Enhancing efficiency in particle aggregation simulations: Coarse-grained particle modeling in the DEM-PBM coupled framework

被引:8
|
作者
De, Tarun [1 ]
Das, Ashok [2 ,3 ]
Singh, Mehakpreet [4 ]
Kumar, Jitendra [5 ]
机构
[1] Indian Inst Technol Kharagpur, Dept Math, Kharagpur 721302, West Bengal, India
[2] Univ Lorraine, Inst Jean Lamour, F-54000 Nancy, France
[3] Univ Limerick, Bernal Inst, Limerick V94T9PX, Ireland
[4] Univ Limerick, Dept Math & Stat, Limerick V94T9PX, Ireland
[5] Indian Inst Technol Ropar, Dept Math, Rupnagar 140001, Punjab, India
关键词
Aggregation; Population balance; Discrete element method; Collision frequency; Coarse graining; Computational efficiency; DISCRETE; GRANULATION; MULTISCALE; FLOW; MOMENTS; SCHEME;
D O I
10.1016/j.cma.2023.116436
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The computational cost of the discrete element method (DEM)-population balance model (PBM) coupled framework is predominantly attributed to DEM simulations. To overcome this challenge, coarse-grained (CG) particles have been introduced in the DEM-PBM coupled framework. In this study, we proposed a new CG-enabled DEM-PBM coupled framework that builds upon the previous work of Das et al. (Proc. R. Soc. Lond. Ser. A Math. Phys. Eng. Sci. 478 (2261) (2022) 20220076). By incorporating the CG technique, the particle number density is reduced, resulting in fewer collisions compared to the resolved system. To address this issue, a scaling law has been developed to derive the collision frequency of the resolved system from the CG system. The verification of the new scaling law has been demonstrated through various simulation studies. Furthermore, the entire DEM-PBM coupled framework has been modified using the proposed methodology. The efficiency of the CG-DEM-PBM coupled simulation method has been successfully demonstrated through simulations of rotating drum and continuous mixing technology (CMT). Compared to the resolved simulation approach, the newly proposed CG-enabled DEM-PBM coupled framework maintains accuracy in terms of particle size distribution and other essential findings while significantly reducing simulation time.
引用
收藏
页数:21
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