Title: h-adaptation strategies and unified basis representation for surrogate and reduced order modelling of fluid flows with immersed/embedded parametrized geometries
Date: 2021-11-15 21:14
Authors: Nicolas Barral
Job_Duration: 1 an
Job_Employer: Inria Bordeaux
Les détails de l'offre: https://recrutement.inria.fr/public/classic/fr/offres/2021-04111
The postdoc will be within the framework of the European project EuroHPC-02-2019 eflows4HPC, and in collaboration with the partners of the pillar I of the project: CIMNE, SISSA, SIEMENS and Duke University.
The main objetive of this work is to develop improved adaptive remeshing techniques in the framework of model reduction and optimization with parametrized geometries, and in particular in conjunction with immersed and/or embedded boundary simulations. he purpose is twofold:
- on one side to propose an efficient (in terms of storage) and unified spatial basis setting to represent multiple solutions on unstructured adaptive meshes. This requirement is essential to provide an efficient unified representation of multiple solutions on adaptive meshes in a parametrized setting. This representation is necessary for several operations related to inverse modelling, of model reduction (e.g. method of snapshots), to compute statistics etc.
- on the other hand we aim at exploiting the information available in a parametrized setting to speed up the adaptation process itself by e.g. constructing appropriate surrogate models of mesh metrics or error estimators
These assignements will both involve theoretical work related to error estimation and approximation in physical and parametric space, with a final demonstration in an efficient setting involving workflows developed at the Barcelona Supercomputing center and based on open source software developed at Inria, Cimne, and at Sissa.