Department of Physics, Hangzhou Dianzi University, Hangzhou 310018, China.
School of Mathematics and Statistics, Huazhong University of Science and Technology, Wuhan 430074, China.
Phys Rev E. 2018 Mar;97(3-1):033309. doi: 10.1103/PhysRevE.97.033309.
In this paper, we present a simple and accurate lattice Boltzmann (LB) model for immiscible two-phase flows, which is able to deal with large density contrasts. This model utilizes two LB equations, one of which is used to solve the conservative Allen-Cahn equation, and the other is adopted to solve the incompressible Navier-Stokes equations. A forcing distribution function is elaborately designed in the LB equation for the Navier-Stokes equations, which make it much simpler than the existing LB models. In addition, the proposed model can achieve superior numerical accuracy compared with previous Allen-Cahn type of LB models. Several benchmark two-phase problems, including static droplet, layered Poiseuille flow, and spinodal decomposition are simulated to validate the present LB model. It is found that the present model can achieve relatively small spurious velocity in the LB community, and the obtained numerical results also show good agreement with the analytical solutions or some available results. Lastly, we use the present model to investigate the droplet impact on a thin liquid film with a large density ratio of 1000 and the Reynolds number ranging from 20 to 500. The fascinating phenomena of droplet splashing is successfully reproduced by the present model and the numerically predicted spreading radius exhibits to obey the power law reported in the literature.
本文提出了一种简单而精确的格子玻尔兹曼(LB)模型,用于处理不混溶的两相流动,能够处理大密度对比。该模型利用两个 LB 方程,其中一个用于求解守恒的 Allen-Cahn 方程,另一个用于求解不可压缩的纳维-斯托克斯方程。在用于纳维-斯托克斯方程的 LB 方程中精心设计了一个强制分布函数,使其比现有 LB 模型简单得多。此外,与以前的 Allen-Cahn 型 LB 模型相比,所提出的模型可以实现更高的数值精度。模拟了几个基准两相问题,包括静态液滴、分层泊肃叶流和旋节分解,以验证本 LB 模型。结果发现,与现有模型相比,本模型可以在 LB 界实现相对较小的伪速度,并且得到的数值结果也与解析解或一些现有结果很好地吻合。最后,我们使用本模型研究了具有 1000 大密度比和雷诺数范围为 20 到 500 的液滴对薄液膜的冲击。成功地再现了液滴飞溅的迷人现象,并且数值预测的扩展半径呈现出符合文献中报道的幂律关系。