A Monte Carlo Method for Fluid Simulation
*Joint first authors
In ACM SIGGRAPH Asia, 2022
Abstract
We present a novel Monte Carlo-based fluid simulation approach capable of pointwise and stochastic estimation of fluid motion. Drawing on the Feynman-Kac representation of the vorticity transport equation, we propose a recursive Monte Carlo estimator of the Biot-Savart law and extend it with a stream function formulation that allows us to treat free-slip boundary conditions using a Walk-on-Spheres algorithm. Inspired by the Monte Carlo literature in rendering, we design and compare variance reduction schemes suited to a fluid simulation context for the first time, show its applicability to complex boundary settings, and detail a simple and practical implementation with temporal grid caching. We validate the correctness of our approach via quantitative and qualitative evaluations – across a range of settings and domain geometries – and thoroughly explore its parameters’ design space. Finally, we provide an in-depth discussion of several axes of future work building on this new numerical simulation modality.
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@article{Rioux-Lavoie:2022:MCFluid, author = {Rioux-Lavoie, Damien and Sugimoto, Ryusuke and Özdemir, Tümay and Shimada, Naoharu H. and Batty, Christopher and Nowrouzezahrai, Derek and Hachisuka, Toshiya }, title = {A Monte Carlo Method for Fluid Simulation}, journal = {ACM Transactions on Graphics}, volume = {41}, number = {6}, year = {2022}, month = dec, doi = {10.1145/3550454.3555450}, }
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