Adaptive POD basis computation for parametrized nonlinear systems using optimal snapshot location

Lass, Oliver; Volkwein, Stefan

Adaptive POD basis computation for parametrized nonlinear systems using optimal snapshot location

Dateien

LassVolkwein.pdfGröße: 847.66 KBDownloads: 385

Datum

2012

Open Access-Veröffentlichung

Open Access Green

Sammlungen

Mathematik und Statistik

Publikationstyp

Preprint

Publikationsstatus

Published

Zusammenfassung

The construction of reduced-order models for parametrized partial differential systems using proper orthogonal decomposition (POD) is based on the information of the so-called snapshots. These provide the spatial distribution of the nonlinear system at discrete parameter and/or time instances. In this work a strategy is used, where the POD reduced-order model is improved by choosing additional snapshot locations in an optimal way; see Kunisch and Volkwein (ESAIM: M2AN, 44:509-529, 2010). These optimal snapshot locations influences the POD basis functions and therefore the POD reduced-order model. This strategy is used to build up a POD basis on a parameter set in an adaptive way. The approach is illustrated by the construction of the POD reduced-order model for the complex-valued Helmholtz equation.

Fachgebiet (DDC)

510 Mathematik

Schlagwörter

Model reduction, proper orthogonal decomposition, optimal snapshot locations, Helmholtz equation, optimal control

Zitieren

ISO 690

LASS, Oliver, Stefan VOLKWEIN, 2012. Adaptive POD basis computation for parametrized nonlinear systems using optimal snapshot location

BibTex

@unpublished{Lass2012Adapt-19173,
  year={2012},
  title={Adaptive POD basis computation for parametrized nonlinear systems using optimal snapshot location},
  author={Lass, Oliver and Volkwein, Stefan}
}

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Universitätsbibliographie

Ja