Inverse Subspace Iteration for Spectral Stochastic Finite Element Methods
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Publication:2801326
DOI10.1137/140999359zbMath1336.65060arXiv1512.04613OpenAlexW3102178085MaRDI QIDQ2801326
Bedřich Sousedík, Howard C. Elman
Publication date: 6 April 2016
Published in: SIAM/ASA Journal on Uncertainty Quantification (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1512.04613
Related Items (8)
Stochastic Galerkin Methods for Linear Stability Analysis of Systems with Parametric Uncertainty ⋮ Stochastic collocation method for computing eigenspaces of parameter-dependent operators ⋮ An efficient reduced‐order method for stochastic eigenvalue analysis ⋮ Asymptotic convergence of spectral inverse iterations for stochastic eigenvalue problems ⋮ Inexact Methods for Symmetric Stochastic Eigenvalue Problems ⋮ Multiparametric shell eigenvalue problems ⋮ Low-Rank Solution Methods for Stochastic Eigenvalue Problems ⋮ A low-rank inexact Newton-Krylov method for stochastic eigenvalue problems
Uses Software
Cites Work
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- Application of the random eigenvalue problem in forced response analysis of a linear stochastic structure
- Solving stochastic systems with low-rank tensor compression
- Approximate methods for stochastic eigenvalue problems
- Hybrid perturbation-polynomial chaos approaches to the random algebraic eigenvalue problem
- Galerkin methods for linear and nonlinear elliptic stochastic partial differential equations
- Numerical integration using sparse grids
- Two-sided and alternating Jacobi-Davidson
- A method for solving stochastic eigenvalue problems
- A method for solving stochastic eigenvalue problems II
- MATLAB codes for finite element analysis. Solids and structures. With CD-ROM
- High dimensional integration of smooth functions over cubes
- Uncertainty quantification for Markov chain models
- Efficient characterization of the random eigenvalue problem in a polynomial chaos decomposition
- Stochastic convergence acceleration through basis enrichment of polynomial chaos expansions
- Spectral Methods for Uncertainty Quantification
- The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations
- An invariant subspace‐based approach to the random eigenvalue problem of systems with clustered spectrum
- The Stochastic Perturbation Method for Computational Mechanics
- Hierarchical Schur complement preconditioner for the stochastic Galerkin finite element methods
- Iterative solution of the random eigenvalue problem with application to spectral stochastic finite element systems
- Is Gauss Quadrature Better than Clenshaw–Curtis?
- Random Eigenvalue Problems in Structural Analysis
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