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Fluid Rendering

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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

As shown in the previous chapters, fluid simulation deals with complex models and algorithms to approximate the myriad of behaviors fluids may have. Those simulations produce large amounts of data. An essential step in analyzing these data is its visualization. As 3D data, rendering techniques are crucial in the visualization step. Render deals with transforming the simulation data into an image. It is a challenging task per se and is even more complicated when the subject, in this case, the fluid, has a non-rigid form that can evolve in 3D space and interact with light in complex ways. We will present in this chapter the traditional techniques used to render fluids and the new perspectives that Machine Learning can provide to improve this process.

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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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Antonio Giraldi, G., Almeida, L.R.d., Lopes Apolinário Jr., A., Silva, L.T.d. (2023). Fluid Rendering. In: Deep Learning for Fluid Simulation and Animation. SpringerBriefs in Mathematics. Springer, Cham. https://doi.org/10.1007/978-3-031-42333-8_7

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