Parallel algorithms for CFD-DEM modeling of dense particulate flows

C. L. Wu*, Oladapo Ayeni, A. S. Berrouk, K. Nandakumar

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

53 Scopus citations


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 languageEnglish
Pages (from-to)221-244
Number of pages24
JournalChemical Engineering Science
StatePublished - 18 Oct 2014
Externally publishedYes


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


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