ON THE MATCHING OF EIGENSOLUTIONS TO PARAMETRIC PARTIAL DIFFERENTIAL EQUATIONS

Moataz M. Alghamdi, Fleurianne Bertrand, Daniele Boffi, Francesca Bonizzoni, Abdul Halim, Gopal Priyadarshi

Research output: Contribution to conferencePaperpeer-review

1 Scopus citations

Abstract

In this paper a novel numerical approximation of parametric eigenvalue problems is presented. We motivate our study with the analysis of a POD reduced order model for a simple one dimensional example. In particular, we introduce a new algorithm capable to track the matching of eigenvalues when the parameters vary.

Original languageEnglish (US)
DOIs
StatePublished - 2022
Event8th European Congress on Computational Methods in Applied Sciences and Engineering, ECCOMAS Congress 2022 - Oslo, Norway
Duration: Jun 5 2022Jun 9 2022

Conference

Conference8th European Congress on Computational Methods in Applied Sciences and Engineering, ECCOMAS Congress 2022
Country/TerritoryNorway
CityOslo
Period06/5/2206/9/22

Bibliographical note

Funding Information:
The work of F. Bertrand, D. Boffi, and A. Halim was supported by the Competitive Research Grants Program CRG2020 “Synthetic data-driven model reduction methods for modal analysis” awarded by the King Abdullah University of Science and Technology (KAUST). D. Boffi is member of the INdAM Research group GNCS and his research is partially supported by IMATI/CNR and by PRIN/MIUR. F. Bonizzoni is member of the INdAM Research group GNCS and her work is part of a project that has received funding from the European Research Council ERC under the European Union’s Horizon 2020 research and innovation program (Grant agreement No. 865751).

Publisher Copyright:
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Keywords

  • Eigenvalue matching
  • Model reduction
  • Parametric eigenvalue problems

ASJC Scopus subject areas

  • Mechanical Engineering

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