Sreekanth Pannala Computing and Computational Science Directorate Computer Science and Mathematics
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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) [email protected]
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