Stéphane Blanco

Thermodynamics, Biophysics, Computational Physics

PhD Physics
A statistical approach to computational physics consitsts in first defining a random process representative of the initial physics, in the sense that its expection equals exactly the observable of interest, and then making a Monte Carlo estimate of this expectation using a large number of independant samples. When adressing transient spatialised physics, this leads to following random paths in both space and time, alterning among the involved coupled phenomena, and branching when a nonlinearity is encountered. EDSTAR (, in collaboration with Méso-Star (, aims at making such approaches accessible to engineers facing the question of modeling and analysing/optimizing complex systems.
This project collects the experimental and modelling work done by the collaborators to control the heat and mass transfer inside high temperature porous media. These media are intended to be used in high temperature and high efficiency exchangers used in solar thermal or thermochemical processes. One of the objectives is to optimize the geometry to maximize the efficiency. Ceramic or metallic foams with open cells are studied, but particular attention is given to structured porous geometry because the progress of additive manufacturing will enable the use of optimized geometry.

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