Hybrid uncertain static analysis with random and interval fields

Wu, D; Gao, W

Hybrid uncertain static analysis with random and interval fields

Wu, D

Gao, W

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Publisher:: Elsevier
Publication Type:: Journal Article
Citation:: Computer Methods in Applied Mechanics and Engineering, 2017, 315, pp. 222-246
Issue Date:: 2017-03-01

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Field	Value	Language
dc.contributor.author	Wu, D https://orcid.org/0000-0002-7284-5024
dc.contributor.author	Gao, W
dc.date.accessioned	2022-08-29T04:38:50Z
dc.date.available	2022-08-29T04:38:50Z
dc.date.issued	2017-03-01
dc.identifier.citation	Computer Methods in Applied Mechanics and Engineering, 2017, 315, pp. 222-246
dc.identifier.issn	0045-7825
dc.identifier.issn	1879-2138
dc.identifier.uri	http://hdl.handle.net/10453/161018
dc.description.abstract	Uncertain static analysis of an engineering structure with diverse type of non-deterministic system parameter is investigated in this study. Unlike the traditional hybrid uncertain static analysis involving random and interval variables, the concept of random and interval fields has been implemented to model the spatially dependent uncertainties associated with the system inputs. A novel computational approach, namely the extended unified interval stochastic sampling (X-UISS) method, is proposed to calculate the statistical characteristics (i.e., mean and standard deviation) of the extreme bounds (i.e., lower and upper bounds) of the concerned responses (e.g., displacement and stress) of engineering structure involving hybrid spatially dependent uncertainties. Subsequently, by utilizing either parametric or nonparametric statistical analysis, the probability density functions (PDFs), as well as the cumulative distribution functions (CDFs), of the extreme bounds of the concerned structural responses can be effectively established. Consequently, the upper and lower bounds of either the concerned responses of the engineering structure at any particular percentile of probability, or the structural reliability against any specified capacities can be effectively secured. The applicability and effectiveness of the proposed computational analysis framework are illustrated through the numerical investigations on various examples.
dc.language	en
dc.publisher	Elsevier
dc.relation.ispartof	Computer Methods in Applied Mechanics and Engineering
dc.relation.isbasedon	10.1016/j.cma.2016.10.047
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	01 Mathematical Sciences, 09 Engineering
dc.subject.classification	Applied Mathematics
dc.title	Hybrid uncertain static analysis with random and interval fields
dc.type	Journal Article
utslib.citation.volume	315
utslib.for	01 Mathematical Sciences
utslib.for	09 Engineering
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	closed_access	*
pubs.consider-herdc	false
dc.date.updated	2022-08-29T04:38:48Z
pubs.publication-status	Published
pubs.volume	315

Abstract:

Uncertain static analysis of an engineering structure with diverse type of non-deterministic system parameter is investigated in this study. Unlike the traditional hybrid uncertain static analysis involving random and interval variables, the concept of random and interval fields has been implemented to model the spatially dependent uncertainties associated with the system inputs. A novel computational approach, namely the extended unified interval stochastic sampling (X-UISS) method, is proposed to calculate the statistical characteristics (i.e., mean and standard deviation) of the extreme bounds (i.e., lower and upper bounds) of the concerned responses (e.g., displacement and stress) of engineering structure involving hybrid spatially dependent uncertainties. Subsequently, by utilizing either parametric or nonparametric statistical analysis, the probability density functions (PDFs), as well as the cumulative distribution functions (CDFs), of the extreme bounds of the concerned structural responses can be effectively established. Consequently, the upper and lower bounds of either the concerned responses of the engineering structure at any particular percentile of probability, or the structural reliability against any specified capacities can be effectively secured. The applicability and effectiveness of the proposed computational analysis framework are illustrated through the numerical investigations on various examples.

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http://hdl.handle.net/10453/161018