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https://hdl.handle.net/1822/53589
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Campo DC | Valor | Idioma |
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dc.contributor.author | Guimarães, Hugo | por |
dc.contributor.author | Matos, José C. | por |
dc.contributor.author | Henriques, António A. | por |
dc.date.accessioned | 2018-03-27T14:58:07Z | - |
dc.date.issued | 2018-07 | - |
dc.date.submitted | 2017-04 | - |
dc.identifier.citation | Guimarães, H., Matos, J. C., & Henriques, A. A. (2018). An innovative adaptive sparse response surface method for structural reliability analysis. Structural Safety, 73, 12-28 | por |
dc.identifier.issn | 0167-4730 | por |
dc.identifier.uri | https://hdl.handle.net/1822/53589 | - |
dc.description.abstract | In the scope of infrastructure risk assessment, structural reliability analysis leads to a challenging problem in order to deal with conflicting objectives: accurate estimation of failure probabilities and computational efficiency. Since the application of classical reliability methods is limited and often leads to a prohibitive computational cost, metamodeling techniques (e.g. polynomial chaos, kriging, response surface methods (RSM), etc.) have been widely used. Nevertheless, existing RSM present limitations handling with highly non-linear limit states, large-scale problems and approximation error. To overcome these problems, this paper describes a cutting-edge response surface algorithm covering the following issues: (i) dimensionality reduction by a variable screening procedure; (ii) definition of a promising search domain; (iii) initial experimental design based on an optimized space-filling scheme; (iv) model selection according to a stepwise regression procedure; (v) model validation by a cross-validation approach; (vi) model fitting using a double weighted regression technique; (vii) sequential sampling scheme by exploring a defined region of interest; (viii) confidence interval of reliability estimates based on a bootstrapping technique. With the aim of proving its efficiency, a wide collection of six illustration examples, concerning both analytical and FE-based problems, was selected. By benchmarking obtained results with literature findings, proposed method not only outperforms existing RSM, but also provides a powerful alternative to the use of other metamodeling techniques | por |
dc.description.sponsorship | ISISE Institute for Sustainability and Innovation in Structural Engineering (PEst-C/ECI/UI4029/2011 FCOM-01-0124-FEDER-022681), FCT Portuguese Scientific Foundation for the research grant PD/BD/113677/2015 under the PhD Programme “Analysis and Mitigation of Risks in Infrastructures InfraRisk-”. The third author would also like to thank the project POCI-01-0145-FEDER-007457 – CONSTRUCT – Institute of R&D in Structures and Construction. This work was also partly financed by FEDER funds through the Competitivity Factors Operational Programme – COMPETE and by national funds through FCT Foundation for Science and Technology within the scope of the project POCI-01-0145-FEDER-007633 | por |
dc.language.iso | eng | por |
dc.publisher | Elsevier 1 | por |
dc.rights | closedAccess | por |
dc.subject | Structural reliability | por |
dc.subject | Response surface | por |
dc.subject | Metamodel | por |
dc.subject | Small failure probability | por |
dc.subject | Confidence interval | por |
dc.title | An innovative adaptive sparse response surface method for structural reliability analysis | por |
dc.type | article | - |
dc.peerreviewed | yes | por |
dc.relation.publisherversion | https://www.sciencedirect.com/science/article/pii/S0167473017301108 | por |
oaire.citationStartPage | 12 | por |
oaire.citationEndPage | 28 | por |
oaire.citationVolume | 73 | por |
dc.identifier.doi | 10.1016/j.strusafe.2018.02.001 | por |
dc.subject.fos | Engenharia e Tecnologia::Engenharia Civil | por |
dc.description.publicationversion | info:eu-repo/semantics/publishedVersion | por |
dc.subject.wos | Science & Technology | por |
sdum.journal | Structural Safety | por |
Aparece nas coleções: | ISISE - Artigos em Revistas Internacionais |
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Ficheiro | Descrição | Tamanho | Formato | |
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1-s2.0-S0167473017301108-main.pdf Acesso restrito! | 1,57 MB | Adobe PDF | Ver/Abrir |