Stephan Rave

Julia Schleuß (Uni Münster): Localized model order reduction via local training and enrichment based on a residual localization strategy

Wednesday, 15.05.2024 14:15 im Raum M5

Mathematik und Informatik

To tackle parametric partial differential equations with highly heterogeneous coefficients, we propose an adaptive localized basis construction procedure based on both offline training and online enrichment. First, in the offline phase, a set of problem-adapted local basis functions is precomputed. Next, in the online phase, we use a localized residual-based a posteriori error estimator to investigate the accuracy of the reduced solution for any given new parameter. As the error estimator is localized, we can exploit it to adaptively enrich the reduced solution space locally where needed. The approach thus guarantees the accuracy of reduced solutions given any possibly insufficient reduced basis that was constructed during the offline phase. Numerical experiments demonstrate the efficiency of the proposed method.

Angelegt am 13.03.2024 von Stephan Rave
Geändert am 10.04.2024 von Stephan Rave
[Edit | Vorlage]

Oberseminar Numerik