Robust estimation of axial loads sustained by tie-rods in historical structures using Artificial Neural Networks

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dc.contributor.affiliationDepartamento de Ingeniería de la Construcción y de Proyectos de Ingeniería Civil
dc.contributor.affiliationEscuela Técnica Superior de Ingeniería de Caminos, Canales y Puertos
dc.contributor.affiliationInstituto Universitario de Investigación de Ciencia y Tecnología del Hormigón
dc.contributor.authorMakoond, Nirvan Chandra
dc.contributor.authorPelà, Lucaes_ES
dc.contributor.authorMolins, Climentes_ES
dc.contributor.funderGeneralitat de Catalunyaes_ES
dc.contributor.funderAgencia Estatal de Investigaciónes_ES
dc.contributor.funderEuropean Regional Development Fundes_ES
dc.contributor.funderAgencia de Gestión de Ayudas Universitarias y de Investigaciónes_ES
dc.date.accessioned2023-10-19T18:02:02Z
dc.date.available2023-10-19T18:02:02Z
dc.date.issued2023-07es_ES
dc.description.abstract[EN] Widely used simplified analytical methods for estimating the tensile force in tie-rods are clearly not applicable when they contain significant discontinuities or irregularities. A common example for which this fact becomes relevant in practice is the use of connectors to unify historical ties consisting of several segments. To address this challenge, a robust hybrid methodology is proposed which can be applied to any historical tie by employing a data-driven approach to a dataset generated using the finite element method. The methodology is applied to a real case study involving two historical ties.en_EN
dc.description.accrualMethodSes_ES
dc.description.bibliographicCitationMakoond, NC.; Pelà, L.; Molins, C. (2023). Robust estimation of axial loads sustained by tie-rods in historical structures using Artificial Neural Networks. Structural Health Monitoring. 22(4):2496-2515. https://doi.org/10.1177/14759217221123326es_ES
dc.description.issue4es_ES
dc.description.sponsorshipThe author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Servei del Patrimoni Arquitectònic of the Generalitat de Catalunya through a project (managed by the City Council of Sant Cugat) aimed at monitoring the church of the Monastery of Sant Cugat (grant number C-10764); the Ministry of Science, Innovation and Universities of the Spanish Government and the ERDF (European Regional Development Fund) through the SEVERUS project (Multilevel evaluation of seismic vulnerability and risk mitigation of masonry buildings in resilient historical urban centres) (grant number RTI2018-099589-B-I00); and the AGAUR agency of the Generalitat de Catalunya in the form of the predoctoral grant of the first author.es_ES
dc.description.upvformatpfin2515es_ES
dc.description.upvformatpinicio2496es_ES
dc.description.volume22es_ES
dc.identifier.doi10.1177/14759217221123326es_ES
dc.identifier.issn1475-9217es_ES
dc.identifier.urihttps://riunet.upv.es/handle/10251/198421
dc.languageIngléses_ES
dc.publisherSAGE Publicationses_ES
dc.relation.ispartofStructural Health Monitoringes_ES
dc.relation.pasarelaS\486293es_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-099589-B-I00/ES/EVALUACION MULTINIVEL DE LA VULNERABILIDADD SISMICA Y MITIGACION DE RIESGO DE EDIFICIOS DE OBRA DE FABRICA EN CENTROS URBANOS HISTORICOS RESILIENTES/es_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/GC//C-10764//Servei del Patrimoni Arquitectònic/es_ES
dc.relation.publisherversionhttps://doi.org/10.1177/14759217221123326es_ES
dc.relation.references10.3390/app11083687es_ES
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dc.rightsReserva de todos los derechoses_ES
dc.rights.accessRightsAbiertoes_ES
dc.subjectAxial force estimationes_ES
dc.subjectVibration testinges_ES
dc.subjectDynamic identificationes_ES
dc.subjectModal analysises_ES
dc.subjectNatural frequencyes_ES
dc.subjectMode shapeses_ES
dc.subject.ods09.- Desarrollar infraestructuras resilientes, promover la industrialización inclusiva y sostenible, y fomentar la innovaciónes_ES
dc.subject.ods11.- Conseguir que las ciudades y los asentamientos humanos sean inclusivos, seguros, resilientes y sostenibleses_ES
dc.titleRobust estimation of axial loads sustained by tie-rods in historical structures using Artificial Neural Networkses_ES
dc.typeArtículoes_ES
dc.type.versioninfo:eu-repo/semantics/publishedVersiones_ES
dspace.entity.typePublication
person.identifier691508
person.identifier.orcid0000-0002-5203-6318
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