聚结(物理)
碰撞
物理
机械
光滑粒子流体力学
冲击参数
悬挂(拓扑)
质量守恒
粒子(生态学)
经典力学
航程(航空)
韦伯数
碰撞频率
计算机模拟
动量(技术分析)
粒子数
粒径
万有引力
恢复系数
表面张力
能量-动量关系
相变
两相流
计算流体力学
相对速度
喷雾干燥
重力
作者
Xiaolong Zhu,Ma Wen,Jinyi Zhang,Chuanyu Pan,Fangwei Han,Chaohang Xu,Jiyun Wang,Guochun Li,Q Zhang,Shuai Kong
摘要
Collisions between droplets and solid particles may result in rebounding, coalescence, or droplet rupture. In spray-based dust suppression, coalescence is the most desirable outcome because it promotes particle mass increase and gravitational settling. Therefore, identifying the governing factors and critical conditions for coalescence is essential for improving spray dust mitigation efficiency. Although previous studies have made significant progress in establishing transition criteria between rebounding and coalescence, quantitative predictive models distinguishing coalescence from rupture remain limited, particularly for suspended particle–droplet interactions at the micro-scale. In this study, a computational fluid dynamics (CFD) model employing a dynamic mesh technique and the coupled level-set/volume of fluid (VOF) method is used to investigate the collision dynamics between suspended particles and droplets. The results demonstrate that the collision outcome is jointly governed by the solid–liquid density ratio, contact angle, relative impact velocity, particle-to-droplet size ratio, droplet viscosity, and surface tension. Based on momentum and energy conservation principles, a predictive criterion model for the transition between coalescence and rupture is proposed, revealing the underlying dynamic mechanisms controlling collision behavior. Based on the proposed model, the influence of key parameters on the coalescence regime is quantified, providing guidance for optimizing spray operating parameters and additive formulations. The present findings not only promote the development of spray dust suppression technology but also provide theoretical support for related fields, including particle surface modification, fire smoke scrubbing, and pharmaceutical engineering.
科研通智能强力驱动
Strongly Powered by AbleSci AI