Agglomeration of wet particles upon collision: Criterion establishment and regulatory mechanism

Wet particle collision and coalescence are pivotal to various industrial processes, yet existing predictive methods rely on oversimplified liquid bridge dynamics with limited accuracy. This study proposes a novel efficient modeling framework based on critical coalescence velocity (CCV) for rapid and accurate prediction of wet particle coalescence behavior. A CCV-driven predictive model, integrating liquid bridge characteristics and particle intrinsic properties, was innovatively incorporated as a coalescence criterion into discrete element method (DEM) simulations. The framework was further extended to particle-wall collision scenarios, with a tailored CCV model formulated to predict particle deposition and rebound. Meanwhile, we investigated the agglomeration behavior between particle - particle and particle - wall using a cross - symmetrical reactor as the platform. Systematic studies revealed two key novel findings: the particle - wall coalescence efficiency peaks when the initial velocity is 6–7 times the CCV, and the axial velocity component dominates coalescence for incident angles of 30°–60°, with kinetic energy retention positively correlated with incident angles below 60°. This framework fills the gap in efficient and accurate prediction of wet particle-particle and particle-wall coalescence, providing a reliable theoretical basis for related industrial process optimization.