C. Coustet

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Richard Fournier

Laboratoire Plasma et Conversion d'Energie

Cyril Caliot

Centre National de la Recherche Scientifique

Mouna El-Hafi

IMT Mines Albi

Léa Penazzi

Institut Universitaire des Systèmes Thermiques Industriels

Stéphane Blanco

Laboratoire Plasma et Conversion d'Energie

Jacques Gautrais

Centre de Recherches sur la Cognition Animale

M. Sans

Centre de Recherche d'Albi en génie des Procédés, des SOlides Divisés, de l'Énergie et de l'Environnement

Loris Ibarrart

Centre National d'Études Spatiales

Mathieu Galtier

Centre National de la Recherche Scientifique

Isabelle Rupp

Électricité de France (France)

Cooperative Institutions

Centre National de la Recherche Scientifique

Université Toulouse III - Paul Sabatier

Laboratoire Plasma et Conversion d'Energie

Université de Toulouse

IMT Mines Albi

Institut National Polytechnique de Toulouse

ÉN

École Nationale Supérieure d'Électrotechnique, d'Électronique, d'Informatique, d'Hydraulique et des Télécommunications

Commissariat à l'Énergie Atomique et aux Énergies Alternatives

Centre de Recherche d'Albi en génie des Procédés, des SOlides Divisés, de l'Énergie et de l'Environnement

Université de Lorraine

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Transfer function estimation with SMC method for combined heat transfer: insensitivity to detail refinement of complex geometries

Léa Penazzi S. Blanco Cyril Caliot C. Coustet Mouna El-Hafi

The optimization of thermal transfers in engineering systems such as heat exchangers requires the analysis of the influence of heat sources upon the temperature at various positions of interest in the studied system. In order to achieve the resolution of the combined modes of heat transfer through these systems, their couplings and the complex 3D geometries involved need to be integrated with full accuracy. Recent developments in probabilistic formulations in the context of transient combined heat transfer (linearized conduction-radiation-convection) have opened a new route to solving such problems with Monte Carlo (MC) algorithms, using state-of-the-art computer graphics digital libraries to handle complex geometries. To estimate the temperature at a probe point of interest, random paths are generated from its position and propagated through the geometry until a known temperature is reached. From a single MC calculation to sample the path statistics, the Symbolic Monte Carlo (SMC) method is used to express the probe temperature as a linear function of the sources. This function can then be used to estimate the probe temperature for any source values, alleviating the need to repeat Monte-Carlo simulations for each source condition, resulting in greatly reduced computation time. This approach is applied to the case of an open-cavity porous medium and computation time insensitivity to the complexity and fineness of the geometry is demonstrated.

10.1615/ichmt.2021.cht-21.300

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Citations (2)

Complementary Finite Element and Monte-Carlo Methods to Solve Industrial Thermal Problems

EPJ Web of Conferences (2024)

C. Péniguel Isabelle Rupp Richard Fournier Stéphane Blanco Vincent Eymet

This paper presents the integration of a Monte-Carlo solver inside SYRTHES, an open-source thermal code, originally based on finite elements method. Insensitive to both the geometric complexity of the model and the fineness of its discretization, this stochastic method is a good complementary option to simulate large configurations with specific locations of interest. Radiation, conduction and convection can be combined to solve thermal problems in complex geometries. The Monte-Carlo method is described before showing its integration in the code SYRTHES. Comparisons against results obtained thanks to finite elements and Monte-Carlo approaches or analytical solutions are presented. Finally, industrial cases illustrate the advantages of using these two complementary approaches.

Solver

Monte Carlo integration

10.1051/epjconf/202430206003

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Functional estimation of the junction temperature with Monte Carlo method for electronic module cooling

Léa Penazzi Anne Castelan Stéphane Blanco Cyril Caliot C. Coustet

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Path integrals formulations leading to propagator evaluation for coupled linear physics in large geometric models

Computer Physics Communications (2023)

Léa Penazzi Stéphane Blanco Cyril Caliot C. Coustet Mouna El-Hafi

Propagator

10.1016/j.cpc.2023.108911

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TOWARD THE USE OF SYMBOLIC MONTE CARLO FOR CONDUCTION-RADIATION COUPLING IN COMPLEX GEOMETRIES

Léa Penazzi Stéphane Blanco Cyril Caliot C. Coustet Mouna El-Hafi

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 transfer 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.

Thermal Radiation

10.1615/rad-19.380

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Citations (5)