Solving partial differential equations in participating media
Bailey Miller, Rohan Sawhney, Keenan Crane, Ioannis Gkioulekas
摘要
We consider the problem of solving partial differential equations (PDEs) in domains with complex microparticle geometry that is impractical, or intractable, to model explicitly. Drawing inspiration from volume rendering, we propose tackling this problem by treating the domain as a participating medium that models microparticle geometry stochastically , through aggregate statistical properties (e.g., particle density). We first introduce the problem setting of PDE simulation in participating media. We then specialize to exponential media and describe the properties that make them an attractive model of microparticle geometry for PDE simulation problems. We use these properties to develop two new algorithms, volumetric walk on spheres and volumetric walk on stars , that generalize previous Monte Carlo algorithms to enable efficient and discretization-free simulation of linear elliptic PDEs (e.g., Laplace) in participating media. We demonstrate experimentally that our algorithms can solve Laplace boundary value problems with complex microparticle geometry more accurately and more efficiently than previous approaches, such as ensemble averaging and homogenization.
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- Monte Carlo geometry processing: a grid-free approach to PDE-based methods on volumetric domainsRohan Sawhney, Keenan CraneSIGGRAPH 2020 · 被引用 99 次
- Homogenized yarn-level clothGeorg Sperl, Rahul Narain, Chris WojtanSIGGRAPH 2020 · 被引用 72 次
- Walk on Stars: A Grid-Free Monte Carlo Method for PDEs with Neumann Boundary ConditionsRohan Sawhney, Bailey Miller, Ioannis Gkioulekas, Keenan CraneSIGGRAPH 2023 · 被引用 48 次
- Grid-free Monte Carlo for PDEs with spatially varying coefficientsRohan Sawhney, Dario Seyb, Wojciech Jarosz, Keenan CraneSIGGRAPH 2022 · 被引用 46 次
- A Practical Walk-on-Boundary Method for Boundary Value ProblemsRyusuke Sugimoto, Terry Chen, Yiti Jiang, Christopher Batty 等SIGGRAPH 2023 · 被引用 42 次
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