Coupling radiative, conductive and convective heat-transfers in a single Monte Carlo algorithm: A general theoretical framework for linear situations

Jean Marc Tregan, Jean Luc Amestoy, Megane Bati, Jean-Jacques Bezian, Stéphane Blanco, Laurent Brunel, Cyril Caliot, Julien Charon, Jean-Francois Cornet, Christophe Coustet, Louis d’Alençon, Jeremi Dauchet, Sebastien Dutour, Simon Eibner, Mouna El Hafi, Vincent Eymet, Olivier Farges, Vincent Forest, Richard Fournier, Mathieu Galtier, Victor Gattepaille, Jacques Gautrais, Zili He, Frédéric Hourdin, Loris Ibarrart, Jean-Louis Joly, Paule Lapeyre, Pascal Lavieille, Marie-Helene Lecureux, Jacques Lluc, Marc Miscevic, Nada Mourtaday, Yaniss Nyffenegger-Péré, Lionel Pelissier, Lea Penazzi, Benjamin Piaud, Clément Rodrigues-Viguier, Gisele Roques, Maxime Roger, Thomas Saez, Guillaume Terrée, Najda Villefranque, Thomas Vourc’h and Daniel Yaacoub

PLOS ONE, 2023, vol. 18, issue 4, 1-54

Abstract: It was recently shown that radiation, conduction and convection can be combined within a single Monte Carlo algorithm and that such an algorithm immediately benefits from state-of-the-art computer-graphics advances when dealing with complex geometries. The theoretical foundations that make this coupling possible are fully exposed for the first time, supporting the intuitive pictures of continuous thermal paths that run through the different physics at work. First, the theoretical frameworks of propagators and Green’s functions are used to demonstrate that a coupled model involving different physical phenomena can be probabilized. Second, they are extended and made operational using the Feynman-Kac theory and stochastic processes. Finally, the theoretical framework is supported by a new proposal for an approximation of coupled Brownian trajectories compatible with the algorithmic design required by ray-tracing acceleration techniques in highly refined geometry.

Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0283681

DOI: 10.1371/journal.pone.0283681

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