Computational fluid dynamic-discrete element method coupling analysis of particle transport in branched networks

作     者：Xiaoyu Wang Jun Yao Liang Gong Yang Li Yongfei Yang Hongliang Zhao Xiaoyu Wang;Jun Yao;Liang Gong;Yang Li;Yongfei Yang;Hongliang Zhao

作者机构：Research Center of Multiphase Flow in Porous MediaChina University of Petroleum(East China)Qingdao 266580China College of New EnergyChina University of Petroleum(East China)Qingdao 266580China Department of Oilfield Exploration&DevelopmentSinopecBeijing 100029China School of Metallurgical and Ecological EngineeringUniversity of Science and Technology BeijingBeijing 100083China 

出 版 物：《Particuology》 (颗粒学报（英文版）)

年 卷 期：2021年第19卷第2期

页      面：140-150页

核心收录：

学科分类：080704[工学-流体机械及工程] 0817[工学-化学工程与技术] 080103[工学-流体力学] 08[工学] 0807[工学-动力工程及工程热物理] 0805[工学-材料科学与工程（可授工学、理学学位）] 0703[理学-化学] 0702[理学-物理学] 0801[工学-力学（可授工学、理学学位）] 

基　　金：Thig work was supportcd by the National Scicnce and Tech nology Major Project of the Ministry of Science and Technology of China(20172X05009-001) the National Natural Science Foun dation of China(No.J1930001,Nu.J1074208,Nu.J1304270,No.51504277.No.51774308 and No.51904321) the Shan dong Provincial Natural Science Foundation(ZR2019JQ21) the ulnllleltdl Resedltl Fulids fU1 the Celldl Uliveisities(Nu.17CX02008A,No.17CX05003,No.18CX02031A,No.18CX07012A and No.19CX05002A) Key Research and Development Plan of Shandong PToVince(2018GSF116009) 

主　　题：Particle-fluid flow CFD-DEM coupling Branched network 

摘      要：An understanding of the particle transport characteristics in a branched network helps to predict the particle distribution and prevent undesired plugging in various engineering *** analysis of particle flow characteristics is challenging in that experiments are expensive and particle flow is difficult to detect without disturbing the *** overcome this difficulty,man-made fractal tree-like branched networks were built,and a coupled computational fluid dynamic and discrete element method model was applied.A series of numerical simulations was carried out to analyze the influence of fractal structure parameters of networks on the particle flow *** joint influence of inertial,shunt capacity and superposition from upstream branches on particle flow was *** injection position at the inlet determined the particle velocity and its future flow *** particle density ratio,particle size and bifurcation angle had a greater influence on the shunting of K2 branches than that in the K1 level and N_(k22)/N_(k21) reached a maximum at 60°.Compared with a network with an even number of branches,there was a preferential branch when the branch number was *** preferential branch effect or asymmetry degree of the level(K2)branches had a more significant impact on particle shunting than that from the upstream branches(K1).