PhD Position at Inria Saclay-Ile de France Title: Anisotropic Mesh Adaptation for RANS Simulations with Moving Geometries in Aeronautics
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Subject: The aim of mesh adaptation is to generate automatically the best mesh to perform a specific numerical simulation [1]. It results in a powerful methodology that reduces significantly the size of the mesh required to reach the desired accuracy. Thus, it impacts favorably the simulation CPU time and memory requirement. Moreover, as the generated adapted mesh is in agreement with the physics of the flow, for some applications, this is the only way to obtain an accurate prediction [3]. Nowadays, mesh adaptation is a mature tool which is well-posed mathematically [9, 10]. And, as it is fully automatic, it has started to be used in industrial R&D departments. Indeed, it has already proved, throughout many publications and applications, its superiority with respect to fixed mesh. However, its domain of application is in majority restricted to inviscid steady [3, 11] or unsteady flows [2, 6]. It has been recently extended to turbulent flows for steady problems [8] (Figure 1) and to moving geometry for unsteady inviscid flows [5] (Figure 2). This thesis aims at first extending mesh adaptation for turbulent flows (RANS) to unsteady turbulent flows (URANS) and second to take into account moving geometries. The aeronautics targeted applications are turbomachinery, rotor blades and store separation. This subject is of paramount importance because URANS simulations with moving geometries are very expensive in CPU time and memory footprint which requires large clusters to perform this type of simulations. In consequence, this kind of simulations are rarely performed in industry. Mesh adaptation is a way to reduce CPU time and memory footprint and make this type of simulation accessible on more reasonable computing ressources.
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PhD Position at Inria Saclay-Ile de France Title: Methods for generating quad-dominant and hex-dominant adaptive meshes for CFD applications
Subject: The aim of mesh adaptation is to generate the best mesh to perform a specific numerical simulation [1]. It results in a powerful methodology that reduces significantly the size of the mesh required to reach the desired accuracy. Thus, it impacts favorably the simulation CPU time and memory requirement. Moreover, as the generated adapted mesh is in agreement with the physics of the flow...
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تاریخ انتشار 2018