A stable SPH model with large CFL numbers for multi-phase flows with large density ratios

被引:70
作者
He, Fang [1 ]
Zhang, Huashan [1 ,3 ]
Huang, Can [2 ,3 ]
Liu, Moubin [3 ]
机构
[1] Zhejiang Univ, Ocean Coll, Zhoushan 316021, Zhejiang, Peoples R China
[2] North China Univ Technol, Sch Mech & Mat Engn, Beijing 100144, Peoples R China
[3] Peking Univ, Coll Engn, Beijing 100871, Peoples R China
基金
中国国家自然科学基金;
关键词
Multi-phase flows; Multi-phase interface; Smoothed particle hydrodynamics (SPH); Shepard kernel; Large CFL numbers; NUMERICAL-SIMULATION; COMPLEX INTERFACES; PARTICLE METHODS; COMPUTATIONS;
D O I
10.1016/j.jcp.2022.110944
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
The discontinuity across interface of multi-phase flows with large density ratios usually poses great challenges for numerical simulations. The smoothed particle hydrodynamics (SPH) is a meshless method with inherent advantages in dealing with multi-phase flows without the necessity of tracking the moving interfaces. In this paper, we develop a new weakly-compressible SPH model for multi-phase flows with large density ratios while allowing large CFL numbers. In the present SPH model, the continuity equation is first modified by eliminating the influence from particles of different phases based on the simple fact that different phases will not contribute when calculating the density for immiscible multi-phase flows; thus, the modified continuity equation will only consider the influence from neighboring particles of the same phase. The pressure and density of the particles of other phases are then re-initialized by using the Shepard interpolation function. The present multi-phase SPH model has been tested by four numerical examples, including the two-phase hydrostatic water, standing waves, liquid sloshing, and dam breaking. It has been demonstrated that the present multi-phase SPH model can obtain satisfactory results stably, even at large CFL numbers, and this means that large time steps can be employed. Therefore, the present multi-phase SPH model can significantly save computational cost through using large time steps, especially for large-scale problems with a large number of particles. (C) 2022 Elsevier Inc. All rights reserved.
引用
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页数:29
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