Volume 9, Issue 2
Algorithms in a Robust Hybrid CFD-DEM Solver for Particle-Laden Flows

Heng Xiao & Jin Sun

Commun. Comput. Phys., 9 (2011), pp. 297-323.

Published online: 2011-09

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  • Abstract

A robust and efficient solver coupling computational fluid dynamics (CFD) with discrete element method (DEM) is developed to simulate particle-laden flows in various physical settings. An interpolation algorithm suitable for unstructured meshes is proposed to translate between mesh-based Eulerian fields and particle-based Lagrangian quantities. The interpolation scheme reduces the mesh-dependence of the averaging and interpolation procedures. In addition, the fluid-particle interaction terms are treated semi-implicitly in this algorithm to improve stability and to maintain accuracy. Finally, it is demonstrated that sub-stepping is desirable for fluid-particle systems with small Stokes numbers. A momentum-conserving sub-stepping technique is introduced into the fluid-particle coupling procedure, so that problems with a wide range of time scales can be solved without resorting to excessively small time steps in the CFD solver. Several numerical examples are presented to demonstrate the capabilities of the solver and the merits of the algorithm.

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@Article{CiCP-9-297, author = {}, title = {Algorithms in a Robust Hybrid CFD-DEM Solver for Particle-Laden Flows}, journal = {Communications in Computational Physics}, year = {2011}, volume = {9}, number = {2}, pages = {297--323}, abstract = {

A robust and efficient solver coupling computational fluid dynamics (CFD) with discrete element method (DEM) is developed to simulate particle-laden flows in various physical settings. An interpolation algorithm suitable for unstructured meshes is proposed to translate between mesh-based Eulerian fields and particle-based Lagrangian quantities. The interpolation scheme reduces the mesh-dependence of the averaging and interpolation procedures. In addition, the fluid-particle interaction terms are treated semi-implicitly in this algorithm to improve stability and to maintain accuracy. Finally, it is demonstrated that sub-stepping is desirable for fluid-particle systems with small Stokes numbers. A momentum-conserving sub-stepping technique is introduced into the fluid-particle coupling procedure, so that problems with a wide range of time scales can be solved without resorting to excessively small time steps in the CFD solver. Several numerical examples are presented to demonstrate the capabilities of the solver and the merits of the algorithm.

}, issn = {1991-7120}, doi = {https://doi.org/10.4208/cicp.260509.230210a}, url = {http://global-sci.org/intro/article_detail/cicp/7501.html} }
TY - JOUR T1 - Algorithms in a Robust Hybrid CFD-DEM Solver for Particle-Laden Flows JO - Communications in Computational Physics VL - 2 SP - 297 EP - 323 PY - 2011 DA - 2011/09 SN - 9 DO - http://dor.org/10.4208/cicp.260509.230210a UR - https://global-sci.org/intro/article_detail/cicp/7501.html KW - AB -

A robust and efficient solver coupling computational fluid dynamics (CFD) with discrete element method (DEM) is developed to simulate particle-laden flows in various physical settings. An interpolation algorithm suitable for unstructured meshes is proposed to translate between mesh-based Eulerian fields and particle-based Lagrangian quantities. The interpolation scheme reduces the mesh-dependence of the averaging and interpolation procedures. In addition, the fluid-particle interaction terms are treated semi-implicitly in this algorithm to improve stability and to maintain accuracy. Finally, it is demonstrated that sub-stepping is desirable for fluid-particle systems with small Stokes numbers. A momentum-conserving sub-stepping technique is introduced into the fluid-particle coupling procedure, so that problems with a wide range of time scales can be solved without resorting to excessively small time steps in the CFD solver. Several numerical examples are presented to demonstrate the capabilities of the solver and the merits of the algorithm.

Heng Xiao & Jin Sun. (2020). Algorithms in a Robust Hybrid CFD-DEM Solver for Particle-Laden Flows. Communications in Computational Physics. 9 (2). 297-323. doi:10.4208/cicp.260509.230210a
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