TOWARD THE USE OF SYMBOLIC MONTE CARLO FOR CONDUCTION-RADIATION COUPLING IN COMPLEX GEOMETRIES
Author(s) -
Léa Penazzi,
Stéphane Blanco,
Cyril Caliot,
C. Coustet,
Mouna El-Hafi,
Richard Fournier,
Mathieu Galtier,
Loris Ibarrart,
Maxime Roger
Publication year - 2019
Publication title -
hal (le centre pour la communication scientifique directe)
Language(s) - English
Resource type - Conference proceedings
DOI - 10.1615/rad-19.380
Subject(s) - monte carlo method , thermal conduction , radiative transfer , statistical physics , coupling (piping) , heat transfer , thermal radiation , convection , computation , monte carlo molecular modeling , physics , function (biology) , transfer function , computer science , computational physics , mechanics , algorithm , mathematics , optics , thermodynamics , markov chain monte carlo , engineering , mechanical engineering , statistics , evolutionary biology , biology , electrical engineering
We address the interest of using Symbolic Monte Carlo to obtain a reduced model for conduction-radiation coupling in complex geometries. Symbolic Monte Carlo was successfully used for radiative transfer in a decoupled manner, but no attempt has yet been reported to extend its use to radiation coupled with other modes. Here we show that from a unique Monte Carlo simulation of radiation coupled with conduction in a semi-transparent solid surrounded by a convective flow, it is possible to build a formulation of the local temperature as function of the convective heat trans- fer coefficient, for instance, including the evaluation of uncertainty. This reduced model (a transfer function) enables to decrease the computation time when the function needs to be evaluated plenty of times for different values of the parameters as in optimization or control algorithms.
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