Roles of clusters in the migration of fines through porous media. (16th January 2023)

• Record Type: Journal Article
• Authors: Xie, Zhouzun; Wang, Shuai; Shen, Yansong
• Is Part Of: Chemical engineering science. Volume 265(2023)
• Publication Date: 2023-01-16
• Subjects: Migration of fines -- Flows in porous media -- Clogging mechanism -- Polydisperse solid-liquid system -- CFD-DEM simulation; Chemical engineering -- Periodicals; Génie chimique -- Périodiques; Chemical engineering; Periodicals; Electronic journals; 660
• DOI: 10.1016/j.ces.2022.118217
• Languages: English
• ISSNs: 0009-2509

Abstract

Highlights: The inherent fundamentals and roles of clusters in fines migration are elucidated. Two clogging mechanisms of fines at pore-scale are essentially unveiled. A constant saturation volume fraction of fines in the entrance is confirmed. An exponential correlation is obtained by growth rate of cluster size. A probabilistic model is derived for predicting clogging performance. Abstract: The migration of fines suspended in the liquid through porous media represents a key challenge in many chemical engineering processes, yet the inherent fundamentals and roles of clusters were not well elucidated. In this work, we numerically study the formation, growth, and connection of clusters in a porous medium and unveil the clogging mechanism of fines at pore-scale, i.e., bridging and locking essentially. A saturation volume fraction of fines in the entrance occurs at the critical transition point from depth filtration to caking, where the volume fraction is calculated by the spherical cap method. An inter-particle contact pair method is developed to quantify the cluster size growth. Inherently, an exponential correlation between clogging ability and size ratios is obtained using the cluster information - growth rate of clusters. A probabilistic model of clogging ability and performance is derived and used to verify the exponential formula. This work provides an effective method to quantify clogging ability and could be applied to more complex systems.