Exploring the ‘fast is slow’ effect in particle suspension clogging: Liquid driving and random walk models

Abstract

This study investigates the impact of driving mode on the clogging behavior of fluid-driven particles using the LB-IB-DEM method. By simulating the clogging process, we employ a power-law distribution to characterize the blockage and unblocking probabilities of particle flow. Our findings reveal that within a Reynolds number range of 5–150, the probability of particle flow blockage increases with driving force, demonstrating a “fast is slow” effect. This phenomenon is explained through a modified random walk model, highlighting the roles of geometry, chain formation probability, and chain structure evolution probability. Notably, the probability of chain structure generation rises with driving force, underpinning the “fast is slow” effect. Additionally, under flow rate control, the unblocking probability shows weak correlation with driving force, whereas under pressure control, the unblocking probability is negatively correlated with driving force. The ratio of import and export flow changes indicates that accumulation speed is crucial in determining the relationship between dredging probability and driving force, with faster accumulation reducing the likelihood of particle arch breakage.