L’objectif est de modéliser la croissance et l’évolution microstructurale de couches minces polycristallines en développant un code de simulation numérique par Monte Carlo cinétique (kMC) qui prend en compte les spécificités des dépôts physiques en phase vapeur (PVD). Pour cela, le (la) post–doctorant(e) devra, dans le cadre du projet DREAM, lier les paramètres de dépôt (énergie déposée, flux, température du substrat, nature de surface…) et les réactions chimiques aux interfaces avec la formation de joints de grains (GB), la microstructure (granulométrie, texture) l’évolution de la morphologie (rugosité, facettage) et la création de défauts qui ont lieu lors de la croissance de couches minces de métaux polycristallins via une simulation multi–échelle.
CNRS - Université de Poitiers – ISAE-ENSMA - UPR 3346
11 Boulevard Marie et Pierre Curie
Site du SP2MI-H1
86360 Chasseneuil du Poitou
Les candidats doivent impérativement postuler sur le site de l'UP :
=> https://www.univ-poitiers.fr/documents/0gb01-chercheur-se-post-doctorant-junior-ufr-sciences-fondamentales-et-appliquees/
Début de publication : 30/08/2023
Date de fin de publication : 30/09/2023
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CDD Technicien-ne électronicien-ne - 12 Mois - Catégorie B
POST-DOC (M/F) - Control by Machine Learning of bluff body wakes
At the CNRS-Laboratory PPRIME, based at the Futuroscope, this post-doctorate position is part of the French ANR COWAVE program between the laboratories PRISME in Orleans, Pprime in Poitiers, LHEEA in Nantes and the PSA automotive industry. This Post-Doc position concerns the Pprime contribution to the COWAVE project which aims the experimental exploration of closed-loop wake control strategies with mobile flaps in a water tunnel facility. Three-dimensional bluff-body wakes generate pressure drag and side forces and thus contribute significantly to the fuel consumption and pollutant emission of road vehicles. Despite this crucial impact and the numerous attempts to reduce harmful environmental effect of bluff body wakes by flow control it is still unclear what is the most efficient control strategy! In this context, the ANR project COWAVE addresses two fundamental aspects of wake control: - First, what kind of actuators are most efficient? While most closed-loop control strategies use viscous entrainment effects to actuate the shear layers in the wake, the exploitation of pressure forces produced by mobile deflectors could be an interesting alternative to be tested. - Second, for the implementation of closed-loop control, we want to test if control strategies obtained by machine learning techniques allow to obtain better efficiency and robustness than the more classical model-based approaches? The proposed Post-Doc position is part of the French ANR COWAVE program between the laboratories PRISME in Orleans, Pprime in Poitiers, LHEEA in Nantes and the PSA automotive industry. This Post-Doc position concerns the Pprime contribution to the COWAVE project which aims the experimental exploration of closed-loop wake control strategies with mobile flaps in a water tunnel facility. APPLY Follow link / Application Deadline : 12 March 2021 https://bit.ly/3qDG6Ml