S. Pannala
Oak Ridge National Laboratory
Computer Science and Mathematics Division
Bldg 6012, Room 101
Phone: (865) 574-3129
Fax: (865) 574-0680
e-mail: pannalas@ornl.gov
http://www.csm.ornl.gov/~pannala

Research Interests:

Sreekanth Pannala is a Senior R&D Staff Member in the Computational Mathematics Group in the Computer Science and Mathematics Division. Sreekanth specializes in the development, implementation, and application of reacting multiphase flow methods for massively parallel computers to a variety of practical applications in chemical, aerospace, nuclear and fossil industries. His interests include multiscale and multiphysics coupling of heterogeneous chemically reacting flow simulations, parallel multiphase Direct Numerical Simulations and Large Eddy Simulations for dense fluidized bed reactors with applications in chemical, fossil, and nuclear industries, and simulations for emissions reduction and efficiency enhancement for automotive and aerospace applications. He is also one of the main developers for MFIX software suite (http://www.mfix.org) which is used by over 1500 researchers from over 500 research establishments around the world. He is part of the MFIX team which received 2006 Mid Atlantic Regional award of Federal Laboratories Consortium’s Technology Transfer Award and also the coveted R&D 100 award for 2007.

Selected current research themes include:

  • Heterogeneous catalysis – Development and implementation of multiscale and multiphysics algorithms for hierarchically modeling heterogeneous catalysis coupled with flow.
  • Catalytic/Chemical reactor modeling and simulation – Development of both highly detailed and low-order computational models of catalytic reactors with laminar or turbulent reacting flows and single or multi-phase heat, mass, and momentum transfer.
  • Multiphase Flow Models – Development, verification, and validation of Direct Numerical Simulations and Large Eddy Simulations of multiphase flows.
  • High Performance Computing – Development of efficient and scalable computational algorithms that can exploit large-scale simulation platforms.
  • Chemical Vapor Deposition (CVD) – Development and application of models for coating nuclear fuel particles and silicon based CVD processes.
  • Mesoscale and Microscopic Models – Development and application of mesoscopic flow modeling tools based on Lattice Boltzmann Methods (LBM and kinetic Monte Carlo (KMC) based simulation tools for modeling microscopic chemical reactions.

 





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