Optimal sensor placement for structural parameter identification of bridges with modeling uncertainties

The uncertainties in the numerical models used for the optimal sensor placement (OSP) studies of civil infrastructures, specifically bridges, considerably affect the results. These effects can be more prominent if the modeling uncertainties are of a kind that significantly alters the mode shapes of...

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Authors: Gönen, Semih|||0000-0002-9588-4552, Demirlioglu, Kultigin, Erduran, Emrah
Format: article
Publication Date:2023
Country:España
Institution:Universitat Politècnica de Catalunya (UPC)
Repository:UPCommons. Portal del coneixement obert de la UPC
Language:English
OAI Identifier:oai:upcommons.upc.edu:2117/394637
Online Access:https://hdl.handle.net/2117/394637
https://dx.doi.org/10.1016/j.engstruct.2023.116561
Access Level:Open access
Keyword:Structural health monitoring
Railroad bridges
Optimal sensor locations
Monte Carlo simulation
Modal identification
Effective independence
Hierarchical clustering
Model uncertainty
Railway bridges
Monitorització de salut estructural
Ponts de ferrocarril
Àrees temàtiques de la UPC::Enginyeria civil::Materials i estructures::Tipologies estructurals
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spelling Optimal sensor placement for structural parameter identification of bridges with modeling uncertaintiesGönen, Semih|||0000-0002-9588-4552Demirlioglu, KultiginErduran, EmrahStructural health monitoringRailroad bridgesOptimal sensor locationsMonte Carlo simulationModal identificationEffective independenceHierarchical clusteringModel uncertaintyRailway bridgesMonitorització de salut estructuralPonts de ferrocarrilÀrees temàtiques de la UPC::Enginyeria civil::Materials i estructures::Tipologies estructuralsThe uncertainties in the numerical models used for the optimal sensor placement (OSP) studies of civil infrastructures, specifically bridges, considerably affect the results. These effects can be more prominent if the modeling uncertainties are of a kind that significantly alters the mode shapes of the structure, such as the boundary conditions of the model. Yet, these effects on the results of OSP analysis remain unexplored, and there are no available methodologies to address all types of model uncertainties in OSP for civil infrastructures. This research presents a new framework to determine the optimal sensor locations to identify the modal properties of bridges under severe modeling uncertainties and its application on a railway bridge. The framework includes finite element model generation and a sensitivity study to select the most influential parameters that change the dynamic response of the bridge. The selected parameters are used in Monte Carlo simulations, and the results enable quantifying the relative amount of information presented at the candidate sensor locations. This information is combined with the spatial position of the candidate sensor locations, and a hierarchical clustering algorithm is used to obtain the optimal sensor locations and the number of sensors. In addition, the OSP analysis is carried out using the Effective Independence method to contribute to the state-of-the-art literature that investigates the uncertainties in OSP for civil infrastructures and uses this method.Peer ReviewedObjectius de Desenvolupament Sostenible::9 - Indústria, Innovació i InfraestructuraObjectius de Desenvolupament Sostenible::9 - Indústria, Innovació i Infraestructura::9.1 - Desenvolupar infraestructures fiables, sostenibles, resilients i de qualitat, incloent infraestructures regionals i transfrontereres, per tal de donar suport al desenvolupament econòmic i al benestar humà, amb especial atenció a l’accés assequible i equitatiu per a totes les personesElsevier20232023-10-0120232023-10-04journal articlehttp://purl.org/coar/resource_type/c_6501AMhttp://purl.org/coar/version/c_ab4af688f83e57aainfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/2117/394637https://dx.doi.org/10.1016/j.engstruct.2023.116561reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2Attribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/3946372026-05-27T15:37:01Z
dc.title.none.fl_str_mv Optimal sensor placement for structural parameter identification of bridges with modeling uncertainties
title Optimal sensor placement for structural parameter identification of bridges with modeling uncertainties
spellingShingle Optimal sensor placement for structural parameter identification of bridges with modeling uncertainties
Gönen, Semih|||0000-0002-9588-4552
Structural health monitoring
Railroad bridges
Optimal sensor locations
Monte Carlo simulation
Modal identification
Effective independence
Hierarchical clustering
Model uncertainty
Railway bridges
Monitorització de salut estructural
Ponts de ferrocarril
Àrees temàtiques de la UPC::Enginyeria civil::Materials i estructures::Tipologies estructurals
title_short Optimal sensor placement for structural parameter identification of bridges with modeling uncertainties
title_full Optimal sensor placement for structural parameter identification of bridges with modeling uncertainties
title_fullStr Optimal sensor placement for structural parameter identification of bridges with modeling uncertainties
title_full_unstemmed Optimal sensor placement for structural parameter identification of bridges with modeling uncertainties
title_sort Optimal sensor placement for structural parameter identification of bridges with modeling uncertainties
dc.creator.none.fl_str_mv Gönen, Semih|||0000-0002-9588-4552
Demirlioglu, Kultigin
Erduran, Emrah
author Gönen, Semih|||0000-0002-9588-4552
author_facet Gönen, Semih|||0000-0002-9588-4552
Demirlioglu, Kultigin
Erduran, Emrah
author_role author
author2 Demirlioglu, Kultigin
Erduran, Emrah
author2_role author
author
dc.subject.none.fl_str_mv Structural health monitoring
Railroad bridges
Optimal sensor locations
Monte Carlo simulation
Modal identification
Effective independence
Hierarchical clustering
Model uncertainty
Railway bridges
Monitorització de salut estructural
Ponts de ferrocarril
Àrees temàtiques de la UPC::Enginyeria civil::Materials i estructures::Tipologies estructurals
topic Structural health monitoring
Railroad bridges
Optimal sensor locations
Monte Carlo simulation
Modal identification
Effective independence
Hierarchical clustering
Model uncertainty
Railway bridges
Monitorització de salut estructural
Ponts de ferrocarril
Àrees temàtiques de la UPC::Enginyeria civil::Materials i estructures::Tipologies estructurals
description The uncertainties in the numerical models used for the optimal sensor placement (OSP) studies of civil infrastructures, specifically bridges, considerably affect the results. These effects can be more prominent if the modeling uncertainties are of a kind that significantly alters the mode shapes of the structure, such as the boundary conditions of the model. Yet, these effects on the results of OSP analysis remain unexplored, and there are no available methodologies to address all types of model uncertainties in OSP for civil infrastructures. This research presents a new framework to determine the optimal sensor locations to identify the modal properties of bridges under severe modeling uncertainties and its application on a railway bridge. The framework includes finite element model generation and a sensitivity study to select the most influential parameters that change the dynamic response of the bridge. The selected parameters are used in Monte Carlo simulations, and the results enable quantifying the relative amount of information presented at the candidate sensor locations. This information is combined with the spatial position of the candidate sensor locations, and a hierarchical clustering algorithm is used to obtain the optimal sensor locations and the number of sensors. In addition, the OSP analysis is carried out using the Effective Independence method to contribute to the state-of-the-art literature that investigates the uncertainties in OSP for civil infrastructures and uses this method.
publishDate 2023
dc.date.none.fl_str_mv 2023
2023-10-01
2023
2023-10-04
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/2117/394637
https://dx.doi.org/10.1016/j.engstruct.2023.116561
url https://hdl.handle.net/2117/394637
https://dx.doi.org/10.1016/j.engstruct.2023.116561
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivatives 4.0 International
http://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
http://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
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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score 15.301603

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