Offres de Thèses et Postdocs

The wind turbine production in a floating wind farm depends essentially on its position, the wind and the state of the sea. The influence of the state of the sea, in particular, is poorly known, because it has not been an influential factor in the development of installed wind farms. First of all, the influence of the movement of the platform directly affects the production capacity of the wind turbine. But beyond that, it induces significant modifications to the wake, and in the context of commercial farms, where the turbines are not widely spaced, leads to interactions between turbines which are still unknown. As Numerical simulations are very expensive, from numerical simulation and historical data, the environmental conditions can be modeled by stochastic models which are faster to simulate. hus, by combining these stochastic models with the physical model, it is possible to evaluate the uncertainty relating to the key parameters (extractable energy, wake topology).

En tentant de tirer profit du coût mesuré des approches RANS et des qualités prédictives des approches LES, les approches hybrides RANS/LES présentent un intérêt fort pour de nombreuses applications mais continuent à se heurter au problème de la gestion des zones de transition. En l’absence d’instabilité hydrodynamique naturellement présente dans le domaine de calcul ou lorsque celle-ci n’est pas suffisamment résolue, la qualité des prévisions LES dépend ainsi en grande partie des fluctuations prescrites dans la zone de transition. L’objectif du post-doctorat proposé en collaboration avec le CEMEF est de développer une méthode d’apprentissage automatique de génération de fluctuations pour les zones de recouvrement RANS/LES. Deux axes ont été identifiés visant à réduire l’étendue des zones grises ; le premier concerne spécifiquement la qualité du signal synthétique généré alors que le deuxième axe s’attache aux paramètres de contrôle d’une méthode de forçage.

The Laboratory of Fluid Mechanics and Acoustics (LMFA) is seeking a highly qualified postdoctoral researcher to contribute to the development of dynamic calibration and optimization strategies for subgrid-scale turbulence modeling within the framework of LB simulations of engineering flows.

Fluid-structure interactions (FSI) in a nuclear reactor core involve thermalhydraulics mechanisms at different scales. FSI simulations at the local (CFD) scale are feasible only for reduced domains. Such domains must however be representative of the actual core conditions. A multi-scale approach is therefore required to understand how to consistently simulate the core thermalhydraulics and the related FSI phenomena.

An experimental project about the generation and characterisation of an atmospheric boundary layer aiming to study the stability of drones within it.

This project is a postdoctoral proposal in the stochastic physics of turbulence aiming to analyze stylized models of multifractal transport and to assess their relevance for turbulent transport.

Fully funded by the French ANR Young Researcher project called SONATE, the aim of the thesis is to understand the aerodynamics, performance and losses of a wind farm at different scales and under inlet flows that correspond to realistic conditions of a real wind farm. The PhD student will carry out large-scale experiments in the atmospheric section of the PRISME wind tunnel, using various measurement tools (pressure, hot-wire, PIV). From these measurements, the project will focus on building representative physics-based reduced-order models, capable of predicting the performance of the wind farms with different inputs depending on the flow conditions (yaw, turbulence, angular momentum added by the blades, etc.).Supervisors: Dr. Cédric Raibaudo (advisor, grant recipient), Pr. Nicolas Mazellier (thesis director)