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dc.contributor.author | Martínez-Rodríguez, David![]() |
es_ES |
dc.contributor.author | Novella Rosa, Ricardo![]() |
es_ES |
dc.contributor.author | Bracho Leon, Gabriela![]() |
es_ES |
dc.contributor.author | Gómez-Soriano, Josep![]() |
es_ES |
dc.contributor.author | Fernandes, Cássio![]() |
es_ES |
dc.contributor.author | Lucchini, Tommaso![]() |
es_ES |
dc.contributor.author | Della Torre, Augusto![]() |
es_ES |
dc.contributor.author | Villanueva Micó, Rafael Jacinto![]() |
es_ES |
dc.contributor.author | Hidalgo, J. Ignacio![]() |
es_ES |
dc.date.accessioned | 2024-06-17T18:08:30Z | |
dc.date.available | 2024-06-17T18:08:30Z | |
dc.date.issued | 2023-08 | es_ES |
dc.identifier.issn | 1568-4946 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/205220 | |
dc.description.abstract | [EN] The particle swarm optimization algorithm is primarily inspired by the natural behaviour of swarms and achieves important results in different applications. However, it is not exempt from stagnation in local optima and has a tendency to prematurely converge to them. Novelty Search is a concept that appeared recently in different fields of computational intelligence. It aims at exploring non-visited areas of the search space through solutions that bring novelty to already discovered solutions. The novelty of this work can be divided into two steps: on one side, this article proposes a variant of the particle swarm optimization algorithm which uses Novelty Search concepts to improve the algorithm¿s performance. Our proposal is first checked and compared using the CEC 2005 benchmark suite and then, we apply it to solve a real-world optimization problem: the design of a combustion system targeting the reduction of pollutant emissions and fuel consumption. The combustion chamber design phase usually is a complex and time-consuming process even with advanced supercomputers, since it depends on several input variables which are highly non-linear and with crossed interaction. Then, the second contribution of this work is to develop a methodology that couples a computational fluid dynamics (CFD) simulation tool with the new optimization algorithm for minimizing the specific fuel consumption of a compression-ignited engine, while constraining the NOx and soot emissions. A 3D-CFD model of the combustion system was built to predict and analyse the performance of the combustion system and hence, select the parameters with a higher impact on the system. The method reduces the computational time and includes tools for the automatic preparation of the input parameters and geometry of the system. The input parameters correspond to geometrical variables that control the bowl shape, the number of holes in the injector, the injection pressure, the swirl number and the exhaust gas recirculation rate. Results show how the simulation tool and the new PSO with Novelty Search algorithm allow us to obtain a new combustion system that minimizes the fuel consumption by 3%, simultaneously reducing NOx and soot emissions. | es_ES |
dc.description.sponsorship | This work has been partially supported by This work has been supported by the grant PID2020-1152 70GB I00 funded by MCIN/AEI/10.13039/501100011033; European Union FEDER funds; Spanish Ministerio de Economía y Competitividad through Grants PID2021-125549OB-I00 and PDC2022-133429-I00. The author C. S. Fernandes thanks the Universitat Politecnica de Valencia for his predoctoral contract (FPI-2019-S2- 20-555), which is included within the framework of Programa de Apoyo para la Investigacion y Desarrollo (PAID). | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | Elsevier | es_ES |
dc.relation.ispartof | Applied Soft Computing | es_ES |
dc.rights | Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) | es_ES |
dc.subject.classification | MATEMATICA APLICADA | es_ES |
dc.subject.classification | INGENIERIA AEROESPACIAL | es_ES |
dc.subject.classification | MAQUINAS Y MOTORES TERMICOS | es_ES |
dc.title | A particle swarm optimization algorithm with novelty search for combustion systems with ultra-low emissions and minimum fuel consumption | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.1016/j.asoc.2023.110401 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-115270GB-I00/ES/ECUACIONES DIFERENCIALES ALEATORIAS. CUANTIFICACION DE LA INCERTIDUMBRE Y APLICACIONES/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PDC2022-133429-I00/ES/SISTEMA WEARABLE DE INTELIGENCIA ARTIFICIAL PARA LA TOMA DE DECISIONES DE PERSONAS CON DIABETES/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2021-125549OB-I00/ES/INTELIGENCIA ARTIFICIAL SOBRE ACELERADORES HARDWARE ESPECIALIZADOS Y SISTEMAS EMPOTRADOS PARA EL TRATAMIENTO PERSONALIZADO DE PRECISION DE LA DIABETES/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/UPV//FPI-2019-S2-20-555//Contrato predoctoral/ | 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.contributor.affiliation | Universitat Politècnica de València. Facultad de Administración y Dirección de Empresas - Facultat d'Administració i Direcció d'Empreses | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Escuela Técnica Superior de Ingeniería del Diseño - Escola Tècnica Superior d'Enginyeria del Disseny | es_ES |
dc.description.bibliographicCitation | Martínez-Rodríguez, D.; Novella Rosa, R.; Bracho Leon, G.; Gómez-Soriano, J.; Fernandes, C.; Lucchini, T.; Della Torre, A.... (2023). A particle swarm optimization algorithm with novelty search for combustion systems with ultra-low emissions and minimum fuel consumption. Applied Soft Computing. 143. https://doi.org/10.1016/j.asoc.2023.110401 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://doi.org/10.1016/j.asoc.2023.110401 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 143 | es_ES |
dc.relation.pasarela | S\493793 | es_ES |
dc.contributor.funder | AGENCIA ESTATAL DE INVESTIGACION | es_ES |
dc.contributor.funder | Agencia Estatal de Investigación | es_ES |
dc.contributor.funder | European Regional Development Fund | es_ES |
dc.contributor.funder | Universitat Politècnica de València | es_ES |
dc.subject.ods | 07.- Asegurar el acceso a energías asequibles, fiables, sostenibles y modernas para todos | es_ES |
dc.subject.ods | 13.- Tomar medidas urgentes para combatir el cambio climático y sus efectos | es_ES |