Abstract
Gas–solid fluidized beds play a vital role in energy production, chemical processing, and thermal management due to their excellent mixing and transport properties. Despite their importance, predicting fluidized bed hydrodynamics remains a major challenge because of the highly coupled and nonlinear interactions between gas and particle phases. Computational fluid dynamics (CFD) has become an indispensable tool for analyzing such systems, but the reliability of predictions depends strongly on solver formulation, closure models, and postprocessing strategies. This study revisits the benchmark experiment of Taghipour et al. [1], which provides high-quality measurements of pressure drop and bed expansion BER, and applies it to the most recent release of OpenFOAM (v12). An Euler–Euler two-fluid approach is employed, incorporating kinetic theory of granular flow for solid-phase stresses and the Gidaspow drag correlation for interphase momentum exchange. Simulations are performed on a two-dimensional rectangular bed fluidized with air and Geldart B particles. Pressure drop and bed expansion ratio (BER) are selected as the main indicators for validation. Beyond conventional postprocessing methods, a new mass-conservation based approach for estimating BER is introduced, which takes into account data from the entire computational domain. The work aims to evaluate the predictive capacity of OpenFOAM v12 in reproducing well-established benchmarks and to advance postprocessing techniques for more reliable characterization of fluidized bed hydrodynamics.