Construction of local reduced spaces for Friedrichs' systems via randomized training

Engwer,Christian; Ohlberger, Mario; Renelt, Lukas

Research article in digital collection (conference) | Peer reviewed

Abstract

This contribution extends the localized training approach, traditionally employed for multiscale problems and parameterized partial differential equations (PDEs) featuring locally heterogeneous coefficients, to the class of linear, positive symmetric operators, known as Friedrichs' operators. Considering a local subdomain with corresponding oversampling domain we prove the compactness of the transfer operator which maps boundary data to solutions on the interior domain. While a Caccioppoli-inequality quantifying the energy decay to the interior holds true for all Friedrichs' systems, showing a compactness result for the graph-spaces hosting the solution is additionally necessary. We discuss the mixed formulation of a convection-diffusion-reaction problem where the necessary compactness result is obtained by the Picard-Weck-Weber theorem. Our numerical results, focusing on a scenario involving heterogeneous diffusion fields with multiple high-conductivity channels, demonstrate the effectiveness of the proposed method.

Details about the publication

Name of the repositoryProceedings of the Conference Algoritmy 2024
StatusPublished
Release year2024 (21/09/2024)
Language in which the publication is writtenEnglish
ConferenceCentral-European Conference on Scientific Computing, ALGORITMY, Podbanské, Slovakia
Link to the full texthttp://www.iam.fmph.uniba.sk/amuc/ojs/index.php/algoritmy/article/view/2144/1027
Keywordsmultiscale methods; localized training; Friedrichs’ systems

Authors from the University of Münster

Engwer, Christian
Professorship for Applications of Partial Differential Equations
Ohlberger, Mario
Professorship of Applied Mathematics, especially Numerics (Prof. Ohlberger)
Renelt, Lukas
Professorship of Applied Mathematics, especially Numerics (Prof. Ohlberger)