An efficient reduced‐order method for stochastic eigenvalue analysis-Reference-Cited by-同舟云学术

An efficient reduced‐order method for stochastic eigenvalue analysis

Published:2022-08-17 Issue:23 Volume:123 Page:5884-5906
ISSN:0029-5981
Container-title:International Journal for Numerical Methods in Engineering
language:en
Short-container-title:Numerical Meth Engineering

Author:

Zheng Zhibao¹²^ORCID,Beer Michael³⁴⁵,Nackenhorst Udo¹²

Affiliation:

1. Institute of Mechanics and Computational Mechanics Leibniz Universität Hannover Hannover Germany

2. International Research Training Group 2657 Leibniz Universität Hannover Hannover Germany

3. Institute for Risk and Reliability Leibniz Universität Hannover Hannover Germany

4. Institute for Risk and Uncertainty and School of Engineering University of Liverpool Liverpool UK

5. International Joint Research Center for Resilient Infrastructure & International Joint Research Center for Engineering Reliability and Stochastic Mechanics Tongji University Shanghai China

Funder

Alexander von Humboldt-Stiftung

Deutsche Stiftung Friedensforschung

Publisher

Wiley

Subject

Applied Mathematics,General Engineering,Numerical Analysis

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/nme.7092

Reference46 articles.

1. An accelerated subspace iteration method

2. Numerical Methods for Large Eigenvalue Problems

3. Random eigenvalue problems for large systems

4. GilbertAD ScheichlR.Multilevel quasi‐Monte Carlo for random elliptic eigenvalue problems II: efficient algorithms and numerical results. arXiv preprint arXiv:2103.03407 2021.

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