<span class="var-sub_title">Large Scale MPI-Parallelization of LBM and DEM Systems: Accelerating Research by Using HPC</span> SC18 Proceedings

The International Conference for High Performance Computing, Networking, Storage, and Analysis

Large Scale MPI-Parallelization of LBM and DEM Systems: Accelerating Research by Using HPC

Authors: Bohumir Jelinek (Mississippi State University), George Mason (Mississippi State University), John Peters (Mississippi State University), Daniel Johnson (Mississippi State University), Marcus Brumfield (Mississippi State University), Alex Carrillo (US Army Engineer Research and Development Center), Clay Goodman (Mississippi State University), Farshid Vahedifard (Mississippi State University)

Abstract: Casting, solidification, and the behavior of dry, saturated, and partially saturated granular media are examples of interesting and important problems in multiple areas of civil, mechanical, and chemical engineering. For interacting particle-fluid systems, the Discrete Element Method (DEM) and Lattice-Boltzmann Method (LBM) provide valuable high-resolution numerical models. Their main issue is high computational demand, which can be addressed by use of HPC resources. This work demonstrates the use of MPI-parallelized LBM and DEM models to accelerate research in solidification and macroscopic behavior of dry and saturated granular media. Large scale parallel simulations of dendritic growth, the calibration-chamber cone penetration test, and a parametric study of shear thickening in granular suspension were performed. Use of HPC dramatically reduced the computational time for these studies and provided high-resolution representation of physical experiments.

Best Poster Finalist (BP): no

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