

exp., 1 barexp., 4 barsmodel, 1 barmodel, 4 bars

Gas holdup Liquid velocity profile

Next Presentation


Development of Improved Engineering Models for Flow, Development of Improved Engineering Models for Flow, Mixing and Transport in Bubble ColumnsMixing and Transport in Bubble Columns

(Review of Phenomenological Model accomplished in CREL during 1995-2001)(Review of Phenomenological Model accomplished in CREL during 1995-2001)

Tracer experiments during Methanol, Fischer-Tropsch and Dimethyl Ether Synthesis

Gas tracer: Ar41

Liquid tracer: Powdered oxide of Mn56 (Mn2O3)

suspended in the heat transfer oil

Solid tracer: Catalyst particles doped with an oxide of Mn56


ContentsContents

• Suitability of the Axial Dispersion Model• One Dimensional Recirculation Model• One Dimensional Recycle with Cross Flow and Dispersion Model• Two-Dimensional Convection-Diffusion Model• Gas Phase Recirculation and Dispersion Model• Scale-up Strategy• Comparison of experimental and simulated tracer responses

Level 3 (3.9 m)

0.0

0.2

0.4

0.6

0.8

1.0

0 20 40 60 80 100Time (sec.)

Nor

mal

ized

Res

pons

e

Sim.

Inj. 2

Inj. 3

Inj. 4

Inj. 5

Inj. 6

Inj. 7

0.0

0.2

0.4

0.6

0.8

1.0

0 20 40 60 80 100Time (Sec.)

No

rma

lize

d R

es

po

ns

e

Exp.

No Attenuation

With Attenuation

Level 13.5

•What is the next step?


Radioactive Tracer Studies in the AFDU Reactor during Radioactive Tracer Studies in the AFDU Reactor during Dimethyl Ether (DME) SynthesisDimethyl Ether (DME) Synthesis

W

N

S

E

Fresh Feed

0.46 m

Gas Tracer InjectionRecycle

Syngas In

Syngas/Products Out

DET

1.83m

2.74m

0.61m

1.74m

1.52m

1.52m

2.74m

2

1

3

4

5

6

7 DET

DET

DET

DET

DET

DET

DET

DET

13.25m

r/R = 0.6r/R = 0.35

24 tubes of 1” O. D.

DME Synthesis

Reactor Insulation

Reactor Wall

Down-flow of Gasand LiquidUp-flow of Gas and Down-

Flow of Liquid

Up-flow of Gasand Liquid

Detector

Lead Shielding

cross-section along with scintillation detectors and their lead shielding


Schematic of the reactor compartmentalization for the gas-Schematic of the reactor compartmentalization for the gas-liquid mixing model with interphase mass transfer (Gupta, 2001)liquid mixing model with interphase mass transfer (Gupta, 2001)

GG22 LL22GG11 LL11

Qg

Qg1Qg2

Cl1Cl2Cg1Cg2

Clb

ClaQl1Ql2

Cg, in

x = 0

x = L

Cgb

Cga

Ql Cl, in

Qg Ql

Level 3 (3.9 m)

0.0

0.2

0.4

0.6

0.8

1.0

0 20 40 60 80 100Time (sec.)

No

rma

lize

d R

es

po

ns

e

Sim.

Inj. 2

Inj. 3

Inj. 4

Inj. 5

Inj. 6

Inj. 7

Level 5 (9.4 m)

0.0

0.2

0.4

0.6

0.8

1.0

0 100 200 300 400 500 600

Time (sec.)

Nor

mal

ized

Res

pons

e

Simulation

Exp. (Inj. 3)

Exp. (Inj. 4)

Exp. (Inj. 5)

Level 6 (11.2 m)

0.0

0.2

0.4

0.6

0.8

1.0

0 100 200 300 400 500 600 700 800

Time (sec.)

No

rma

lize

d R

es

po

ns

e

Simulation

Catalyst (N2 Center)


Implementation of Breakup and Coalescence Models into CFD of Implementation of Breakup and Coalescence Models into CFD of Bubble Column FlowsBubble Column Flows

G

G

L

The engineering models needs input

Only Eulerian model seems feasible for churn turbulent flow regime

In churn turbulent regime, bubble size is widely distributed; the mean bubble diameter seems to be the simplest assumption

However, it is difficult to choose the “right” bubble diameter without going through tedious trial-and-error procedure

If one try to change to another column or operation condition, the “right” bubble diameter normally may not work any more

We need to predict rather than input bubble diameter, we had better predict it locally!

???

Next Presentation

Chemical Reaction Engineering Laboratory (CREL)

CFD Modeling of Bubble Column Flows(Review of CFD activities in CREL 1995-2001)

Gas Outlet

Gas Inlet

Gas Outlet

Gas Inlet

Bubbly flow regime Churn turbulent regime

Outline:•Hydrodynamics of bubble columns

•Eulerian-Eulerian Two-Fluid Model•Algebraic Slip Mixture Model (ASMM)

•Hydrodynamics of (passive) tracers (gas/liquid) in bubble column flows•Implementation of the Bubble Population Balance in CFD

Compiled by: M. Rafique•Research Associate•Ph.D. (Fluid Mechanics), INPL, France

Contributors:•Dr. M. P. Dudukovic•Dr. M. H. Al-Dahhan•Dr. S. Kumar•Dr. Y. Pan•Dr. M. Rafique•Mr. P. Chen

Acknowledgement: DOE Contract: DE FC 22 95 PC 95051


D=15.2 cm

0.2 cm

L=

10D

=15

2 cm

Ug =1cm/s

width

10 cm

D=15.2 cm

0.2 cm

L=

10D

=15

2 cm

Ug =1cm/s

width

10 cm

2D 3D

Mesh system &

Gas holdup contours

2D & 3D dynamic simulations


0 sec 2 sec 4 sec 6 sec 9 sec 19 sec

Numerical (liquid) Tracer Study Numerical particle tracking (calculation of turbulent diffusivities)


Meso-scale modeling of bubble column flows

M. Rafique, M. H. Al-Dahhan, M. P. Dudukovic

Objective: •To simulate the bubble column hydrodynamics by resolving meso-scale flow structures through grid refinement.•To study the effect of attraction and repulsion forces on the hydrodynamics

D=15.2 cm

0.2 cm

Ug=1cm/s

width

10 cm

D=15.2 cm

L =

110

cm

Ug=1cm/s

10 cm

Fin

e g

rid

(0

.2x

0.2

5 c

m)

Co

ars

e g

rid

(0

.5x

0.5

cm

)


Coarse gridCd+Cv

Fine gridCd+Cv

Fine gridCd+Cv+Catt

Instantaneous contours of gas volume fraction

Next Presentation

Optical Fiber Probes for Bubble DynamicsMeasurement in Bubble Columns

J. L. Xue, M. H. Al-Dahhan & M. P. Dudukovic

In cooperation withRobert F. Mudde

Delft University of Technology, The Netherlands


November, 2001


Measurement of Bubble Dynamics in BubbleColumns Using Four-point Optical Probe

J. L. Xue, M. H. Al-Dahhan & M. P. Dudukovic

In cooperation withRobert F. Mudde

Delft University of Technology, The Netherlands


Oct. 24, 2002


bubble dynamics, i.e. bubble size distribution, bubble velocity distribution, specific interfacial area and gas holdup are among the key parameters that affect the hydrodynamics in bubble columns.

Measurement of bubble dynamics is difficult, especially in churn-turbulent flows.

Non-invasive techniques, e.g. video imaging techniques, are limited to 2-D transparent columns. and can not be used in real 3-D systems which are opaque due to high volume fraction of the dispersed phase.

Optical probes can be applied in practical 3-D systems. The measurements of bubble dynamics by two-point probes are not reliable. Four-point optical probe was adopted in this research to measure the bubble dynamics in bubble columns.

Motivation


L

r

Probe

Tip0

Tip3

Tip1

Tip2

L

r

Probe

Tip0

Tip3

Tip1

Tip2

Tip1

Tip3 Tip2

Tip0

rr

r

Tip1

Tip3 Tip2

Tip0

rr

r

Bottom view

Side view

With a new data processing algorithm, it can measure:

Bubble velocity vector

Bubble size

Specific interfacial area

Gas holdup

The Configuration of the Four-point Optical Probe

Next Presentation

Computed Tomography

in

Slurry Bubble Column Reactors

Ashfaq Shaikh, M.H. Al-Dahhan


CREL Annual MeetingOctober 24, 2002

Acknowledgements: DE-FG-26-99FT40594

• Evaluate the CT/Overall gas holdup algorithm

Mimic fluid System: Therminol LT-air-glass beads (150 m)

Single source CT Two-phase systems

Three-phase systemsOne equation, two unknowns

Need one more equation


CT/Overall gas holdup (Rados, 2002)

Sensitivity analysis

Assumptions in CT/Overall gas holdup procedure has been critically examined

Next Presentation

Assessing and Reinforcing the Phenomenological Assessing and Reinforcing the Phenomenological Consistency of Multiphase Flow Artificial Neural Consistency of Multiphase Flow Artificial Neural

Network CorrelationsNetwork Correlations L.A. Tarca, B.P.A. Grandjean, F. Larachi

Classically built ANN models may be phenomenological consistent in vicinity of some data points but not in the whole input space Large prediction errors

800

1000

1200

1400

1600

1800

2000

3.0E-03 8.0E-03 1.3E-02

L(kg/m.s)

D P

/Z (P

a/m

)0

200

400

600

800

1000

1200

1400

1600

1800

2000

0 0.5 1 1.5

Gas superficial velocity, UG (m/s)

Irri

ga

ted

pre

ss

ure

dro

p, D

P/Z

(P

a/m

)

Liquid Viscosity

(r L = 1150 kg/m3)

f - L = 1 cP

D - L = 10 cP

O - L = 20 cP

(d)

Piché et al. (2001) [3]Counter-current packed bed

0)/(

1

D

pL

ZP

0

)/(

2

D

pL

ZP

,,,,Re,,Re/ BLLLGG SStGaGaANNZP D

L

Using phenomenological error (PCE) of the trained models we guide a Genetic Algorithm search for pertinent dimensionless numbers to predict a reactor characteristic

otherwise

a

yyy

U

y

U

yif

fkkkkk

k

pTpLpGpLpG

PCp

0

0)(

&0)(

&0)(

&0)(

&0)(

1

r

T

k

PCp

N

fPCE

k

1100[%] Phenomenological Consistency Error

Phenomenological and prediction error decrease by combining multiple “good” ANNs

g

ZPy

Lr/D

Pressure drop in counter-current packed

beds

……

bm1

…

…

bm2

……

bm3

1

2

3

gZP

Lr/D

UG

UL

rG

L

aT

Z

DC

rL

L,G

log

log

log ^10

N10N13N14N18N23N26N27

N9N10N13N14N21N24N27

N10N14N17N18N24N27

……

bm1

…

…

bm2

……

bm3

1

2

3

UG

UL

rG

L

aT

Z

DC

rL

LG

log

log

log ^10

N10N13N14N18N23N26N27

N9N10N13N14N21N24N27

N10N14N17N18N24N27

THEORY OF TRICKLE BED MAGNETOHYDRODYNAMICS IN INHOMOGENEOUS MAGNETIC FIELDS – Potential route to process intensification by I. Iliuta and F. Larachi

0

6000

12000

18000

24000

-1000 -500 0 500 1000

BdB/dz (T2/m)

P/H

, Pa/

m

Liquid velocity=0.007 m/sLiquid velocity=0.002 m/s

(b)

FMg+

FMl-

FMg-

FMl+

0

0.05

0.1

0.15

0.2

0.25

0.3

-1000 -500 0 500 1000BdB/dz, T2/m

L

Liquid velocity=0.007 m/s

Liquid velocity=0.002 m/s

(a)

FMg+

FMl-

FMg-

FMl+

When magnetic gradients are negative,liquid holdup decreases with increasing|BdB/dz| because the driving force (two-phase pressure drop) increases

- for negative magnetic gradients, the upward gas magnetization force reduces the effect of gravity (sub or micro-gravity) and two-phase pressure drop increases

When magnetic gradients are positive, liquid holdup increases with increasing |BdB/dz| because the driving force decreases

-for positive magnetic gradients, gas magnetization force amplifies the effect of gravity (macro-gravity) and two-phase pressure drop is reduced

rG=47

kg/m3

rG=1.2

kg/m3

0.4

0.48

0.56

0.64

0.72

-100 0 100 200 300 400 500 600 700

BdB/dz, T2/m

Phe

nol c

onve

rsio

n

0.2

0.4

0.6

0.8

1

Wet

ting

effic

ienc

y

vSL=0.001 m/svSG=0.0283 m/sCP,0=0.01 mol/l

(a)

0.4

0.5

0.6

0.7

0.8

0.9

-100 0 100 200 300 400 500 600 700

BdB/dz, T2/mP

heno

l con

vers

ion

0.2

0.4

0.6

0.8

1

Wet

ting

effic

ienc

y

vSL=0.0005 m/svSG=0.0283 m/sCP,0=0.01 mol/l

(b)

Elevated levels of magnetic field gradient improve the liquid holdup and thus the wetting efficiency of the catalyst particle

Because phenol oxidation is liquid-reactant limited, as catalyst wetting improves the phenol conversion increases significantly

Prediction of HETP for randomly packed tower operation: Prediction of HETP for randomly packed tower operation: Integration of aqueous and non-aqueous mass transfer Integration of aqueous and non-aqueous mass transfer characteristics into one consistent correlationcharacteristics into one consistent correlation

Simon PICHÉ, Stéphane LÉVESQUE, Bernard GRANDJEAN, Faïçal LARACHIDepartment of chemical engineering & CERPICQuébec, CANADA G1K 7P4

L

G

L

G

S

POLLUTION CONTROL: Particulate removal, SO2, NOX, VOC & TRS scrubbing

WATER PURIFICATION: Ammonia stripping and recovery, VOC stripping

DISTILLATION: Styrene purification (Ethylbenzene - Styrene separation)

(Vacuum or Pressure) Demethanizers (ex: CH4 removal / heavy feedstock)

OBJECTIVE: Build a new, efficient & consistent correlation using

an artificial neural network, dimensionless analysis & data (HETP,

KGaW, KLaW) reconciliation procedure that could predict either HETP

for distillation or kGaW, kLaW, KGaW & KLaW for absorption and stripping

DATABASE: 3770 absorption/stripping measurements

2357 distillation measurements

(1) Testing of ANN correlations developed for aqueous solutions [1] on HETP (non-aqueous solutions)

(2) Extraction of pseudo interfacial areas from HETP and mass transfer coefficients

(with previously developed ANN-k) & development of new interfacial area correlation (ANN-aW)

(3) Weights reconciliation on the 6 mass transfer parameters (HETP, aw, kLaw, kGaw, KLaw, KGaw)

General procedure and Results

ANN-kI

k (cal)

aw (pseudo)

(5,802 data)

aw (exp)

(325 data)

ANN-aw(3)

ANN-aw(3) & ANN-k

I weights reconciliation

HETP, KLaw, KGaw, kLaw, kGaw, aw (6,127 data)

ANN-awII ANN-k

II

HETP, Kaw & kaw (exp)

(5,802 data)

ANN-awI & ANN-k

I testing on HETP

= 76%, = 100%

[1] Piché, S., Larachi, F. & Grandjean, B., Reconciliation procedure for gas-liquid interfacial area and mass transfer coefficient in randomly packed towers, Ind. Eng. Chem. Res., 41 (19) (2002) 4911-4920 .

ANN STRUCTURES: = G (gas) and L (liquid)

[1] aw/aT = f (ReL, FrL, EoL, wall factor, ) – ANN-awI

k/(aTD) = f (Re, Fr, Sc, ) – ANN-kI

This work

aw/aT = f (ReL, FrL, EoL, wall factor, RSI) - ANN-awII

k/(aTD) = f (Re, Fr, Sc, ) – ANN-kII

RSI (Relative stability index) = (dL/dxvol) / L(mixture)

RSI=0 (aqueous solutions); RSI<>0 (non-aqueous

mixtures)

STATISTICAL PERFORMANCE:

HETP (N=2357, =21%); aW/aT (N=325, =24%);

kLaW/kGaW (N=1461, =23%); KLaW/KGaW (N=1984,

=29%)

Next Presentation


Modelling of Radioactive Tracer Distribution in Bubble Columns

bbyy

Chengyu MaoChengyu Mao

Advisor: Prof. M.P. DudukovicAdvisor: Prof. M.P. Dudukovic

Prof. P.A. RamachandranProf. P.A. Ramachandran


Liquid Recirculation Model

Recycle with Cross Flow and Dispersion Model (RCFDM)

Single Bubble Class Model (SBCM)

Distributed Bubble Size Model (DBSM)

Two Dimensional Convection with Eddy Diffusion Model

Many engineering models are available for description of flow, mixing, and transport in bubble columns. However, their accuracy to simulate and predict experimental data needs to be verified.


Single Bubble Class Model (SBCM)

Two Dimensional Convection with Eddy Diffusion Model

Liquid tracer concentration distribution

Method 1

Calculate Cross-Sectional concentration, normalize and compare with data

Method 2

Calculate 2D Response accounting approximately for the attenuation of radiation, normalize and compare with data

Method 3

Calculate 3D Response accounting fully for the attenuation of radiation, normalize and compare with data

Next Presentation

Liquid MaldistributionLiquid Maldistributioninin Trickle Bed Reactors Trickle Bed ReactorsExperimental and CFD Modeling StudyExperimental and CFD Modeling Study

M.P. Dudukovic, M.H. Al-Dahhan, P. SpickaChemical Reaction Engineering Laboratory, Washington University

St Louis, USA

D. Védrine, J. BousquetCentre Européen de Recherche et Technique, TOTALFINAELF

Harfleur, FRANCE

Nicolas DromardMaster in Process Engineering, INPL, Nancy, FRANCE

Chemical and Process Engineer, ENSIC, Nancy, FRANCE

Liquid Maldistribution in TBRsLiquid Maldistribution in TBRs

• An Experimental Study• How to quantify maldistribution?• Determination of the parameters

responsible for maldistribution

• A step to CFD modeling• Generate a pseudo random

porosity profile

x (mm)

y(m

m)

-60 -40 -20 0 20 40 60

-60

-40

-20

0

20

40

60 31.0

28.0

25.1

22.1

19.2

16.2

13.3

10.3

7.4

4.4

1.5

Exit liquid distribution

UL = 8 mm.s-1 & UG = 0.1 m.s-11 Flux in kg.m-2.s-1

r

0.950.910.880.840.800.760.720.680.650.610.570.530.490.460.420.380.340.300.260.230.190.150.110.070.04

Pseudo RandomPorosity Profile

R(column center)

0(wall)

Z

0(bottom)

L(top)

?

Next Presentation

Multiphase Packed-bed Reactor Modeling

Jing GuoCREL Annual Meeting, 2002 Dr. M. H. Al-Dahhan

MotivationScale up of packed bed:

Simulation vs huge amount of experimental work

? How to choose multiple level model for reaction system of interest

Understand and compare the hierarchy of model for catalytic multiphase packed-bed reactorsCapture the time-dependent reaction features of catalytic wet oxidation in packed beds

Objective

outputinput

C0, usL

Xa, C, usL,

Reactor scale

Completely actively wetted

Completely inactively wetted

Half wetted

Pellet scale


Combination of Reactor and Pellet Scale Model

C i, N

C i, N-1

C i, j

C i, 2

C i, 1

C i, 0

Rea

c tor

Sca

le

El-Hisnawi Model

Ci,jDry side Wet sidePellet scale

Beaudry Model

El-Hisnawi Model

Beaudry Model

Predict axial concentration

distribution

Refine local effectiveness factor

Predict catalyst local performance


I:reactant componentJ:Cell sequence

Rea

ctor

Axi

s

Pellet scale

Ul, Ug

Reactionwet oxidation of phenol

over deactivating catalyst

Active site distribution after 110 hours

Next Presentation

New CT Setup and studies on Gas-Liquid Hold-up in Structured Packing

using CT

Shaibal RoyMuthanna Al-Dahhan

Main difference between the old and new CT

Resolution Characteristics of new CT setup

Gas Liquid Flow Characteristics (hold-up and pressure drop) in a 12 inch

Structured packing

Poster 1

4”

4"

Guide for the source

Plate 1

Plate 2

A Study of Structured Packing for Solid Catalyzed Gas-Liquid Reaction

Shaibal RoyMuthanna Al-Dahhan

Structured Packing for solid catalyzed gas-liquid reaction provides

Large Volumetric productivity Lower pressure drop Excellent mass transfer properties Higher selectivity (low axial dispersion, short

diffusion length scale) Ease of scale-up

Motivation

Poster 2

Research Objective

The overall objective of the proposed study is to develop better

understanding

and fundamentally based model for comparison of structured packing (e.g.

Monolith and other selected configuration) with conventional reactors for

multiphase reactionsResearch Goal

Apparent Kinetic model with extrudates

And washcoated monolith

Hydrodynamic aspects in structured packing

Combined effects in overall performance of structured packing for multiphase reactions

Compare with conventional packed bed

reactor

Develop model for performance prediction

Next Presentation


A Non-Invasive Method for Overall Solids Flux Measurements A Non-Invasive Method for Overall Solids Flux Measurements in a Circulating Fluidized Bed (CFB)in a Circulating Fluidized Bed (CFB)

Satish Bhusarapu, Pascal Fongarland,

M. H. Al-Dahhan and M. P. Dudukovic’

CREL Annual MeetingCREL Annual MeetingOctober 24, 2002October 24, 2002

Chemical Reaction Engineering Laboratory

Department of Chemical Engineering

St.Louis, MO 63130


6” Column

Disengagementaxisymmetric

section

Deflector plate

Filterunit

Downcomer

18’ Length

2” Diameter26’ Riser

Challenge : How to measure overall solids mass flux Challenge : How to measure overall solids mass flux accurately in a CFB ?accurately in a CFB ?

Obtain solids velocity and concentration in a standpipe where solids hold up is high

• Solids velocity – “time of flight” measurements – track a single radioactive tracer using a two detector set-up

• Solids concentration – -ray line densitometry

Overall solids flux at varying operating conditions

Next Presentation

Photobioreactors for Culturing High Value Microalgae and Cyanobacteria: Experimentation and Modeling


Hu-Ping Luo, Muthanna Al-DahhanChemical Reaction Engineering Laboratory (CREL)

Washington University

CREL ANNUAL MEETING October 24, 2002

http://www.ust.hk/iscre17/contact.htm


Cells’ growth depends on their movement

radius, r, (cm)x, cm

y, c

m

Wall or internals

Split Column

Spiral movements, time scale: 1 s

In Nonlinear and Dynamic Systems, results are determined by the process

A cell’s movement in the reactor determines its accessibility to the light, nutrients, the shear stress

need to endure, etc.

Feeding to the cells is irregular in bioreactors, especially for light

Light distribution


Dynamic approach for photobioreactor analysis

Challenge: How to combine the knowledge of: Physiology of photosynthesis processReactor hydrodynamic

Current approaches: use Static kinetic model for bio-reactions, take into account only average light intensity (effects of hydrodynamic are ignored)

Our new approach: combines dynamic kinetic model for bio-reactions with hydrodynamic information via CARPT experimental technique.

Please stop at my poster, I’ll show you all the details 0

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0 50 100 150 200 250 300

Time, hr

Cel

l co

nce

ntr

atio

n (

*10

6 c

ell/m

l)

EXP

Simulation of Wu

Ug=5 cm/s (this work)

Ug=1 cm/s (this work)

Next Presentation

FLOW PATTERN IMAGINGINSIDE A SIMULATED ANAEROBIC DIGESTER

USING CARPT AND CT

Washington University Group: Rebecca Hofmann, Mehul Vesvikar, Rajneesh Varma, Khursheed Karim, Muthanna Al-Dahhan

Oak Ridge National Lab. Group: Thomas Klasson, Alan Wintenberg, Chuck Alexander, David Depaoli


ANIMAL WASTE :Environmental Perspective ANIMAL WASTE :Environmental Perspective and motivation for Treatmentand motivation for Treatment

More than one billion tons of animal waste generated every year in the USA.

Unsafe and improperly disposed

– Surface & groundwater contamination – Ammonia leaching– Methane emission– Odors

Methane = Energy source, hence animal waste = renewable energy source

Biomass has applications of fertilizer and land fill

High failure rate observed in digesters that is attributed to mixing related problems

Effects of hydrodynamics and mixing in anaerobic bioreactors needs investigation.

Objective of The Present Work

To demonstrate the ability of single particle CARPT technique to visualize 3D flow patterns inside a simulated digester.

To determine the gas phase hold-up of the three phase anaerobic system using single source CT.


Next Presentation

Modeling of Catalytic Partial Oxidation Reactors

R.C. Ramaswamy, P.A. Ramachandran& M.P. Dudukovic

CREL Annual MeetingOctober 24, 2002


Catalytic Partial Oxidation of Methane to Syn-gas

CH4 & O2

(2:1)

Tin ~773 K

H2/CO < 2;

CO2 & H2O

Texit ~ 1300 K

Exo. rxn. &Endo. rxn.

A schematic of syn-gas packed bed reactor

Synthesis Gas (mixture of CO and H2)• Feed stock to chemical process industries• Feed stock to Syn-fuels, H2 for fuel cells


Reactions :1) Exothermic Combustion Reaction2) Endothermic Steam Reforming Reaction3) Slightly Exothermic Water Gas Shift Reaction

Mathematical models are required for design, control and optimization purposes

Next Presentation

Transport and Capture of Particles in Magnetic FieldsPrakash Kumar

Advisors: Prof. Pratim Biswas, Prof. M. P. Dudukovic

2. Setup to study the particle transport Magnetic fields.

1. Model to predict the particle trajectories in magnetic fields.

10-7

10-6

10-5

10-10

10-8

10-6

10-4

10-2

100

diameterj (m)co

llisi

on fr

eque

ncy(

cm3 /s

ec)

capture efficiency based on total no concentration vs gap(based on 4 runs)

Gap between magnet and the tube, Zgap(mm)0 5 10 15 20 25

Ove

rall

capt

ure

efiic

ienc

y

0.0

0.1

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ExperimentalModel

3

0

22395.0

ji

jimangetic dd

ddM

Brownian (Friedlander 1964)

(Magnetic)

3. Comparison of theoretical and experimetal results.

4. Effect of magnetic fields on particle aggregation.

The End

CHEMICAL REACTION ENGINEERING LABORATORY CARPT Calibration Issues Poster 1 Bad Reconstruction...

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