Coupling Conduction, Convection and Radiative Transfer in a Single Path-Space: Application to Infrared Rendering
Mégane Bati, Stéphane Blanco, Christophe Coustet, Vincent Eymet, Vincent Forest, Richard Fournier, Jacques Gautrais, Nicolas Mellado, Mathias Paulin, Benjamin Piaud
Abstract
In the past decades, Monte Carlo methods have shown their ability to solve PDEs, independently of the dimensionality of the integration domain and for different use-cases (e.g. light transport, geometry processing, physics simulation). Specifically, the path-space formulation of transport equations is a key ingredient to define tractable and scalable solvers, and we observe nowadays a strong interest in the definition of simulation systems based on Monte Carlo algorithms. We also observe that, when simulating combined physics (e.g. thermal rendering from a heat transfer simulation), there is a lack of coupled Monte Carlo algorithms allowing to solve all the physics at once, in the same path space, rather than combining several independent MC estimators, a combination that would make the global solver critically sensitive to the complexity of each simulation space. This brings to our proposal: a coupled, single path-space, Monte Carlo algorithm for efficient multi-physics problems solving. In this work, we combine our understanding and knowledge of Physics and Computer Graphics to demonstrate how to formulate and arrange different simulation spaces into a single path space. We define a tractable formalism for coupled heat transfer simulation using Monte Carlo, and we leverage the path-space construction to interactively compute multiple simulations with different conditions in the same scene, in terms of boundary conditions and observation time. We validate our proposal in the context of infrared rendering with different thermal simulation scenarios: e.g., room temperature simulation, visualization of heat paths within materials (detection of thermal bridges), heat diffusion capacity of thermal exchanger. We expect that our theoretical framework will foster collaboration and multidisciplinary studies. The perspectives this framework opens are detailed and we suggest a research agenda towards the resolution of coupled PDEs at the interface of Physics and Computer Graphics.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext 871ca697-1c6e-41d8-ba6c-b65bc52f7479Cited by top-tier papers5
- Walk on Stars: A Grid-Free Monte Carlo Method for PDEs with Neumann Boundary ConditionsRohan Sawhney, Bailey Miller, Ioannis Gkioulekas, Keenan CraneSIGGRAPH 2023 · 48 citations
- Walkin' Robin: Walk on Stars with Robin Boundary ConditionsBailey Miller, Rohan Sawhney, Keenan Crane, Ioannis GkioulekasSIGGRAPH 2024 · 30 citations
- Guiding-Based Importance Sampling for Walk on StarsTianyu Huang, Jingwang Ling, Shuang Zhao, Feng XuSIGGRAPH 2025 · 6 citations
- Solving partial differential equations in participating mediaBailey Miller, Rohan Sawhney, Keenan Crane, Ioannis GkioulekasSIGGRAPH 2025 · 2 citations
- Monte Carlo PDE Solvers for Nonlinear Radiative Boundary ConditionsAnchang Bao, Enya Shen, Jianmin WangSIGGRAPH 2026
Builds on7
- Monte Carlo geometry processing: a grid-free approach to PDE-based methods on volumetric domainsRohan Sawhney, Keenan CraneSIGGRAPH 2020 · 99 citations
- Path replay backpropagation: differentiating light paths using constant memory and linear timeDelio Vicini, Sébastien Speierer, Wenzel JakobSIGGRAPH 2021 · 97 citations
- Walk on Stars: A Grid-Free Monte Carlo Method for PDEs with Neumann Boundary ConditionsRohan Sawhney, Bailey Miller, Ioannis Gkioulekas, Keenan CraneSIGGRAPH 2023 · 48 citations
- Grid-free Monte Carlo for PDEs with spatially varying coefficientsRohan Sawhney, Dario Seyb, Wojciech Jarosz, Keenan CraneSIGGRAPH 2022 · 46 citations
- Towards practical physical-optics renderingShlomi Steinberg, Pradeep Sen, Ling-Qi YanSIGGRAPH 2022 · 14 citations
Related papers
- Path-space differentiable renderingCheng Zhang, Bailey Miller, Kai Yan, Ioannis Gkioulekas et al.SIGGRAPH 2020 · 155 citations
- Monte Carlo estimators for differential light transportTizian Zeltner, Sébastien Speierer, Iliyan Georgiev, Wenzel JakobSIGGRAPH 2021 · 70 citations
- Path-Space Differentiable Rendering of Implicit SurfacesSiwei Zhou, Youngha Chang, Nobuhiko Mukai, Hiroaki Santo et al.SIGGRAPH 2024 · 1 citation
- Path-space differentiable rendering of participating mediaCheng Zhang, Zihan Yu, Shuang ZhaoSIGGRAPH 2021 · 50 citations
- Differentiable Neutron TransportXi Deng, Maosen Tang, Michael Czekanski, David Bindel et al.SIGGRAPH 2026
