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Fluids and Deep Learning: A Brief Review

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Deep Learning for Fluid Simulation and Animation

Part of the book series: SpringerBriefs in Mathematics ((BRIEFSMATH))

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Abstract

This chapter surveys deep learning models for fluid simulation and rendering. Regarding the former, we can group the works into small and large-scale fluid simulation, the interaction of the flow with other objects, and fluid control. Steered by this fact, we review works in turbulence, fluid solvers improvement, super-resolution, and generation of small-scale details for visual effects and video game applications. Also, applications of physics-based deep learning to produce fluid simulations with desirable behaviors for movies and the game industry are considered. Concerning rendering, we will highlight the most recent works applying machine learning techniques to generate photorealistic images.

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Authors and Affiliations

  1. National Laboratory for Scientific Computing, Petrópolis, Rio de Janeiro, Brazil

    Gilson Antonio Giraldi & Liliane Rodrigues de Almeida

  2. Institute of Computing, Federal University of Bahia, Salvador, Bahia, Brazil

    Antonio Lopes Apolinário Jr.

  3. Campus Petrópolis, Federal Center for Technological Education Celso Suckow da Fonseca – RJ, Petrópolis, Rio de Janeiro, Brazil

    Leandro Tavares da Silva

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  1. Gilson Antonio Giraldi
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  2. Liliane Rodrigues de Almeida
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  3. Antonio Lopes Apolinário Jr.
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  4. Leandro Tavares da Silva
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Antonio Giraldi, G., Almeida, L.R.d., Lopes Apolinário Jr., A., Silva, L.T.d. (2023). Fluids and Deep Learning: A Brief Review. In: Deep Learning for Fluid Simulation and Animation. SpringerBriefs in Mathematics. Springer, Cham. https://doi.org/10.1007/978-3-031-42333-8_2

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