Coarse-grained DEM simulation for mixing and segregation of binary-sized particles

Abstract

While the Discrete Element Method (DEM) are promising tools for analyzing and predicting powder mixing and segregation, the DEM simulation of large-scale powder handling processes remains computationally challenging. To address this issue, we developed a Coarse-Grained (CG) method for granular shear flow (CGSF). Considering the CGSF has been applied exclusively for monodisperse particles with homogeneous particle sizes, an extended CG model for particles with inhomogeneous properties under a granular shear flow is required. As segregation progresses, microscopic particle mixing and segregation can occur on a smaller scale than the CG particle size. Hence, a new method is proposed by which the composition of the original intra-CG particles can change dynamically. Consequently, we propose a coarse-grained model for powder mixing and segregation under dense granular shear flow by extending the CGSF to a binary-sized particle system and developing a method for estimating the microscopic mixing and segregation of the original particles based on the Dynamically Changing Composition (DCC) of the original particles. Using the extended CGSF with DCC, we simulated the powder mixing and segregation of binary-sized particles in a rotating drum, with the performance of the proposed model evaluated in terms of powder mixing, segregation behavior, and computing speed.