Approximation of constrained problems using the PGD method with application to pure Neumann problems
Embargo End Date2019-01-13
Permanent link to this recordhttp://hdl.handle.net/10754/668543
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AbstractIn this paper we introduce, analyze, and compare several approaches designed to incorporate a linear (or affine) constraint within the Proper Generalized Decomposition framework. We apply the considered methods and numerical strategies to two classes of problems: the pure Neumann case where the role of the constraint is to recover unicity of the solution; and the Robin case, where the constraint forces the solution to move away from the already existing unique global minimizer of the energy functional.
CitationKergrene, K., Prudhomme, S., Chamoin, L., & Laforest, M. (2017). Approximation of constrained problems using the PGD method with application to pure Neumann problems. Computer Methods in Applied Mechanics and Engineering, 317, 507–525. doi:10.1016/j.cma.2016.12.023
SponsorsSP is grateful for the support by a Discovery Grant from the Natural Sciences and Engineering Research Council of Canada. He also acknowledges the support by KAUST under Award Number OCRF-2014-CRG3-2281.