Adaptive coarse-graining for large-scale DEM simulations

Description

The large time and length scales and, not least, the vast number of particles involved in industrial-scale simulations inflate the computational costs of the Discrete Element Method (DEM) excessively. Coarse-grain models can help to lower the computational demands significantly. However, for effects that intrinsically depend on particle size, coarse-grain models fail to correctly predict the behavior of the granular system. To solve this problem we have developed a new technique based on the efficient combination of fine-scale and coarse grain DEM models. The method is designed to capture the details of the granular system in spatially confined sub-regions while keeping the computational benefits of the coarse grain model where a lower resolution is sufficient. To this end, our method establishes two-way coupling between resolved and coarse grain parts of the system by volumetric passing of boundary conditions. Even more, multiple levels of coarse-graining may be combined to achieve an optimal balance between accuracy and speedup. This approach enables us to reach large time and length scales while retaining specifics of crucial regions. Furthermore, the presented model can be extended to coupled CFD-DEM simulations, where the resolution of the CFD mesh may be changed adaptively as well.

Period	30 May 2017
Event title	12 th International Conference on Computational Fluid Dynamics in the Oil & Gas, Metallurgical and Process Industries
Event type	Conference
Location	NorwayShow on map