摘要
The Z–S–C multiphase lattice Boltzmann model [Zheng, Shu, and Chew(ZSC), J. Comput. Phys. 218, 353(2006)]is favored due to its good stability, high efficiency, and large density ratio. However, in terms of mass conservation, this model is not satisfactory during the simulation computations. In this paper, a mass correction is introduced into the ZSC model to make up the mass leakage, while a high-order difference is used to calculate the gradient of the order parameter to improve the accuracy. To verify the improved model, several three-dimensional multiphase flow simulations are carried out,including a bubble in a stationary flow, the merging of two bubbles, and the bubble rising under buoyancy. The numerical simulations show that the results from the present model are in good agreement with those from previous experiments and simulations. The present model not only retains the good properties of the original ZSC model, but also achieves the mass conservation and higher accuracy.
The Z–S–C multiphase lattice Boltzmann model [Zheng, Shu, and Chew(ZSC), J. Comput. Phys. 218, 353(2006)]is favored due to its good stability, high efficiency, and large density ratio. However, in terms of mass conservation, this model is not satisfactory during the simulation computations. In this paper, a mass correction is introduced into the ZSC model to make up the mass leakage, while a high-order difference is used to calculate the gradient of the order parameter to improve the accuracy. To verify the improved model, several three-dimensional multiphase flow simulations are carried out,including a bubble in a stationary flow, the merging of two bubbles, and the bubble rising under buoyancy. The numerical simulations show that the results from the present model are in good agreement with those from previous experiments and simulations. The present model not only retains the good properties of the original ZSC model, but also achieves the mass conservation and higher accuracy.
作者
覃章荣
陈燕雁
凌风如
孟令娟
张超英
Zhang-Rong Qin;Yan-Yan Chen;Feng-Ru Ling;Ling-Juan Meng;Chao-Ying Zhang(Guangxi Collaborative Innovation Center of Multi-source Information Integration and Intelligent Processing,Guangxi Normal University,Guilin 541004,China)
基金
Project supported by the National Natural Science Foundation of China(Grant Nos.11862003 and 81860635)
the Key Project of the Natural Science Foundation of Guangxi Zhuang Autonomous Region,China(Grant No.2017GXNSFDA198038)
the Project of Natural Science Foundation of Guangxi Zhuang Autonomous Region,China(Grant No.2018GXNSFAA281302)
the Project for Promotion of Young and Middle-aged Teachers’Basic Scientific Research Ability in Guangxi Universities,China(Grant No.2019KY0084)
the“Bagui Scholar”Teams for Innovation and Research Project of Guangxi Zhuang Autonomous Region,China
the Graduate Innovation Program of Guangxi Normal University,China(Grant No.JXYJSKT-2019-007)。
