You Xie, Erik Franz, MengYu Chu, Nils Thuerey We propose a temporally coherent generative model addressing the super-resolution problem for fluid flows. Our work represents a first approach to synthesize four-dimensional physics fields with neural networks. Based on a conditional generative adversarial network that is designed for the inference of three-dimensional volumetric data, our model […]

Stefan Jeschke, Tomáš Skřivan, Matthias Müller-Fischer, Nuttapong Chentanez, Miles Macklin, Chris Wojtan The current state of the art in real-time two-dimensional water wave simulation requires developers to choose between efficient Fourier-based methods, which lack interactions with moving obstacles, and finite-difference or finite element methods, which handle environmental interactions but are significantly more expensive. This paper […]

François Dagenais, Julián Guzmán, Valentin Vervondel, Alexander Hay, Sébastien Delorme, David Mould, and Eric Paquette We propose an approach for real-time shallow water simulation, building upon the virtual pipes model with multi-layered heightmaps. Our approach introduces the use of extended pipes which resolve flow through fully-flooded passages, which is not possible using current multi-layered techniques. […]

Stefan Band, Christoph Gissler, Markus Ihmsen, Jens Cornelis, Andreas Peer, Matthias Teschner Implicit incompressible SPH (IISPH) solves a pressure Poisson equation (PPE). While the solution of the PPE provides pressure at fluid samples, the embedded boundary handling does not compute pressure at boundary samples. Instead, IISPH uses various approximations to remedy this deficiency. In this […]

Kui Wu, Nghia Truong, Cem Yuksel, Rama Hoetzlein We introduce efficient, large scale fluid simulation on GPU hardware using the fluid-implicit particle (FLIP) method over a sparse hierarchy of grids represented in NVIDIA GVDB Voxels. Our approach handles tens of millions of particles within a virtually unbounded simulation domain. We describe novel techniques for parallel […]