Presented by

Micro-Mesoscopic Modeling of Heterogeneous Chemically Reacting Flows (MMMHCRF) Over Catalytic/Solid Surfaces

Sreekanth PannalaComputing and Computational Science Directorate

Computer Science and Mathematics

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Goal

Develop a multiphysics and multiscale mathematics framework for accurate modeling of heterogeneous reacting

flows over catalytic surfaces

Develop a multiphysics and multiscale mathematics framework for accurate modeling of heterogeneous reacting

flows over catalytic surfaces

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Flow over a catalyst surface

Lattice Boltzmann (LBM) Kinetic Monte Carlo (KMC) Density Functional Theory (DFT)Closelycoupled

Reactionbarriers

Figure adapted from Succi et al., 2001

Chemically reactive flow over a surfaceis a basic building block which is centralto many energy-related applications

Illustrative benchmark to demonstrate the capabilityto integrate scales of several orders of magnitude

QM: ~1 nmKMC: ~1 mLBM: ~1 mm

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Approach: KMC–LBM couplingthrough Compound Wavelet Matrix

Construct a CWM from LBM and KMC Use CWM for coupling of mesoscopic and

microscopic simulations in time and space Use a Multiple Time Stepping (MTS) algorithm

for higher order accuracy in time Use fractal projection to map the surface

topographical information to constructthe KMC in one less dimension

KMC contribution

LBM contribution

Compound WaveletMatrix (CWM)

x-yyy

x

x

x

Fractalprojection

Actualsurface

KMC

LBM

t viqi

viqiTx

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Increasing spatial or temporal scalesIncreasing spatial or temporal scales

Homogenization at the level corresponding

to LBM, feedingfrom KMC to LBM

CWM methodology in work:Transferring information from KMC to LBM

Micro-informationKMC

Homogenized properties at next scale

Wavelettransformation

Objective:Develop algorithmsto construct projection operators and time integration methods to connect the microscale (e.g., KMC) and the mesoscale (e.g., LBM)

The interactions between various physical processesat different scales are encapsulated by CWM and can be employed in control and design of reacting surfaces

Time separation between methods and scalessimplifies the problem

The method recovers the mean field behaviorin the macroscopic limit

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Recent results*

1D reaction/diffusion simulation performedat two different length and time scales Fine (KMC and diffusion equation using finite difference

at fine scale) Coarse (analytical species solution and diffusion equation

using finite difference at coarse scale)

Reconstructed the fine simulation results to reasonable accuracy using CWM at fraction of cost

Method allows for bi-directional transfer of information, i.e., upscaling and downscaling

*Frantziskonis et al. (under review)

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100 200 300 4000

1020304050

*Frantziskonis et al. (under review)

Recent results*

Successfully applied CWM strategyfor coupling reaction/diffusion system

A very unique, rigorous, and powerful way to bridge temporal and spatial scales for multiphysics/multiscale simulations

Transferring mean field

Transferring fine-scale statistics

Sp

ecie

s co

nce

ntr

atio

n

A(0

k,t)

20 40 60 80 100 1200

20

40

60

80

100

Time, t

Coarse

Fine

Time, t

A(0

k,t)

100 200 300 4000

1020304050

Transferring mean field

25 500 100 2000

1020304050

A(0

k,t)

Time, t

CWMreconstruction

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Applications

Chemical looping combustion (CLC)

Efficient,low-emissionsand amenableto CO2 sequestration

SCOT (staged combustion with oxygen transfer)

CLC adaptedfor transportation

Polyethylene production

Important processwhich uses ~10%of crude petroleum

Reactiveflows through fibrous media

Light-weight,low-cost and high- strength composites

Fuel cell components Scaffolds for

biomedicalapplications

Coal gasification and combustion

New technologiesfor cleaner andefficient coalcombustion

Fibrous substrate for discontinuous fiber substrate The voids found by probing the substrate

with a fixed-size sphere are denoted by spheres

Schematic of burning of coalparticle using laser heating in

microgravity environment showingthe various regimes of combustion

[Adapted from Wendt et al., 2002]

Coal particle

radiation z

p

z

aa

r

a

b

Gas phaseGas phase

Gas flow in the charGas flow in the char

Pyrolysis frontPyrolysis front

Not yet reacted coalNot yet reacted coal

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Spouted bed coater (device scale)

Coated fuel particle(small scale)

• 0.5- to 1-mm particles • Coating encapsulates

fission products• Failure rate < 1 in 105 • Quality depends on surface

processes at nm length scale and ns time scales

Links multiscale mathematics

with petascale computingand GNEP

Links multiscale mathematics

with petascale computingand GNEP

Design challenge:Maintain optimal temperatures, species, residence times in each zone to attain right microstructureof coating layersat nm scale

Truly multiscale problem: ~O(13) time scales,~O(8) length scales

• Coating at high temperature (1300–1500°C) in batch spouted bed reactor for ~104 s

• Particles cycle thru deposition and annealing zones where complex chemistry occurs

~10-3 m

~10-1 m

UO2

~10-3 m

Pickup zone (~10-6-10-2s)

Pickup zone (~10-6-10-2s)

Si-CSi-C

Inner Pyrolitic C

Inner Pyrolitic C

Amorphous CAmorphous C

KernelKernel

Additional applications:Nuclear fuel coating process

Ballistic zone

Pickup zone (~10-6-10-2s)

Pickup zone (~10-6-10-2s)

Transportreaction zone

(~10-6-10-2s)

Transportreaction zone

(~10-6-10-2s)

Hopperflow

zone (~s)

Hopperflow

zone (~s) Inlet gas

Going forward

Extend the methodologyto multiple spatial dimensions

Couple the KMC with LBM simulator

Develop error measuresand error control strategies

Implement the multiscale frameworkinto highly scalable parallel environment

Apply the developed frameworkto the targeted applications

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The Team

Sreekanth Pannala

Srdjan Simunovic

StuartDaw

PhaniNukala

Oak RidgeNational

Laboratory

Rodney Fox

George Frantziskonis

SudibMishra

PierreDeymier

Thomas O’Brien

DominicAlfonso

MadhavaSyamlal

Ames LaboratoryIowa State University

Universityof Arizona

National Energy Technology Laboratory

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ORNL contact

Sreekanth PannalaOak Ridge National Laboratory(865) 574-3129pannalas@ornl.gov

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