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Multi-objective design of post-tensioned concrete road bridges using artificial neural networks

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Multi-objective design of post-tensioned concrete road bridges using artificial neural networks

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dc.contributor.author García-Segura, Tatiana es_ES
dc.contributor.author Yepes, V. es_ES
dc.contributor.author Frangopol, D.M. es_ES
dc.date.accessioned 2018-05-19T04:22:55Z
dc.date.available 2018-05-19T04:22:55Z
dc.date.issued 2017 es_ES
dc.identifier.issn 1615-147X es_ES
dc.identifier.uri http://hdl.handle.net/10251/102256
dc.description.abstract [EN] In order to minimize the total expected cost, bridges have to be designed for safety and durability. This paper considers the cost, the safety, and the corrosion initiation time to design post-tensioned concrete box-girder road bridges. The deck is modeled by finite elements based on problem variables such as the cross-section geometry, the concrete grade, and the reinforcing and post-tensioning steel. An integrated multi-objective harmony search with artificial neural networks (ANNs) is proposed to reduce the high computing time required for the finite-element analysis and the increment in conflicting objectives. ANNs are trained through the results of previous bridge performance evaluations. Then, ANNs are used to evaluate the constraints and provide a direction towards the Pareto front. Finally, exact methods actualize and improve the Pareto set. The results show that the harmony search parameters should be progressively changed in a diversification-intensification strategy. This methodology provides trade-off solutions that are the cheapest ones for the safety and durability levels considered. Therefore, it is possible to choose an alternative that can be easily adjusted to each need. es_ES
dc.description.sponsorship The authors acknowledge the financial support of the Spanish Ministry of Economy and Competitiveness, along with FEDER funding (BRIDLIFE Project: BIA2014-56574-R) and the Research and Development Support Program of Universitat Politecnica de Valencia (PAID-02-15). en_EN
dc.language Inglés es_ES
dc.publisher Springer-Verlag es_ES
dc.relation.ispartof Structural and Multidisciplinary Optimization es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Multi-objective harmony search es_ES
dc.subject Artificial neural networks es_ES
dc.subject Post-tensioned concrete bridges es_ES
dc.subject Durability es_ES
dc.subject Safety es_ES
dc.subject.classification INGENIERIA DE LA CONSTRUCCION es_ES
dc.subject.classification PROYECTOS DE INGENIERIA es_ES
dc.title Multi-objective design of post-tensioned concrete road bridges using artificial neural networks es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1007/s00158-017-1653-0 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//BIA2014-56574-R/ES/TOMA DE DECISIONES EN LA GESTION DEL CICLO DE VIDA DE PUENTES PRETENSADOS DE ALTA EFICIENCIA SOCIAL Y MEDIOAMBIENTAL BAJO PRESUPUESTOS RESTRICTIVOS/ es_ES
dc.rights.accessRights Abierto es_ES
dc.date.embargoEndDate 2018-07-01 es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería de la Construcción y de Proyectos de Ingeniería Civil - Departament d'Enginyeria de la Construcció i de Projectes d'Enginyeria Civil es_ES
dc.description.bibliographicCitation García-Segura, T.; Yepes, V.; Frangopol, D. (2017). Multi-objective design of post-tensioned concrete road bridges using artificial neural networks. Structural and Multidisciplinary Optimization. 56(1):139-150. doi:10.1007/s00158-017-1653-0 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1007/s00158-017-1653-0 es_ES
dc.description.upvformatpinicio 139 es_ES
dc.description.upvformatpfin 150 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 56 es_ES
dc.description.issue 1 es_ES
dc.relation.pasarela S\338059 es_ES
dc.contributor.funder Ministerio de Economía, Industria y Competitividad es_ES
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