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Rolling noise reduction through GA-based wheel shape optimization techniques

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Rolling noise reduction through GA-based wheel shape optimization techniques

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dc.contributor.author Garcia-Andrés, Xavier es_ES
dc.contributor.author Gutiérrez-Gil, Jorge es_ES
dc.contributor.author Andrés, Víctor Tomás es_ES
dc.contributor.author Martínez-Casas, José es_ES
dc.contributor.author Denia, Francisco David es_ES
dc.date.accessioned 2022-09-27T12:53:21Z
dc.date.available 2022-09-27T12:53:21Z
dc.date.issued 2022-05-11
dc.identifier.isbn 9788490489697
dc.identifier.uri http://hdl.handle.net/10251/186614
dc.description.abstract [EN] Railway rolling noise is nowadays a major source of acoustic pollution in urban areas, with nearly up to 12 million people daily affected in Europe by this phenomenon [1]. Hence, the search for ways of decreasing such noise radiation has become a highly active and significant research field. Following this approach, a Genetic Algorithms-based shape optimization of the railway wheel [2] is developed with the aim of minimizing rolling noise. Different approaches are considered to address the problem, such as directly minimizing radiated Sound poWer Level (SWL) or using the maximization of the natural frequencies if computational efficiency is especially critical. A parametric Finite Element model is implemented for the wheel based on the most relevant geometric parameters in rolling noise radiation. For the acoustic calculation, the sound radiation models used in the TWINS software [3] are adopted, which also accounts for the whole dynamics of the wheel/rail system. Furthermore, for every candidate wheel proposed, a structural analysis is computed in order to check design feasibility in accordance with the corresponding standard [4]. In all cases, new geometries for the wheel cross section are achieved that reduce the radiated rolling noise. es_ES
dc.description.sponsorship This study has been supported by the Agencia Estatal de Investigación and the European Regional Development Fund (project TRA2017-84701-R). es_ES
dc.format.extent 9 es_ES
dc.language Inglés es_ES
dc.publisher Editorial Universitat Politècnica de València es_ES
dc.relation.ispartof Proceedings of the YIC 2021 - VI ECCOMAS Young Investigators Conference
dc.rights Reconocimiento - No comercial - Compartir igual (by-nc-sa) es_ES
dc.subject Railway wheel es_ES
dc.subject Geometric optimization es_ES
dc.subject Genetic Algorithms es_ES
dc.subject Rolling noise es_ES
dc.title Rolling noise reduction through GA-based wheel shape optimization techniques es_ES
dc.type Capítulo de libro es_ES
dc.type Comunicación en congreso es_ES
dc.identifier.doi 10.4995/YIC2021.2021.12577
dc.relation.projectID info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TRA2017-84701-R/ES/DESARROLLO DE UN MODELO INTEGRAL DE INTERACCION VEHICULO%2FVIA EN CURVA PARA LA REDUCCION DEL IMPACTO ACUSTICO DEL TRANSPORTE FERROVIARIO/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería Mecánica y de Materiales - Departament d'Enginyeria Mecànica i de Materials es_ES
dc.description.bibliographicCitation Garcia-Andrés, X.; Gutiérrez-Gil, J.; Andrés, VT.; Martínez-Casas, J.; Denia, FD. (2022). Rolling noise reduction through GA-based wheel shape optimization techniques. En Proceedings of the YIC 2021 - VI ECCOMAS Young Investigators Conference. Editorial Universitat Politècnica de València. 304-312. https://doi.org/10.4995/YIC2021.2021.12577 es_ES
dc.description.accrualMethod OCS es_ES
dc.relation.conferencename VI ECCOMAS Young Investigators Conference es_ES
dc.relation.conferencedate Julio 07-09, 2021 es_ES
dc.relation.conferenceplace Valencia, España es_ES
dc.relation.publisherversion http://ocs.editorial.upv.es/index.php/YIC/YIC2021/paper/view/12577 es_ES
dc.description.upvformatpinicio 304 es_ES
dc.description.upvformatpfin 312 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.relation.pasarela OCS\12577 es_ES
dc.contributor.funder Agencia Estatal de Investigación es_ES
dc.contributor.funder European Regional Development Fund es_ES


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