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Calibration of the numerical model of a freight railway vehicle based on experimental modal parameters

2022Journal article Open access
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dc.contributor.authorRibeiro, Diogo
dc.contributor.authorBragança, C.
dc.contributor.authorCosta, C.
dc.contributor.authorJorge, P.
dc.contributor.authorSilva, R.
dc.contributor.authorArêde, A.
dc.contributor.authorCalçada, R.
dc.date.accessioned2022-12-21T11:11:43Z
dc.date.available2022-12-21T11:11:43Z
dc.date.issued2022
dc.description.abstractThe simulation of the dynamic behavior of the train-track system is strongly dependent on the accuracy of the numerical models of the train and track subsystems. The use of calibrated numerical models of the railway vehicles, based on experimental data, enhances their ability to correctly reproduce the dynamic responses of the train under operational conditions. In this scope, studies involving the experimental calibration of freight wagon models are still scarce. This article aims to fill this gap by presenting an efficient methodology for the calibration of a numerical model of a freight railway wagon based on experimental modal parameters. A dynamic test was performed during the unloading operation of the train, adopting a dedicated approach which does not interfere with its tight operational schedule. From data collected during the dynamic test, five natural frequencies and mode shapes associated with rigid-body and flexural movements of the wagon platform were identified through the Enhanced Frequency-Domain Decomposition (EFDD) method. A detailed 3D finite-element (FE) model of the loaded freight wagon was developed, requiring precise knowledge of the vehicle design details which, in most situations, are difficult to obtain due to confidentiality reasons of the manufacturers. The model calibration was performed through an iterative method based on a genetic algorithm and allowed to obtain optimal values for seven numerical parameters related to the suspension’s stiffnesses and mass distribution. The stability of the parameters considering different initial populations demonstrated the robustness of the optimization algorithm. The average error of the natural frequencies decreased from 8.5% before calibration to 3.2% after calibration, and the average MAC values improved from 0.911 to 0.950, revealing a significant improvement of the initial numerical model.pt_PT
dc.description.sponsorshipThe authors would like to acknowledge the support of the Base Funding UIDB/04708/2020 and Programmatic Funding UIDP/04708/2020 of the CONSTRUCT (Instituto de I&D em Estruturas e Construções) funded by national funds through the FCT/MCTES (PIDDAC). The authors also express their gratitude to Dr. Nuno Pinto and Mr. Valdemar Luís, both technicians of LESE laboratory, for their indispensable assistance during the preparation and execution of the experimental testpt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1016/j.istruc.2022.01.085pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.22/21221
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherElsevierpt_PT
dc.relationInstitute of R&D in Structures and Construction
dc.relationInstitute of R&D in Structures and Construction
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S2352012422000856pt_PT
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/pt_PT
dc.subjectFreight wagonpt_PT
dc.subjectFE modelpt_PT
dc.subjectDynamic testspt_PT
dc.subjectModel updatingpt_PT
dc.subjectGenetic algorithmpt_PT
dc.titleCalibration of the numerical model of a freight railway vehicle based on experimental modal parameterspt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleInstitute of R&D in Structures and Construction
oaire.awardTitleInstitute of R&D in Structures and Construction
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04708%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F04708%2F2020/PT
oaire.citation.endPage122pt_PT
oaire.citation.startPage108pt_PT
oaire.citation.titleStructurespt_PT
oaire.citation.volume38pt_PT
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
person.familyNameRibeiro
person.givenNameDiogo
person.identifier277594
person.identifier.ciencia-id2318-666E-AA75
person.identifier.orcid0000-0001-8624-9904
person.identifier.scopus-author-id24476782300
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
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relation.isAuthorOfPublication.latestForDiscoveryb9d8c427-25f3-4ab7-b368-f9101b55b9a9
relation.isProjectOfPublicationb301f286-1b56-4c75-b9cf-e85edc77b88a
relation.isProjectOfPublicationef3b9273-d8d8-4941-8b8c-e856809e3ebb
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