The use of reduced order models in the solution of inverse problems

The use of reduced order models in the solution of inverse problems

Sandu, Adrian; Ştefănescu, Răzvan; Rao, Vishwas; Nino, Elias

Abstract:

Reduced order modeling is now widely accepted as a powerful technique to increase the e ciency of PDE simulations by orders of magnitude. We discuss the use of reduced order modeling in the solution of inverse problems, posed as PDE-constrained optimization problems. Different avors of reduced order models, including POD DEIM and POD tensorial, are discussed. Also discussed are strategies for updating the reduced order basis and for controlling the progress of the optimization process.

Reduced order modeling is now widely accepted as a powerful technique to increase the e ciency of PDE simulations by orders of magnitude. We discuss the use of reduced order modeling in the solution of inverse problems, posed as PDE-constrained optimization problems. Different avors of reduced order models, including POD DEIM and POD tensorial, are discussed. Also discussed are strategies for updating the reduced order basis and for controlling the progress of the optimization process.

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Como citar:

Sandu, Adrian; Ştefănescu, Răzvan; Rao, Vishwas; Nino, Elias; "The use of reduced order models in the solution of inverse problems", p-24-24. In: Proceedings of the 13th International Symposium on Multiscale, Multifunctional and Functionally Graded Materials [=Blucher Material Science Proceedings, v.1, n.1]. São Paulo: Blucher, 2014.
ISSN 23589337, DOI