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Explicit parametric solutions for Stokes flow and saddle-point problems with PGD

Author
Diez, P.; Zlotnik, S.; Huerta, A.
Type of activity
Presentation of work at congresses
Name of edition
Aerospace Europe CEAS 2017 Conference
Date of publication
2017
Presentation's date
2017-10-18
Abstract
Design optimization and uncertainty quantification, among other applications of industrial interest, require fast or multiple queries of some parametric model. The Proper Generalized Decomposition (PGD) provides a separable solution, a computational vademecum explicitly dependent on the parameters, efficiently computed with a greedy algorithm combined with an alternated directions scheme and compactly stored. This strategy has been successfully employed in many problems in computational mechanic...
Keywords
Brinkman models, Design optimization, PGD, computational vademecum, Proper Generalized Decomposition, Stokes models, boundary value problems, high-dimensional data, saddle-point problems, uncertainty quantification
Group of research
LACÀN - Numerical Methods for Applied Sciences and Engineering

Participants