Mesoscopic Cluster Lifetime Informs the Transition Timescale in Clogging Probability Models

This study investigates the rheological behavior and the dynamic evolution of particle clusters in non-Brownian suspensions under linear shear flow using high-fidelity fully resolved LBM-IBM-DEM simulations. The research aims to provide a direct physical basis for the key fitting parameter in probability-based clogging prediction models. We first validated the accuracy of our simulations at both the macroscopic (apparent viscosity) and microscopic (radial distribution function) scales, and analyzed the effects of shear rate and particle volume fraction on rheological properties. The results indicate that the apparent viscosity increases significantly with the particle Reynolds number and volume fraction. The radial distribution function reveals pronounced spatial correlations of particles along the compressional axis, consistent with the orientation of contact force chains. More importantly, using a self-developed cluster tracking algorithm, we discovered that cluster lifetimes follow an exponential distribution, and their normalized form is independent of cluster size—demonstrating that their evolution is governed by a universal stochastic process. This mesoscopic-scale finding indicates that the state transition rates in probability models can be scaled by a simple characteristic time, enhancing the model's physical interpretability and providing a new theoretical basis for accurately predicting the flow stability and clogging risk of suspensions.