Parallel algorithms for CFD–DEM modeling of dense particulate flows

• 3D parallel CFD–DEM algorithms have been developed for dense particulate flows.
• We propose implicit two-phase coupling scheme to enhance numerical stability.
• We introduce multi-threading to overcome load-balancing difficulties.
• We propose an efficient algorithm to handle data-exclusive access by multithreads.

Most of the CFD codes are parallelized under distributed-memory parallel computing environments. For this reason, many attempts have been made to develop parallel DPM/DEM algorithms for dense particulate flows under the same parallel architecture. For such a development, it is very difficult to achieve efficient load balancing of processors due to the heterogeneous particle spatial distribution that often characterizes dense particulate systems. In this work, parallel CFD–DEM algorithms have been developed under the distributed memory environment with a fluid flow solver based on finite volume method and arbitrary 3D unstructured meshes. An implicit two-phase coupling scheme was proposed to enhance numerical stability for complex dense particulate flow problems. Parallelization-generated numerical difficulties such as void fraction calculation, two-phase momentum exchange, and contact force calculations for particles at irregular and arbitrary partition boundaries were efficiently addressed. The load-balancing difficulty due to heterogeneous particle distribution was partly overcome by the introduction of multi-threading. An efficient algorithm is proposed to handle data-exclusive access of the shared-memory by multi-threads on a compute node. The developed parallel DPM model has been successfully used to simulate many important applications such as bubbling fluidized bed, granular Rayleigh–Taylor instability, and particle swarm dynamics.

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