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Railway catenary optimisation with span variability by an iterative optimisation algorithm for large numbers of parameters

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Railway catenary optimisation with span variability by an iterative optimisation algorithm for large numbers of parameters

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dc.contributor.author Gil-Romero, Jaime es_ES
dc.contributor.author Song, Y. es_ES
dc.contributor.author Gregori Verdú, Santiago es_ES
dc.contributor.author Tur Valiente, Manuel es_ES
dc.contributor.author Rønnquist, A. es_ES
dc.contributor.author Fuenmayor Fernández, Francisco-Javier es_ES
dc.date.accessioned 2024-07-01T18:36:26Z
dc.date.available 2024-07-01T18:36:26Z
dc.date.issued 2024-01-15 es_ES
dc.identifier.issn 0141-0296 es_ES
dc.identifier.uri http://hdl.handle.net/10251/205619
dc.description.abstract [EN] Optimising the catenary topology to improve the pantograph-catenary interaction is computationally expensive. Especially in the case of large numbers of parameters. Unfortunately, varying span lengths and dropper distribution in realistic systems requires the inclusion of a vast number of parameters, making the optimisation problem extremely complicated. Published optimisation works assume that the catenary is a perfectly periodical structure to reduce the number of parameters involved in the optimisation and keep the computational cost below a feasible limit. This paper attempts to deal with the scientific challenge of optimising a realistic system by proposing an iterative optimisation strategy consisting of optimising groups of parameters separately and repeating the optimisations iteratively to consider the dependence between parameters that otherwise would need to be optimised together. This solution performs topological catenary optimisation in catenary zones with span variability or transition zones in which optimisations that assume periodicity are no longer valid. es_ES
dc.description.sponsorship The authors would like to acknowledge the financial support received from the State Research Agency of the Spanish Science and Innovation Ministry, Spain (PID2020-113458RB-I00) and from the Valencian Regional Government, Spain (PROMETEO/2021/046). es_ES
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation.ispartof Engineering Structures es_ES
dc.rights Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) es_ES
dc.subject Catenary es_ES
dc.subject Pantograph es_ES
dc.subject Optimisation es_ES
dc.subject Experimental validation es_ES
dc.subject.classification INGENIERIA MECANICA es_ES
dc.title Railway catenary optimisation with span variability by an iterative optimisation algorithm for large numbers of parameters es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.engstruct.2023.117090 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-113458RB-I00/ES/ENSAYOS HIL DE PANTOGRAFOS CON MODELOS AVANZADOS DE CATENARIAS VIRTUALES / es_ES
dc.relation.projectID info:eu-repo/grantAgreement/GENERALITAT VALENCIANA//PROMETEO%2F2021%2F046//MODELADO NUMÉRICO AVANZADO EN INGENIERÍA MECÁNICA/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Escuela Técnica Superior de Ingenieros Industriales - Escola Tècnica Superior d'Enginyers Industrials es_ES
dc.description.bibliographicCitation Gil-Romero, J.; Song, Y.; Gregori Verdú, S.; Tur Valiente, M.; Rønnquist, A.; Fuenmayor Fernández, F. (2024). Railway catenary optimisation with span variability by an iterative optimisation algorithm for large numbers of parameters. Engineering Structures. 299. https://doi.org/10.1016/j.engstruct.2023.117090 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1016/j.engstruct.2023.117090 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 299 es_ES
dc.relation.pasarela S\502416 es_ES
dc.contributor.funder GENERALITAT VALENCIANA es_ES
dc.contributor.funder AGENCIA ESTATAL DE INVESTIGACION es_ES
dc.contributor.funder Universitat Politècnica de València es_ES


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