On Uncertainty Quantification of Eigenvalues and Eigenspaces with Higher Multiplicity
Author:
Affiliation:
1. Institute for Numerical Simulation, Friedrich-Hirzebruch-Allee 7, 53115 Bonn, Germany.
Funder
Deutsche Forschungsgemeinschaft
DFG under Germany’s Excellence Strategy
Publisher
Society for Industrial & Applied Mathematics (SIAM)
Reference52 articles.
1. Random matrix eigenvalue problems in structural dynamics
2. Sparse Tensor Approximation of Parametric Eigenvalue Problems
3. Superconducting TESLA cavities
4. Finite Element Methods in Probabilistic Structural Analysis: A Selective Review
5. A Low-Rank Inexact Newton–Krylov Method for Stochastic Eigenvalue Problems
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1. Analytic and Gevrey Class Regularity for Parametric Elliptic Eigenvalue Problems and Applications;SIAM Journal on Numerical Analysis;2024-08-05
2. Shape uncertainty quantification of Maxwell eigenvalues and -modes with application to TESLA cavities;Computer Methods in Applied Mechanics and Engineering;2024-08
3. Efficient Shape Uncertainty Quantification for the TESLA Cavity;2024 IEEE 21st Biennial Conference on Electromagnetic Field Computation (CEFC);2024-06-02
4. The Gevrey class implicit mapping theorem with application to UQ of semilinear elliptic PDEs;Mathematical Models and Methods in Applied Sciences;2024-03-05
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