Approximation of skewed interfaces with tensor-based model reduction procedures: application to the reduced basis hierarchical model reduction approach

Ohlberger M, Smetana K

Research article (journal) | Peer reviewed

Abstract

In this article we introduce a procedure, which allows to recover the potentially very good approximation properties of tensor-based model reduction procedures for the solution of partial differential equations in the presence of interfaces or strong gradients in the solution which are skewed with respect to the coordinate axes. The two key ideas are the location of the interface either by solving a lower-dimensional partial differential equation or by using data functions and the subsequent removal of the interface of the solution by choosing the determined interface as the lifting function of the Dirichlet boundary conditions. We demonstrate in numerical experiments for linear elliptic equations and the reduced basis-hierarchical model reduction approach that the proposed procedure locates the interface well and yields a significantly improved convergence behavior even in the case when we only consider an approximation of the interface.

Details about the publication

Volume321
Page range1185-1205
StatusPublished
Release year2016
Language in which the publication is writtenEnglish
DOI: 10.1016/j.jcp.2016.06.021
Link to the full texthttp://arxiv.org/pdf/1406.7426.pdf
Keywordsdimensional reduction; tensor-based model reduction; hierarchical model reduction; reduced basis methods; proper generalized decomposition; adaptive modelling

Authors from the University of Münster

Ohlberger, Mario
Professorship of Applied Mathematics, especially Numerics (Prof. Ohlberger)
Center for Nonlinear Science
Smetana, Kathrin
Professorship of Applied Mathematics, especially Numerics (Prof. Ohlberger)