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Adhesive particulate flow: The discrete-element method and its application in energy and environmental engineering

微粒 有限元法 环境科学 能量(信号处理) 机械工程
作者
Shuiqing Li,Jeffrey S. Marshall,Guanqing Liu,Qiang Yao
出处
期刊:Progress in Energy and Combustion Science [Elsevier]
卷期号:37 (6): 633-668 被引量:169
标识
DOI:10.1016/j.pecs.2011.02.001
摘要

Abstract In this paper, recent advances in the discrete-element method (DEM) for describing motion, deposition, agglomeration or aggregation of a large number of adhesive spherical particles immersed in fluid flows, termed as adhesive particulate flow, are reviewed. The constitutive equations together with the length and time scales of DEM are compared with those of other similar Lagrangian particle methods, e.g., molecular dynamics (MD), Brownian dynamics (BD), dissipative particle dynamics (DPD). The adhesive contact force and torque models in the presence of different adhesive effects are examined, including van der Waals force, ligand-receptor binding, liquid bridging force, interface adhesion, and sintering forces, all of which play an important role in DEM formulations for different types of adhesive particulate flow problems of interest in energy, combustion and environmental fluid mechanics problems. A summary of various kinds of particle-field interactions is presented, including fluid forces, electric field forces, acoustic force, and thermophoretic force. The computational method is illustrated by application to a series of examples involving capture of spherical particles by a fiber in a uniform upstream flow, examining the deposition/aggregation patterns of both mono-size and binary-size particles on the cylinder with and without the presence of electric field effects, which may be due either to charging of the cylinder or polarization of the particles. Particle capture problems of this sort are commonly encountered in filtration problems and ash-removal problems experienced in environmental and combustion applications, respectively. The article concludes with a discussion of remaining modeling challenges in development of discrete-element methods for adhesive particulate flow fields.

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