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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. | 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. | ||
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| + | == Abstract == | ||
| + | <pdf>Media:Draft_Sanchez Pinedo_351038822933_abstract.pdf</pdf> | ||
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| + | == Full Paper == | ||
| + | <pdf>Media:Draft_Sanchez Pinedo_351038822933_paper.pdf</pdf> | ||
Latest revision as of 16:06, 25 November 2022
Summary
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.
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Published on 24/11/22
Accepted on 24/11/22
Submitted on 24/11/22
Volume Science Computing, 2022
DOI: 10.23967/eccomas.2022.213
Licence: CC BY-NC-SA license
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