A semi-resolved CFD–DEM approach for particulate flows with kernel based approximation and Hilbert curve based searching strategy

Abstract

Particulate flow has a wide range of industrial applications and is frequently modeled with coupled CFD–DEM approaches. Herein, we first identified a simulation gap between the resolved CFD–DEM and unresolved CFD–DEM through a size effect study. Then we analyzed the error sources of the conventional unresolved CFD–DEM when modeling particulate flows with comparable mesh size and particle diameter. We finally developed a semi-resolved CFD–DEM model, which combines the advantages of both resolved and unresolved CFD–DEM models. The semi-resolved CFD–DEM uses a drag force model to characterize particle–fluid interaction, while the relative velocity in the drag force model is corrected through kernel-based approximations on the neighboring fluid cells rather than simply taking values in the local cell containing the concerned particle, and the void fraction in the force model is corrected as well. In order to improve the computational efficiency, a Hilbert curve based searching strategy is used to identify the fluid cells covered by the influencing area of the kernel function. A number of numerical simulations have been conducted and numerical results from different CFD–DEM approaches are compared together with experimental data. It is shown that the presented semi-resolved CFD–DEM bridges the simulation gap between the resolved CFD–DEM and unresolved CFD–DEM while it is as efficient as the conventional unresolved CFD–DEM and as accurate as the resolved CFD–DEM.