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  4. Reduced Basis Approximation And A Posteriori Error Estimates For Parametrized Elliptic Eigenvalue Problems
 
research article

Reduced Basis Approximation And A Posteriori Error Estimates For Parametrized Elliptic Eigenvalue Problems

Fumagalli, Ivan
•
Manzoni, Andrea  
•
Parolini, Nicola  
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2016
Esaim-Mathematical Modelling And Numerical Analysis-Modelisation Mathematique Et Analyse Numerique

We develop a new reduced basis (RB) method for the rapid and reliable approximation of parametrized elliptic eigenvalue problems. The method hinges upon dual weighted residual type a posteriori error indicators which estimate, for any value of the parameters, the error between the high-fidelity finite element approximation of the first eigenpair and the corresponding reduced basis approximation. The proposed error estimators are exploited not only to certify the RB approximation with respect to the high-fidelity one, but also to set up a greedy algorithm for the offline construction of a reduced basis space. Several numerical experiments show the overall validity of the proposed RB approach.

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Type
research article
DOI
10.1051/m2an/2016009
Web of Science ID

WOS:000388087600011

Author(s)
Fumagalli, Ivan
Manzoni, Andrea  
Parolini, Nicola  
Verani, Marco
Date Issued

2016

Publisher

Edp Sciences S A

Published in
Esaim-Mathematical Modelling And Numerical Analysis-Modelisation Mathematique Et Analyse Numerique
Volume

50

Issue

6

Start page

1857

End page

1885

Subjects

Parametrized eigenvalue problems

•

reduced basis method

•

a posteriori error estimation

•

greedy algorithm

•

dual weighted residual

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
CMCS  
Available on Infoscience
January 24, 2017
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/133698
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