Meta-model based stochastic isogeometric analysis of composite plates

Liu, Z; Yang, M; Cheng, J; Wu, D; Tan, J

Meta-model based stochastic isogeometric analysis of composite plates

Liu, Z Yang, M Cheng, J Wu, D

Tan, J

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Publisher:: Elsevier
Publication Type:: Journal Article
Citation:: International Journal of Mechanical Sciences, 2021, 194, pp. 1-13
Issue Date:: 2021-03-15

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Field	Value	Language
dc.contributor.author	Liu, Z
dc.contributor.author	Yang, M
dc.contributor.author	Cheng, J
dc.contributor.author	Wu, D https://orcid.org/0000-0002-7284-5024
dc.contributor.author	Tan, J
dc.date.accessioned	2022-06-21T03:40:44Z
dc.date.available	2022-06-21T03:40:44Z
dc.date.issued	2021-03-15
dc.identifier.citation	International Journal of Mechanical Sciences, 2021, 194, pp. 1-13
dc.identifier.issn	0020-7403
dc.identifier.issn	1879-2162
dc.identifier.uri	http://hdl.handle.net/10453/158295
dc.description.abstract	A stochastic isogeometric analysis approach (SIGA) is presented for functionally graded porous plates with graphene platelets reinforcement (FGP-GPLs). Different kinds of random fields and variables are applied to describe the uncertain system inputs which are including material properties of the FGP matrix and graphene platelets, magnitudes and directions of applied loads. A Nyström based Karhunen-Loève expansion is presented for random field discretization within the IGA scheme. The arbitrary polynomial chaos-Kriging (aPCK) method is presented for uncertainty quantification. To sustain the robustness of the aPCK approach for engineering problems involving high-dimension of uncertainty, a new Dagum kernel function is introduced in Kriging. The mean, standard deviation, probability density function (PDF) and cumulative distribution function (CDF) of structural outputs can be effectively estimated. Three illustrative examples are investigated to assess the performance of the proposed method for mathematical and engineering applications.
dc.language	en
dc.publisher	Elsevier
dc.relation.ispartof	International Journal of Mechanical Sciences
dc.relation.isbasedon	10.1016/j.ijmecsci.2020.106194
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0905 Civil Engineering, 0910 Manufacturing Engineering, 0913 Mechanical Engineering
dc.subject.classification	Mechanical Engineering & Transports
dc.title	Meta-model based stochastic isogeometric analysis of composite plates
dc.type	Journal Article
utslib.citation.volume	194
utslib.for	0905 Civil Engineering
utslib.for	0910 Manufacturing Engineering
utslib.for	0913 Mechanical 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	2022-06-21T03:40:42Z
pubs.publication-status	Published
pubs.volume	194

Abstract:

A stochastic isogeometric analysis approach (SIGA) is presented for functionally graded porous plates with graphene platelets reinforcement (FGP-GPLs). Different kinds of random fields and variables are applied to describe the uncertain system inputs which are including material properties of the FGP matrix and graphene platelets, magnitudes and directions of applied loads. A Nyström based Karhunen-Loève expansion is presented for random field discretization within the IGA scheme. The arbitrary polynomial chaos-Kriging (aPCK) method is presented for uncertainty quantification. To sustain the robustness of the aPCK approach for engineering problems involving high-dimension of uncertainty, a new Dagum kernel function is introduced in Kriging. The mean, standard deviation, probability density function (PDF) and cumulative distribution function (CDF) of structural outputs can be effectively estimated. Three illustrative examples are investigated to assess the performance of the proposed method for mathematical and engineering applications.

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http://hdl.handle.net/10453/158295