Solving 2D damped Kuramoto-Sivashinsky with multiple relaxation time lattice Boltzmann method

被引:0
作者
MohammadiArani, Reza [1 ]
Dehghan, Mehdi [1 ]
Abbaszadeh, Mostafa [1 ]
机构
[1] Amirkabir Univ Technol, Tehran Polytech, Fac Math & Comp Sci, Dept Appl Math, 424 Hafez Ave, Tehran 15914, Iran
关键词
Lattice Boltzmann method; Two-dimensional damped; Kuramoto-Sivashinsky equation; Chapman-Enskog analysis; von Neumann analysis; Numerical simulation; Artificial intelligence (AI) algorithm; NATURAL-CONVECTION; EQUATION; SIMULATION; MODEL; DIFFUSION; SCHEME; STATES;
D O I
10.1016/j.apnum.2023.10.005
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
Lattice Boltzmann method (LBM) is a powerful fluid flow solver. Using this method to solve other PDEs might be a difficult task. The first challenge is to find a suitable local equilibrium distribution function (EDF) capable of recovering the desired PDE. The next difficulty arises from the explicit nature of LBM. The conditional stability of the LBM algorithm affects the numerical solution accuracy. Damped Kuramoto-Sivashinsky (DKS) equation is a fourth-order PDE that recently challenged many numerical methods' abilities. This equation is highly sensitive to a parameter that causes three states of solutions in a small interval of freedom. In this paper, we challenged LBM to solve the two-dimensional DKS equation by finding EDF using the Chapman- Enskog analysis up to the fourth-order. Also, the von Neumann analysis and a simple genetic algorithm are applied to find reliable values for the free parameters. Furthermore, a modification on image-based ghost node method is proposed for implementation of the boundary conditions in the complex geometries.
引用
收藏
页码:83 / 103
页数:21
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