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dc.creatorHernández Montes, Enriquees
dc.creatorJalón Ramírez, María Lourdeses
dc.creatorRodríguez Romero, Rubénes
dc.creatorChiachío Ruano, Juanes
dc.creatorCompán Cardiel, Víctor Jesúses
dc.creatorGil Martín, Luisa Maríaes
dc.date.accessioned2023-05-17T08:08:19Z
dc.date.available2023-05-17T08:08:19Z
dc.date.issued2023-06-01
dc.identifier.citationHernández Montes, E., Jalón Ramírez, M.L., Rodríguez Romero, R., Chiachío Ruano, J., Compán Cardiel, V.J. y Gil Martín, L.M. (2023). Bayesian structural parameter identification from ambient vibration in cultural heritage buildings: the case of the San Jerónimo monastery in Granada, Spain. Engineering Structures, 284 (115924). https://doi.org/10.1016/j.engstruct.2023.115924.
dc.identifier.issn0141-0296es
dc.identifier.issn1873-7323es
dc.identifier.urihttps://hdl.handle.net/11441/146167
dc.description.abstractThe deterioration of Cultural Heritage assets caused by the natural hazards is a pressing issue in many countries. Therefore, reliable models based on the large-scale structural response of the assets is key to assess their resilience. However, reliable models such as large and detailed Finite Element (FE) models, require a large number of data and input parameters. This paper proposes a Bayesian learning approach to identify the main parameters of a FE model with quantified uncertainty based on ambient vibration data. As a novelty when compared with other Bayesian structural parameter identification methods from ambient vibration data, here the likelihood function is formulated in a principled way considering information from both frequencies and modes using a probabilistic version of the Modal Assurance Criterion for the modes. This method is embedded into a parameterised computational model to automate the simulation process, and a real case study for a sixteenth century heritage building in Granada (Spain) is presented. The results show the suitability and effectiveness of the proposed Bayesian approach in identifying the most plausible values of the uncertain model parameters in a rigorous probabilistic way, but also in obtaining the modelled frequencies and the modal assurance criterion values with quantified uncertainty.es
dc.formatapplication/pdfes
dc.format.extent11 p.es
dc.language.isoenges
dc.publisherElsevieres
dc.relation.ispartofEngineering Structures, 284 (115924).
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectAmbient vibration testses
dc.subjectBayesian learninges
dc.subjectCultural heritage buildingses
dc.subjectFinite element modelses
dc.subjectOperational modal analysises
dc.titleBayesian structural parameter identification from ambient vibration in cultural heritage buildings: the case of the San Jerónimo monastery in Granada, Spaines
dc.typeinfo:eu-repo/semantics/articlees
dcterms.identifierhttps://ror.org/03yxnpp24
dc.type.versioninfo:eu-repo/semantics/publishedVersiones
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.contributor.affiliationUniversidad de Sevilla. Departamento de Estructuras de Edificación e Ingeniería del Terrenoes
dc.relation.projectID821054es
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S0141029623003383?via%3Dihubes
dc.identifier.doi10.1016/j.engstruct.2023.115924es
dc.contributor.groupUniversidad de Sevilla. TEP114: Tecnología Arquitectónicaes
dc.journaltitleEngineering Structureses
dc.publication.volumen284es
dc.publication.issue115924es

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