## Abstract

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.

Original language | British English |
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Pages (from-to) | 221-244 |

Number of pages | 24 |

Journal | Chemical Engineering Science |

Volume | 118 |

DOIs | |

State | Published - 18 Oct 2014 |

## Keywords

- Computational fluid dynamics
- Dense particulate flow
- Discrete element method
- Load balancing
- Parallel algorithm