Sreekanth Pannala Computing and Computational Science Directorate Computer Science and Mathematics

1. Micro-Mesoscopic Modeling of Heterogeneous Chemically Reacting Flows (MMMHCRF) Over Catalytic/Solid Surfaces Sreekanth Pannala Computing and Computational Science DirectorateComputer Science and Mathematics

2. Goal Develop a multiphysics and multiscale mathematics framework for accurate modeling of heterogeneous reactingflows over catalytic surfaces

3. QM: ~1 nm Flow over a catalyst surface • 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 KMC: ~1 m LBM: ~1 mm Lattice Boltzmann (LBM) Kinetic Monte Carlo (KMC) Density Functional Theory (DFT) Closelycoupled Reactionbarriers Figure adapted from Succi et al., 2001

4. 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) algorithmfor higher order accuracy in time • Use fractal projection to map the surface topographical information to constructthe KMC in one less dimension y x-y y KMC contribution LBM viqi T x Compound Wavelet Matrix (CWM) x LBM contribution t viqi KMC x Fractalprojection Actualsurface x

5. CWM methodology in work:Transferring information from KMC to LBM Wavelettransformation Micro-informationKMC Homogenized properties at next scale Homogenization at the level correspondingto LBM, feedingfrom KMC to LBM Increasing spatial or temporal scales

6. Recent results* • 1D reaction/diffusion simulation performedat two different length and time scales • Fine (KMC and diffusion equation using finite differenceat fine scale) • Coarse (analytical species solution and diffusion equationusing 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)

7. Recent results* 100 50 50 80 • 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 CWMreconstruction 40 40 Transferring mean field Transferring mean field Coarse 60 Species concentration A(0k,t) 30 30 A(0k,t) 20 20 40 Fine 10 10 0 0 20 100 100 200 200 300 300 400 400 Time, t 0 20 40 60 80 100 120 50 Time, t Transferring fine-scale statistics 40 30 A(0k,t) 20 10 0 25 500 100 200 Time, t *Frantziskonis et al. (under review)

8. Applications • Fibrous substrate for discontinuous fiber substrate • The voids found by probing the substratewith a fixed-size sphere are denoted by spheres a a a  r b p radiation z z Coal particle Gas phase Schematic of burning of coalparticle using laser heating in microgravity environment showingthe various regimes of combustion[Adapted from Wendt et al., 2002] Gas flow in the char Pyrolysis front Not yet reacted coal

9. Additional applications:Nuclear fuel coating process Spouted bed coater (device scale) Coated fuel particle (small scale) • 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 ~10-1 m Amorphous C Si-C Ballistic zone Kernel UO2 Inner Pyrolitic C Transportreaction zone (~10-6-10-2s) ~10-3 m Hopperflowzone (~s) Pickup zone (~10-6-10-2s) Pickup zone (~10-6-10-2s) ~10-3 m Links multiscale mathematicswith petascale computingand GNEP • 0.5- to 1-mm particles • Coating encapsulatesfission products • Failure rate < 1 in 105 • Quality depends on surface processes at nm length scale and ns time scales Inlet gas • 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. 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 10 Pannala_MM_0611

11. The Team Oak RidgeNationalLaboratory National Energy Technology Laboratory Ames LaboratoryIowa State University Universityof Arizona Sreekanth Pannala Srdjan Simunovic StuartDaw PhaniNukala Rodney Fox George Frantziskonis SudibMishra PierreDeymier Thomas O’Brien DominicAlfonso MadhavaSyamlal

12. ORNL contact Sreekanth Pannala Oak Ridge National Laboratory (865) 574-3129 pannalas@ornl.gov 12 Pannala_MM_0611