A surrogate model for uncertainty quantification and global sensitivity analysis of nonlinear large-scale dome structures

Zhang, H; Song, Y; Zhu, X; Zhang, Y; Wang, H; Gao, Y

A surrogate model for uncertainty quantification and global sensitivity analysis of nonlinear large-scale dome structures

Zhang, H Song, Y Zhu, X

Zhang, Y Wang, H Gao, Y

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Publisher:: HIGHER EDUCATION PRESS
Publication Type:: Journal Article
Citation:: Frontiers of Structural and Civil Engineering, 2023, 17, (12), pp. 1813-1829
Issue Date:: 2023-12-01

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Field	Value	Language
dc.contributor.author	Zhang, H
dc.contributor.author	Song, Y
dc.contributor.author	Zhu, X https://orcid.org/0000-0001-5083-9320
dc.contributor.author	Zhang, Y
dc.contributor.author	Wang, H
dc.contributor.author	Gao, Y
dc.date.accessioned	2024-03-24T03:31:53Z
dc.date.available	2024-03-24T03:31:53Z
dc.date.issued	2023-12-01
dc.identifier.citation	Frontiers of Structural and Civil Engineering, 2023, 17, (12), pp. 1813-1829
dc.identifier.issn	2095-2430
dc.identifier.issn	2095-2449
dc.identifier.uri	http://hdl.handle.net/10453/177047
dc.description.abstract	Full-scale dome structures intrinsically have numerous sources of irreducible aleatoric uncertainties. A large-scale numerical simulation of the dome structure is required to quantify the effects of these sources on the dynamic performance of the structure using the finite element method (FEM). To reduce the heavy computational burden, a surrogate model of a dome structure was constructed to solve this problem. The dynamic global sensitivity of elastic and elastoplastic structures was analyzed in the uncertainty quantification framework using fully quantitative variance- and distribution-based methods through the surrogate model. The model considered the predominant sources of uncertainty that have a significant influence on the performance of the dome structure. The effects of the variables on the structural performance indicators were quantified using the sensitivity index values of the different performance states. Finally, the effects of the sample size and correlation function on the accuracy of the surrogate model as well as the effects of the surrogate accuracy and failure probability on the sensitivity index values are discussed. The results show that surrogate modeling has high computational efficiency and acceptable accuracy in the uncertainty quantification of large-scale structures subjected to earthquakes in comparison to the conventional FEM.
dc.language	English
dc.publisher	HIGHER EDUCATION PRESS
dc.relation.ispartof	Frontiers of Structural and Civil Engineering
dc.relation.isbasedon	10.1007/s11709-023-0007-9
dc.rights	info:eu-repo/semantics/embargoedAccess
dc.rights	This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://dx.doi.org/10.1007/s11709-023-0007-9
dc.subject.classification	3302 Building
dc.subject.classification	4005 Civil engineering
dc.title	A surrogate model for uncertainty quantification and global sensitivity analysis of nonlinear large-scale dome structures
dc.type	Journal Article
utslib.citation.volume	17
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology/School of Civil and Environmental Engineering
utslib.copyright.status	embargoed	*
utslib.copyright.embargo	2025-01-12T00:00:00+1000Z
dc.date.updated	2024-03-24T03:31:50Z
pubs.issue	12
pubs.publication-status	Published
pubs.volume	17
utslib.citation.issue	12

Abstract:

Full-scale dome structures intrinsically have numerous sources of irreducible aleatoric uncertainties. A large-scale numerical simulation of the dome structure is required to quantify the effects of these sources on the dynamic performance of the structure using the finite element method (FEM). To reduce the heavy computational burden, a surrogate model of a dome structure was constructed to solve this problem. The dynamic global sensitivity of elastic and elastoplastic structures was analyzed in the uncertainty quantification framework using fully quantitative variance- and distribution-based methods through the surrogate model. The model considered the predominant sources of uncertainty that have a significant influence on the performance of the dome structure. The effects of the variables on the structural performance indicators were quantified using the sensitivity index values of the different performance states. Finally, the effects of the sample size and correlation function on the accuracy of the surrogate model as well as the effects of the surrogate accuracy and failure probability on the sensitivity index values are discussed. The results show that surrogate modeling has high computational efficiency and acceptable accuracy in the uncertainty quantification of large-scale structures subjected to earthquakes in comparison to the conventional FEM.

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http://hdl.handle.net/10453/177047