Modeling Gas–Solid Flows in Circulating Fluidized Bed Risers Using Computational Fluid Dynamics

The present work focuses on the advanced modeling and simulation of gas–solid flows in circulating fluidized bed (CFB) risers using computational fluid dynamics (CFD). Gas–solid flows play a crucial role in various industrial processes, particularly in the recovery of heavy petroleum fractions. The research utilizes the Euler–Lagrange framework with a point-particle approach to model these flows. For dense flow conditions, the gas phase formulation is modified to account for volume fraction. Additionally, a stochastic particle–particle collision model, which is computationally less intensive than deterministic approaches and previously untested for dense flows, is employed. Key findings indicate that the dilute flow formulation remains valid up to a solid mass loading 8 in well-distributed vertical flows. However, in CFB risers, due to the agglomeration of solids into clusters, the dense formulation becomes necessary at lower mass loadings of 4. Comparisons with experiments and simulations using deterministic models demonstrate that the proposed stochastic model accurately predicts dense gas–solid flows in CFB risers up to 22. Finally, the implications of this study are significant for industrial applications, providing a computationally efficient method to accurately model dense gas–solid flows, which is essential for optimizing processes in the petroleum industry.