Statistical analysis of the material, geometrical and imperfection characteristics of structural stainless steels and members

Traditional member-based two-step design approaches included in current structural codes for steel structures, as well as more recent system-based direct-design alternatives, require building rigorous structural reliability frameworks for the calibration of partial coefficients (resistance factors)...

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Autores: Arrayago Luquin, Itsaso|||0000-0002-0054-9322, Rasmussen, Kim J.R., Real Saladrigas, Esther|||0000-0003-1723-3380
Tipo de recurso: artículo
Fecha de publicación:2020
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/331159
Acceso en línea:https://hdl.handle.net/2117/331159
https://dx.doi.org/10.1016/j.jcsr.2020.106378
Access Level:acceso abierto
Palabra clave:Stainless steel
Stainless steel structures
Statistical data
Reliability calibration
Geometric properties
Material properties
Imperfections
Residual stresses
Acer inoxidable -- Estructures
Àrees temàtiques de la UPC::Enginyeria civil::Materials i estructures::Materials i estructures metàl·liques
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spelling Statistical analysis of the material, geometrical and imperfection characteristics of structural stainless steels and membersArrayago Luquin, Itsaso|||0000-0002-0054-9322Rasmussen, Kim J.R.Real Saladrigas, Esther|||0000-0003-1723-3380Stainless steelStainless steel structuresStatistical dataReliability calibrationGeometric propertiesMaterial propertiesImperfectionsResidual stressesAcer inoxidable -- EstructuresÀrees temàtiques de la UPC::Enginyeria civil::Materials i estructures::Materials i estructures metàl·liquesTraditional member-based two-step design approaches included in current structural codes for steel structures, as well as more recent system-based direct-design alternatives, require building rigorous structural reliability frameworks for the calibration of partial coefficients (resistance factors) to achieve specified target reliability requirements. Key design parameters affecting the strength of structures and their random variations are generally modelled by nominal or characteristic values in design standards, which are combined with partial coefficients that need to be calibrated from measurements on real samples. While the statistical characterization of material and geometric properties of structural steels has been consolidated over the last decades, information about the characterization of structural stainless steels is virtually non-existent due to the limited pool of available data. Thus, this paper presents the basic ingredient for developing reliability frameworks for stainless steel structures and components by statistically characterizing the main random parameters affecting their strength through a comprehensive database collected from the literature. Based on the collected data, appropriate probabilistic models are proposed for geometric properties, material properties, imperfections and residual stresses of different stainless steel alloys and cross-section or product types. The data is equally applicable to member-based reliability analyses as described in existing codes and system-based analyses targeted at the direct-design of stainless steel structures by advanced analysis.This research project has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under the Marie Sklodowska-Curie Grant Agreement No. 842395. The time dedicated by numerous authors of referenced papers to provide additional data and information is also much appreciated.Peer Reviewed20202020-12-0120202020-11-03journal articlehttp://purl.org/coar/resource_type/c_6501AMhttp://purl.org/coar/version/c_ab4af688f83e57aainfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/2117/331159https://dx.doi.org/10.1016/j.jcsr.2020.106378reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)InglésengEuropean Commission http://doi.org/10.13039/100010661 Horizon 2020 Framework Programme 842395 New Generation Design Methods for Stainless Steel Structuresopen accesshttp://purl.org/coar/access_right/c_abf2Attribution-NonCommercial-NoDerivatives 4.0 Internationalhttps://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/3311592026-05-27T15:37:01Z
dc.title.none.fl_str_mv Statistical analysis of the material, geometrical and imperfection characteristics of structural stainless steels and members
title Statistical analysis of the material, geometrical and imperfection characteristics of structural stainless steels and members
spellingShingle Statistical analysis of the material, geometrical and imperfection characteristics of structural stainless steels and members
Arrayago Luquin, Itsaso|||0000-0002-0054-9322
Stainless steel
Stainless steel structures
Statistical data
Reliability calibration
Geometric properties
Material properties
Imperfections
Residual stresses
Acer inoxidable -- Estructures
Àrees temàtiques de la UPC::Enginyeria civil::Materials i estructures::Materials i estructures metàl·liques
title_short Statistical analysis of the material, geometrical and imperfection characteristics of structural stainless steels and members
title_full Statistical analysis of the material, geometrical and imperfection characteristics of structural stainless steels and members
title_fullStr Statistical analysis of the material, geometrical and imperfection characteristics of structural stainless steels and members
title_full_unstemmed Statistical analysis of the material, geometrical and imperfection characteristics of structural stainless steels and members
title_sort Statistical analysis of the material, geometrical and imperfection characteristics of structural stainless steels and members
dc.creator.none.fl_str_mv Arrayago Luquin, Itsaso|||0000-0002-0054-9322
Rasmussen, Kim J.R.
Real Saladrigas, Esther|||0000-0003-1723-3380
author Arrayago Luquin, Itsaso|||0000-0002-0054-9322
author_facet Arrayago Luquin, Itsaso|||0000-0002-0054-9322
Rasmussen, Kim J.R.
Real Saladrigas, Esther|||0000-0003-1723-3380
author_role author
author2 Rasmussen, Kim J.R.
Real Saladrigas, Esther|||0000-0003-1723-3380
author2_role author
author
dc.subject.none.fl_str_mv Stainless steel
Stainless steel structures
Statistical data
Reliability calibration
Geometric properties
Material properties
Imperfections
Residual stresses
Acer inoxidable -- Estructures
Àrees temàtiques de la UPC::Enginyeria civil::Materials i estructures::Materials i estructures metàl·liques
topic Stainless steel
Stainless steel structures
Statistical data
Reliability calibration
Geometric properties
Material properties
Imperfections
Residual stresses
Acer inoxidable -- Estructures
Àrees temàtiques de la UPC::Enginyeria civil::Materials i estructures::Materials i estructures metàl·liques
description Traditional member-based two-step design approaches included in current structural codes for steel structures, as well as more recent system-based direct-design alternatives, require building rigorous structural reliability frameworks for the calibration of partial coefficients (resistance factors) to achieve specified target reliability requirements. Key design parameters affecting the strength of structures and their random variations are generally modelled by nominal or characteristic values in design standards, which are combined with partial coefficients that need to be calibrated from measurements on real samples. While the statistical characterization of material and geometric properties of structural steels has been consolidated over the last decades, information about the characterization of structural stainless steels is virtually non-existent due to the limited pool of available data. Thus, this paper presents the basic ingredient for developing reliability frameworks for stainless steel structures and components by statistically characterizing the main random parameters affecting their strength through a comprehensive database collected from the literature. Based on the collected data, appropriate probabilistic models are proposed for geometric properties, material properties, imperfections and residual stresses of different stainless steel alloys and cross-section or product types. The data is equally applicable to member-based reliability analyses as described in existing codes and system-based analyses targeted at the direct-design of stainless steel structures by advanced analysis.
publishDate 2020
dc.date.none.fl_str_mv 2020
2020-12-01
2020
2020-11-03
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
AM
http://purl.org/coar/version/c_ab4af688f83e57aa
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/2117/331159
https://dx.doi.org/10.1016/j.jcsr.2020.106378
url https://hdl.handle.net/2117/331159
https://dx.doi.org/10.1016/j.jcsr.2020.106378
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.relation.none.fl_str_mv European Commission http://doi.org/10.13039/100010661 Horizon 2020 Framework Programme 842395 New Generation Design Methods for Stainless Steel Structures
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivatives 4.0 International
https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivatives 4.0 International
https://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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