A space-time PGD approach for 3D nonlinear parametrized problems néron boucard
Résumé
This paper deals with the recurring question of the resolution of a problem for many different configurations. In spite of the fact that computational power has been increasing continuously, the direct treatment of such a problem often remains inaccessible. When dealing with high-fidelity models, the number of degrees of freedom can lead to systems so large that direct techniques are inapplicable. Model reduction techniques constitute an efficient way to circumvent this difficulty by seeking the solution of a problem in a reduced-order basis (ROB), whose dimension is much lower than the original vector space. A posteriori methods usually consist in defining this ROB by the decomposition of the solution of a surrogate model relevant to the initial model. A priori methods follow a different path by building progressively an approximate separated representation of the solution, without assuming any basis