Greedy sampling of distributed parameters in the reduced-basis method by numerical optimization

Iapichino, Laura; Volkwein, Stefan

Greedy sampling of distributed parameters in the reduced-basis method by numerical optimization

Dateien

Iapichino_Volkwein_315.pdfGröße: 915.66 KBDownloads: 179

Datum

2013

Open Access-Veröffentlichung

Open Access Green

Sammlungen

Mathematik und Statistik
Zukunftskolleg

Publikationstyp

Working Paper/Technical Report

Publikationsstatus

Published

Zusammenfassung

In the present paper the authors study second-order elliptic parametric partial differential equations, where the Parameters are scalars or distributed functions. By utilizing a modified greedy algorithm a reduced-basis approximation is derived. This new strategy combines the classical greedy algorithm with techniques from PDE constrained optimization. Numerical examples for the Graetz problem illustrate the efficiency of the strategy to handle not only scalar, but also distributed parameter functions.

Fachgebiet (DDC)

510 Mathematik

Zitieren

ISO 690

IAPICHINO, Laura, Stefan VOLKWEIN, 2013. Greedy sampling of distributed parameters in the reduced-basis method by numerical optimization

BibTex

@techreport{Iapichino2013Greed-22838,
  year={2013},
  series={Konstanzer Schriften in Mathematik},
  title={Greedy sampling of distributed parameters in the reduced-basis method by numerical optimization},
  number={315},
  author={Iapichino, Laura and Volkwein, Stefan}
}

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