A comparative study of interface-conforming ALE-FE scheme and diffuse interface AMR-LB scheme for interfacial dynamics

JOURNAL OF COMPUTATIONAL PHYSICS

卷:395

Article

Zhang, Changjuan^1,2  Fakharic, Abbas³  Li, Jie^4,5  Luo, Li-Shi^1,6  Qian, Tiezheng² 

[1] Beijing Computat Sci Res Ctr, Beijing 100193, Peoples R China

[2] Hong Kong Univ Sci & Technol, Dept Math, Kowloon, Clear Water Bay, Hong Kong, Peoples R China

[3] Univ Notre Dame, Dept Civil & Environm Engn & Earth Sci, South Bend, IN 46556 USA

[4] Univ Cambridge, BP Inst, Cambridge CB3 0EZ, England

[5] Univ Cambridge, Dept Engn, Cambridge CB3 0EZ, England

[6] Old Dominion Univ, Dept Math & Stat, Norfolk, VA 23529 USA

关键词: Adaptive mesh refinement;    Lattice Boltzmann method;    Arbitrary Lagrangian Eulerian method;    Finite element method;    Bubble dynamics;    Ohnesorge number;   

DOI  :  10.1016/j.jcp.2019.06.048

来源: Elsevier

【 摘 要 】

In this work, a comparative study for two simulation methods is conducted for interfacial flows in two dimensions: an arbitrary Lagrangian Eulerian (ALE) finite element method (FEM) on interface-conforming meshes and a phase field lattice Boltzmann method (LBM) on Cartesian meshes with quadtree adaptive mesh refinement (AMR). The methods are validated by simulations of a bubble without and with buoyancy force. In particular, a suspended bubble with initial nonequilibrium shape and a rising bubble driven by buoyancy force are simulated to validate the methods. Additional simulations of the breakup of a rising bubble and the bubble interaction with a horizontal wall are used to quantify the efficacy and efficiency of the two methods. It is observed that the phase field LBM is more dissipative due to the nature of the diffuse interface method used to capture the interfaces. Overall, the results obtained from both methods agree well with each other when the effects due to the numerical artifacts intrinsic to the diffuse interface method can be neglected. Also, the LBM is in general more efficient and easier to be parallelized. (C) 2019 Elsevier Inc. All rights reserved.

【 授权许可】

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