An Enhanced Numerical Simulation of Porous Particle Movements by Coupling Porous Drag Correlation Considering the Permeability

Abstract

Porous particles are widely encountered in industrial processes. However, predictions of their motion still largely rely on drag correlations originally developed for solid particles, which may lead to significant deviations. Using symbolic regression, this study proposed a new drag correlation for porous particles, which considers porosity and permeability. The correlation ensures both physical meaning and high prediction accuracy over a wide range of Reynolds numbers. Then, the correlation was embedded into numerical simulation frameworks, and a systematic simulation on the settling behaviors of single solid and porous particles was conducted. Compared with five classical drag correlations for solid spheres, simulations based on the new drag correlation agreed better with both porous particle and solid particle settling processes observed in particle tracking velocimetry settling experiments. It was found that terminal settling velocities of porous particles were often overestimated by 15%–30% when using traditional solid drag correlations. However, after applying the proposed drag correlation for porous particles, the average deviation of terminal settling velocity was reduced to 5%. This correlation provided a reliable basis for drag closure in multiphase-flow numerical simulations of complex systems that contain porous particles (e.g., porous adsorbents, catalysts, and agglomerated particles) and offered a new method to enhance the predictive accuracy of porous-particle simulations in multiphase flows.