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Towards Large Multi-scale Particle Simulations with Conjugate Heat Transfer on Heterogeneous Super Computers

In: High Performance Computing in Science and Engineering ‘14

Author

Listed:
  • Gonzalo Brito Gadeschi

    (RWTH Aachen University, Institute of Aerodynamics)

  • Christoph Siewert

    (RWTH Aachen University, Institute of Aerodynamics)

  • Andreas Lintermann

    (RWTH Aachen University, Institute of Aerodynamics)

  • Matthias Meinke

    (RWTH Aachen University, Institute of Aerodynamics)

  • Wolfgang Schröder

    (RWTH Aachen University, Institute of Aerodynamics)

Abstract

We present numerical methods based on hierarchical Cartesian grids for the simulation of particle flows of different length scales. These include Eulerian-Lagrangian approaches for fully resolved moving particles with conjugate heat-transfer as well as one-way coupled Lagrangian particle models for large-scale particle simulations. The domain decomposition of all phases involved is performed on a joint hierarchical Cartesian grid where the individual cells can belong to one or more sub-grids discretizing different physics, such that numerical methods can operate independently on these sub-sets of the joint mesh to solve, e.g., the Navier-Stokes equations, the heat equation, or the particle motion. Due to the wide range of length scales involved, we first demonstrate the scalability of our automatic mesh generation approach. We then proceed to detail the method for fully-resolved particle simulation and the first steps towards its porting to heterogeneous supercomputers. Finally, we detail the parallelization strategy for the particle motion used by large scale one-way Lagrangian particle simulations.

Suggested Citation

  • Gonzalo Brito Gadeschi & Christoph Siewert & Andreas Lintermann & Matthias Meinke & Wolfgang Schröder, 2015. "Towards Large Multi-scale Particle Simulations with Conjugate Heat Transfer on Heterogeneous Super Computers," Springer Books, in: Wolfgang E. Nagel & Dietmar H. Kröner & Michael M. Resch (ed.), High Performance Computing in Science and Engineering ‘14, edition 127, pages 307-319, Springer.
    • Handle: RePEc:spr:sprchp:978-3-319-10810-0_21
    DOI: 10.1007/978-3-319-10810-0_21
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