Journal article
A modular nonlinear stochastic finite element formulation for uncertainty estimation
- Abstract:
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The Monte Carlo method is widely used for the estimation of uncertainties in mechanical engineering design. However, while flexible, this method remains impractical in terms of computational time and scalability. To bypass these limitations, other more efficient approaches such as the Galerkin stochastic finite element method (GSFEM) or the collocation method have been proposed. GSFEM provides accurate output statistics, has the advantage of being sampling independent and can be modular in te...
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- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, pdf, 1.0MB, Terms of use)
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- Publisher copy:
- 10.1016/j.cma.2022.115044
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Bibliographic Details
- Publisher:
- Elsevier
- Journal:
- Computer Methods in Applied Mechanics and Engineering More from this journal
- Volume:
- 396
- Article number:
- 115044
- Publication date:
- 2022-05-25
- Acceptance date:
- 2022-04-21
- DOI:
- ISSN:
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0045-7825
Item Description
- Language:
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English
- Keywords:
- Pubs id:
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1259816
- Local pid:
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pubs:1259816
- Deposit date:
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2022-05-16
Terms of use
- Copyright holder:
- Ammouche and Jérusalem
- Copyright date:
- 2022
- Rights statement:
- /© 2022 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons. org/licenses/by/4.0/).
- Licence:
- CC Attribution (CC BY)
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