A particle swarm optimization algorithm with novelty search for combustion systems with ultra-low emissions and minimum fuel consumption

[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...

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Autores: Martínez-Rodríguez, David, Fernandes, Cássio, Lucchini, Tommaso, Della Torre, Augusto, Hidalgo, J. Ignacio, Novella Rosa, Ricardo|||0000-0002-5123-6924, Bracho Leon, Gabriela|||0000-0002-9198-7044, Gómez-Soriano, Josep|||0000-0002-2742-9224, Villanueva Micó, Rafael Jacinto|||0000-0002-0131-0532
Tipo de recurso: artículo
Fecha de publicación:2023
País:España
Institución:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglés
OAI Identifier:oai:riunet.upv.es:10251/205220
Acceso en línea:https://riunet.upv.es/handle/10251/205220
Access Level:acceso abierto
Palabra clave:MATEMATICA APLICADA
INGENIERIA AEROESPACIAL
MAQUINAS Y MOTORES TERMICOS
07.- Asegurar el acceso a energías asequibles, fiables, sostenibles y modernas para todos
13.- Tomar medidas urgentes para combatir el cambio climático y sus efectos
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oai_identifier_str oai:riunet.upv.es:10251/205220
network_acronym_str ES
network_name_str España
repository_id_str
dc.title.none.fl_str_mv A particle swarm optimization algorithm with novelty search for combustion systems with ultra-low emissions and minimum fuel consumption
title A particle swarm optimization algorithm with novelty search for combustion systems with ultra-low emissions and minimum fuel consumption
spellingShingle A particle swarm optimization algorithm with novelty search for combustion systems with ultra-low emissions and minimum fuel consumption
Martínez-Rodríguez, David
MATEMATICA APLICADA
INGENIERIA AEROESPACIAL
MAQUINAS Y MOTORES TERMICOS
07.- Asegurar el acceso a energías asequibles, fiables, sostenibles y modernas para todos
13.- Tomar medidas urgentes para combatir el cambio climático y sus efectos
title_short A particle swarm optimization algorithm with novelty search for combustion systems with ultra-low emissions and minimum fuel consumption
title_full A particle swarm optimization algorithm with novelty search for combustion systems with ultra-low emissions and minimum fuel consumption
title_fullStr A particle swarm optimization algorithm with novelty search for combustion systems with ultra-low emissions and minimum fuel consumption
title_full_unstemmed A particle swarm optimization algorithm with novelty search for combustion systems with ultra-low emissions and minimum fuel consumption
title_sort A particle swarm optimization algorithm with novelty search for combustion systems with ultra-low emissions and minimum fuel consumption
dc.creator.none.fl_str_mv Martínez-Rodríguez, David
Fernandes, Cássio
Lucchini, Tommaso
Della Torre, Augusto
Hidalgo, J. Ignacio
Novella Rosa, Ricardo|||0000-0002-5123-6924
Bracho Leon, Gabriela|||0000-0002-9198-7044
Gómez-Soriano, Josep|||0000-0002-2742-9224
Villanueva Micó, Rafael Jacinto|||0000-0002-0131-0532
author Martínez-Rodríguez, David
author_facet Martínez-Rodríguez, David
Fernandes, Cássio
Lucchini, Tommaso
Della Torre, Augusto
Hidalgo, J. Ignacio
Novella Rosa, Ricardo|||0000-0002-5123-6924
Bracho Leon, Gabriela|||0000-0002-9198-7044
Gómez-Soriano, Josep|||0000-0002-2742-9224
Villanueva Micó, Rafael Jacinto|||0000-0002-0131-0532
author_role author
author2 Fernandes, Cássio
Lucchini, Tommaso
Della Torre, Augusto
Hidalgo, J. Ignacio
Novella Rosa, Ricardo|||0000-0002-5123-6924
Bracho Leon, Gabriela|||0000-0002-9198-7044
Gómez-Soriano, Josep|||0000-0002-2742-9224
Villanueva Micó, Rafael Jacinto|||0000-0002-0131-0532
author2_role author
author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv Facultad de Administración y Dirección de Empresas
Departamento de Matemática Aplicada
Departamento de Máquinas y Motores Térmicos
Escuela Técnica Superior de Ingeniería Aeroespacial y Diseño Industrial
Instituto Universitario de Investigación CMT - Clean Mobility & Thermofluids
Instituto Universitario de Matemática Multidisciplinar
Escuela Técnica Superior de Ingeniería Industrial
AGENCIA ESTATAL DE INVESTIGACION
Agencia Estatal de Investigación
European Regional Development Fund
Universitat Politècnica de València
Repositorio Institucional de la Universitat Politècnica de València Riunet
dc.subject.none.fl_str_mv MATEMATICA APLICADA
INGENIERIA AEROESPACIAL
MAQUINAS Y MOTORES TERMICOS
07.- Asegurar el acceso a energías asequibles, fiables, sostenibles y modernas para todos
13.- Tomar medidas urgentes para combatir el cambio climático y sus efectos
topic MATEMATICA APLICADA
INGENIERIA AEROESPACIAL
MAQUINAS Y MOTORES TERMICOS
07.- Asegurar el acceso a energías asequibles, fiables, sostenibles y modernas para todos
13.- Tomar medidas urgentes para combatir el cambio climático y sus efectos
description [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.
publishDate 2023
dc.date.none.fl_str_mv 2023
2023-08-01
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://riunet.upv.es/handle/10251/205220
url https://riunet.upv.es/handle/10251/205220
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.relation.none.fl_str_mv Agencia Estatal de Investigación http://dx.doi.org/10.13039/501100011033 Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020 PID2020-115270GB-I00 ECUACIONES DIFERENCIALES ALEATORIAS. CUANTIFICACION DE LA INCERTIDUMBRE Y APLICACIONES
Agencia Estatal de Investigación http://dx.doi.org/10.13039/501100011033 Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023 PDC2022-133429-I00 SISTEMA WEARABLE DE INTELIGENCIA ARTIFICIAL PARA LA TOMA DE DECISIONES DE PERSONAS CON DIABETES
Agencia Estatal de Investigación http://dx.doi.org/10.13039/501100011033 Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023 PID2021-125549OB-I00 INTELIGENCIA ARTIFICIAL SOBRE ACELERADORES HARDWARE ESPECIALIZADOS Y SISTEMAS EMPOTRADOS PARA EL TRATAMIENTO PERSONALIZADO DE PRECISION DE LA DIABETES
Universitat Politècnica de València https://doi.org/10.13039/501100004233 FPI-2019-S2-20-555 Contrato predoctoral
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reconocimiento - No comercial - Sin obra derivada (by-nc-nd)
http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reconocimiento - No comercial - Sin obra derivada (by-nc-nd)
http://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
instname:Universitat Politècnica de València (UPV)
instname_str Universitat Politècnica de València (UPV)
reponame_str RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
collection RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
repository.name.fl_str_mv
repository.mail.fl_str_mv
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spelling A particle swarm optimization algorithm with novelty search for combustion systems with ultra-low emissions and minimum fuel consumptionMartínez-Rodríguez, DavidFernandes, CássioLucchini, TommasoDella Torre, AugustoHidalgo, J. IgnacioNovella Rosa, Ricardo|||0000-0002-5123-6924Bracho Leon, Gabriela|||0000-0002-9198-7044Gómez-Soriano, Josep|||0000-0002-2742-9224Villanueva Micó, Rafael Jacinto|||0000-0002-0131-0532MATEMATICA APLICADAINGENIERIA AEROESPACIALMAQUINAS Y MOTORES TERMICOS07.- Asegurar el acceso a energías asequibles, fiables, sostenibles y modernas para todos13.- Tomar medidas urgentes para combatir el cambio climático y sus efectos[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.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).ElsevierFacultad de Administración y Dirección de EmpresasDepartamento de Matemática AplicadaDepartamento de Máquinas y Motores TérmicosEscuela Técnica Superior de Ingeniería Aeroespacial y Diseño IndustrialInstituto Universitario de Investigación CMT - Clean Mobility & ThermofluidsInstituto Universitario de Matemática MultidisciplinarEscuela Técnica Superior de Ingeniería IndustrialAGENCIA ESTATAL DE INVESTIGACIONAgencia Estatal de InvestigaciónEuropean Regional Development FundUniversitat Politècnica de ValènciaRepositorio Institucional de la Universitat Politècnica de València Riunet20232023-08-01journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://riunet.upv.es/handle/10251/205220reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valénciainstname:Universitat Politècnica de València (UPV)InglésengAgencia Estatal de Investigación http://dx.doi.org/10.13039/501100011033 Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020 PID2020-115270GB-I00 ECUACIONES DIFERENCIALES ALEATORIAS. CUANTIFICACION DE LA INCERTIDUMBRE Y APLICACIONESAgencia Estatal de Investigación http://dx.doi.org/10.13039/501100011033 Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023 PDC2022-133429-I00 SISTEMA WEARABLE DE INTELIGENCIA ARTIFICIAL PARA LA TOMA DE DECISIONES DE PERSONAS CON DIABETESAgencia Estatal de Investigación http://dx.doi.org/10.13039/501100011033 Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023 PID2021-125549OB-I00 INTELIGENCIA ARTIFICIAL SOBRE ACELERADORES HARDWARE ESPECIALIZADOS Y SISTEMAS EMPOTRADOS PARA EL TRATAMIENTO PERSONALIZADO DE PRECISION DE LA DIABETESUniversitat Politècnica de València https://doi.org/10.13039/501100004233 FPI-2019-S2-20-555 Contrato predoctoralopen accesshttp://purl.org/coar/access_right/c_abf2Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) http://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessoai:riunet.upv.es:10251/2052202026-06-13T07:49:27Z
score 15,81155

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