Validation of pressure drop prediction and bed generation of fixed-beds with complex particle shapes using discrete element method and computational fluid dynamics

Abstract

Catalytic fixed-bed reactors with a low tube-to-particle diameter ratio are widely used in industrial applications. The heterogeneous packing morphology in this reactor type causes local flow phenomena that significantly affect the reactor performance. Particle-resolved computational fluid dynamics has become a predictive numerical method to analyze the flow, temperature, and species field, as well as local reaction rates spatially and may, therefore, be used as a design tool to develop new improved catalyst shapes. Most validation studies which have been presented in the past were limited to simple particle shapes. More complex catalyst shapes are supposed to increase the reactor performance. A workflow for the simulation of fixed-bed reactors filled with various industrially relevant complex particle shapes is presented and validated against experimental data in terms of bed voidage and pressure drop. Industrially relevant loading strategies are numerically replicated and their impact on particle orientation and bed voidage is investigated.