Comparison of sub-grid drag laws for modeling fluidized beds with the coarse grain DEM–CFD approach

Abstract

Fluidized particulate systems can be well described by coupling the discrete element method (DEM) with computational fluid dynamics (CFD). However, the simulations are computationally very demanding. The computational demand is drastically reduced by applying the coarse grain (CG) approach, where several particles are summarized into larger grains. Scaling rules are applied to the dominant forces to obtain precise solutions. However, with growing grain size, an adequate representation of the interaction forces and, thus, representation of sub-grid effects such as bubble and cluster formation in the fluidized particulate system becomes challenging. As a result, particle drag can be overestimated, leading to an increase in average particle height. In this work, limitations of the system-to-grain ratio are identified but also a dependency on system width. To address this issue, sub-grid drag models are often applied to increase the accuracy of simulations. Nonetheless, the sub-grid models tend to have an ad hoc fitting, and thorough testing of the system configurations is often missing. Here, five different sub-grid drag models are compared and tested on fluidized bed systems with different Geldart group particles, fluidization velocity, and system-to-grain diameter ratios.