Physics-based fluid simulation in computer graphics: Survey, research trends, and challenges

Publication date

2024

Authors

Wang, Xiaokun
Xu, Yanrui
Liu, Sinuo
Ren, Bo
Kosinka, Jiří
Telea, A.ORCID 0000-0003-0750-0502ISNI 0000000041071164
Wang, Jiamin
Song, Chongming
Chang, Jian
Li, Chenfeng

Editors

Advisors

Supervisors

Document Type

Article
Open Access logo

License

cc_by

Abstract

Physics-based fluid simulation has played an increasingly important role in the computer graphics community. Recent methods in this area have greatly improved the generation of complex visual effects and its computational efficiency. Novel techniques have emerged to deal with complex boundaries, multiphase fluids, gas–liquid interfaces, and fine details. The parallel use of machine learning, image processing, and fluid control technologies has brought many interesting and novel research perspectives. In this survey, we provide an introduction to theoretical concepts underpinning physics-based fluid simulation and their practical implementation, with the aim for it to serve as a guide for both newcomers and seasoned researchers to explore the field of physics-based fluid simulation, with a focus on developments in the last decade. Driven by the distribution of recent publications in the field, we structure our survey to cover physical background; discretization approaches; computational methods that address scalability; fluid interactions with other materials and interfaces; and methods for expressive aspects of surface detail and control. From a practical perspective, we give an overview of existing implementations available for the above methods.

Keywords

computer graphics, fluid coupling, fluid simulation, physical simulation, Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design, Artificial Intelligence

Citation

Wang, X, Xu, Y, Liu, S, Ren, B, Kosinka, J, Telea, A C, Wang, J, Song, C, Chang, J, Li, C, Zhang, J J & Ban, X 2024, 'Physics-based fluid simulation in computer graphics : Survey, research trends, and challenges', Computational Visual Media, vol. 10, no. 5, pp. 803–858. https://doi.org/10.1007/s41095-023-0368-y