Approximation of constrained problems using the PGD method with application to pure Neumann problems

作者：Kergrene Kenan; Prudhomme Serge^*; Chamoin Ludovic; Laforest Marc

来源：Computer Methods in Applied Mechanics and Engineering, 2017, 317: 507-525.

DOI：10.1016/j.cma.2016.12.023

• Model reduction
• Low-rank approximation
• Tensor product approximation
• Proper Generalized Decomposition (PGD)
• Constrained problem
• Mixed formulation

In 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.

• 出版日期2017-4-15