A CPU-GPU cross-platform coupled CFD-DEM approach for complex particle-fluid flows. (21st September 2020) - He, Yi; Muller, Frans; Hassanpour, Ali; Bayly, Andrew E.
Highlights: CFD solver is coupled with a stand-alone GPU-based DEM via network communication. Communication overhead is insensitive to the number of particles being simulated. A dual-grid approach is proposed for data mapping between Eulerian and Lagrangian properties. This coupling scheme can handle large-scale, general-purposed industrial applications. DEM calculation is no longer the computational bottleneck for a coupled CFD-DEM simulation. Abstract: High computational cost presents a significant barrier to the general application of coupled computational fluid dynamics and discrete element method (CFD-DEM) simulations, especially so for industrial systems with a large number of particles and complex geometries. In this study, a new cross-platform coupling approach is developed by integrating a CFD solver with a standalone GPU-based DEM solver via network communication. Consequently, the two modelling techniques benefit from the most appropriate hardware architecture. The developed coupling approach shows predictions comparable to experiments on a small-scale fluidized bed. Its computational performance is evaluated on a larger fluidized bed and shows superior performance over the CPU-based parallelization methods, making DEM calculation no longer the computational bottleneck. Its general applicability to handle complex geometrical domains is further demonstrated by simulations of a gas-solid cyclone separator. This work demonstrates the benefits of a novel coupling approach which enables efficient and robust solutions for industrial applications.