Liquid Splash Modeling with Neural Networks [article]

Kiwon Um, Xiangyu Hu, Nils Thuerey
2018 arXiv   pre-print
This paper proposes a new data-driven approach to model detailed splashes for liquid simulations with neural networks. Our model learns to generate small-scale splash detail for the fluid-implicit-particle method using training data acquired from physically parametrized, high resolution simulations. We use neural networks to model the regression of splash formation using a classifier together with a velocity modifier. For the velocity modification, we employ a heteroscedastic model. We evaluate
more » ... our method for different spatial scales, simulation setups, and solvers. Our simulation results demonstrate that our model significantly improves visual fidelity with a large amount of realistic droplet formation and yields splash detail much more efficiently than finer discretizations.
arXiv:1704.04456v2 fatcat:qzsah4z57jadvavhwsz62bn5mq