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Published July 1, 2021 | public
Journal Article

Kinetic-Based Multiphase Flow Simulation

Abstract

Multiphase flows exhibit a large realm of complex behaviors such as bubbling, glugging, wetting, and splashing which emerge from air-water and water-solid interactions. Current fluid solvers in graphics have demonstrated remarkable success in reproducing each of these visual effects, but none have offered a model general enough to capture all of them concurrently. In contrast, computational fluid dynamics have developed very general approaches to multiphase flows, typically based on kinetic models. Yet, in both communities, there is dearth of methods that can simulate density ratios and Reynolds numbers required for the type of challenging real-life simulations that movie productions strive to digitally create, such as air-water flows. In this article, we propose a kinetic model of the coupling of the Navier-Stokes equations with a conservative phase-field equation, and provide a series of numerical improvements over existing kinetic-based approaches to offer a general multiphase flow solver. The resulting algorithm is embarrassingly parallel, conservative, far more stable than current solvers even for real-life conditions, and general enough to capture the typical multiphase flow behaviors. Various simulation results are presented, including comparisons to both previous work and real footage, to highlight the advantages of our new method.

Additional Information

© 2020 IEEE. Manuscript received 18 Apr. 2019; revised 29 Nov. 2019; accepted 31 Jan. 2020. Date of publication 7 Feb. 2020; date of current version 26 May 2021. The authors would like to thank Dr. Ryoichi Ando from National Institute of Informatics, Tokyo, Japan, for sharing his fluid simulation codes for comparison, Jinglei Yang from the University of California, Santa Barbara, for her early help on rendering, as well as Yiran Sun and Chaoyang Lyu from ShanghaiTech University for rendering and figures. This work was supported by the Young Scientists Fund of the National Natural Science Foundation of China (Grant No. 61502305), as well as startup funds from ShanghaiTech University. They also thank the reviewers for their comments.

Additional details

Created:
August 20, 2023
Modified:
October 19, 2023