A fast adhesive discrete element method for random packings of fine particles

被引:71
作者
Chen, Sheng [1 ]
Liu, Wenwei [1 ]
Li, Shuiqing [1 ]
机构
[1] Tsinghua Univ, Key Lab Thermal Sci & Power Engn, Dept Energy & Power Engn, Minist Educ, Beijing 100084, Peoples R China
关键词
Discrete element method; Reduced stiffness; Microspheres; Cohesive particles; Rolling resistance; Packing structure; COMPUTER-SIMULATION; FLUIDIZATION BEHAVIOR; DUST COAGULATION; DEM SIMULATIONS; LOOSE PACKINGS; CONTACT; STIFFNESS; IMPACT; MODEL; DEPOSITION;
D O I
10.1016/j.ces.2018.09.026
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
Introducing a reduced particle stiffness in discrete element method (DEM) allows for bigger time steps and therefore fewer total iterations in a simulation. Although this approach works well for dry nonadhesive particles, it has been shown that for fine particles with adhesion, system behaviors are drastically sensitive to the particle stiffness. Besides, a simple and applicable principle to set the parameters in adhesive DEM is also lacking. To solve these two problems, we first propose a fast DEM based on scaling laws to reduce particle Young's modulus, surface energy and to modify rolling and sliding resistances simultaneously in the framework of Johnson-Kendall-Roberts (JKR)-based contact theory. A novel inversion method is then presented to help users to quickly determine the damping coefficient, particle stiffness and surface energy to reproduce a prescribed experimental result. After validating this inversion method, we apply the fast adhesive DEM to packing problems of microparticles. Measures of packing fraction, averaged coordination number and distributions of local packing fraction and contact number of each particle are in good agreement with results simulated using original value of particle properties. The new method should be helpful to accelerate DEM simulations for systems associated with aggregates or agglomerates. (C) 2018 Elsevier Ltd. All rights reserved.
引用
收藏
页码:336 / 345
页数:10
相关论文
共 54 条
[1]   THERMAL OR ELECTRICAL-CONDUCTION THROUGH A GRANULAR MATERIAL [J].
BATCHELOR, GK ;
OBRIEN, RW .
PROCEEDINGS OF THE ROYAL SOCIETY OF LONDON SERIES A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES, 1977, 355 (1682) :313-333
[2]   Edwards statistical mechanics for jammed granular matter [J].
Baule, Adrian ;
Morone, Flaviano ;
Herrmann, Hans J. ;
Makse, Hernan A. .
REVIEWS OF MODERN PHYSICS, 2018, 90 (01)
[3]   Structure and mechanical properties of high-porosity macroscopic agglomerates formed by random ballistic deposition -: art. no. 115503 [J].
Blum, J ;
Schräpler, R .
PHYSICAL REVIEW LETTERS, 2004, 93 (11) :115503-1
[4]   Scaling laws for migrating cloud of low-Reynolds-number particles with Coulomb repulsion [J].
Chen, Sheng ;
Liu, Wenwei ;
Li, Shuiqing .
JOURNAL OF FLUID MECHANICS, 2018, 835 :880-897
[5]   Effect of long-range electrostatic repulsion on pore clogging during microfiltration [J].
Chen, Sheng ;
Liu, Wenwei ;
Li, Shuiqing .
PHYSICAL REVIEW E, 2016, 94 (06)
[6]   Effect of long-range repulsive Coulomb interactions on packing structure of adhesive particles [J].
Chen, Sheng ;
Li, Shuiqing ;
Liu, Wenwei ;
Makse, Hernan A. .
SOFT MATTER, 2016, 12 (06) :1836-1846
[7]   Sticking/rebound criterion for collisions of small adhesive particles: Effects of impact parameter and particle size [J].
Chen, Sheng ;
Li, Shuiqing ;
Yang, Mengmeng .
POWDER TECHNOLOGY, 2015, 274 :431-440
[8]   DUST COAGULATION [J].
CHOKSHI, A ;
TIELENS, AGGM ;
HOLLENBACH, D .
ASTROPHYSICAL JOURNAL, 1993, 407 (02) :806-819
[9]   Calibration of the discrete element method [J].
Coetzee, C. J. .
POWDER TECHNOLOGY, 2017, 310 :104-142
[10]   DISCRETE NUMERICAL-MODEL FOR GRANULAR ASSEMBLIES [J].
CUNDALL, PA ;
STRACK, ODL .
GEOTECHNIQUE, 1979, 29 (01) :47-65