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dc.contributor.authorPons Prats, Jordi
dc.contributor.authorComa Company, Martí
dc.contributor.authorBetran, Jaume
dc.contributor.authorRoca, Xavier
dc.contributor.authorBugeda Castelltort, Gabriel
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Física
dc.contributor.otherUniversitat Politècnica de Catalunya. Doctorat en Ciència i Tecnologia Aeroespacials
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria Civil i Ambiental
dc.date.accessioned2021-03-23T16:33:54Z
dc.date.available2021-03-23T16:33:54Z
dc.date.issued2017
dc.identifier.citationPons-Prats, J. [et al.]. Industrial application of genetic algorithms to cost reduction of a wind turbine equipped with a tuned mass damper. A: International Conference on Evolutionary and Deterministic Methods for Design, Optimization and Control with Applications to Industrial and Societal Problems. "Evolutionary and Deterministic Methods for Design Optimization and Control With Applications to Industrial and Societal Problems". 2017, p. 419-436. ISBN 978-3-319-89890-2. DOI 10.1007/978-3-319-89890-2_27.
dc.identifier.isbn978-3-319-89890-2
dc.identifier.urihttp://hdl.handle.net/2117/342309
dc.description.abstractDesign optimization has already become an important tool in industry. The benefits are clear, but several drawbacksare still present, being the main one the computational cost. The numerical simulation involved in the solution of eachevaluation is usually costly, but time and computational resources are limited. Computational resources can be easilyincreased because, nowadays, its cost is rapidly decreasing. Anyway, there is always an upper limit due to financialconstraints. On the other hand, time is key in industry. Lead time must be reduced to ensure competitiveness. It meansthe design stage has a reduced time slo
dc.format.extent18 p.
dc.language.isoeng
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Energies::Energia eòlica
dc.subject.lcshWind turbines
dc.subject.otherRMOP
dc.subject.otherGenetic Algorithms
dc.subject.otherOptimization platform
dc.subject.otherWind Energy
dc.subject.otherWind Turbine design
dc.subject.otherTuned mass damper.
dc.titleIndustrial application of genetic algorithms to cost reduction of a wind turbine equipped with a tuned mass damper
dc.typeConference report
dc.subject.lemacTurbines -- Mètodes numèrics
dc.contributor.groupUniversitat Politècnica de Catalunya. GMNE - Grup de Mètodes Numèrics en Enginyeria
dc.contributor.groupUniversitat Politècnica de Catalunya. RMEE - Grup de Resistència de Materials i Estructures en l'Enginyeria
dc.identifier.doi10.1007/978-3-319-89890-2_27
dc.relation.publisherversionhttps://www.esteco.com/corporate/eurogen-2017
dc.rights.accessOpen Access
local.identifier.drac28703436
dc.description.versionPostprint (published version)
local.citation.authorPons-Prats, J.; Coma, M.; Betran, J.; Roca, X.; Bugeda, G.
local.citation.contributorInternational Conference on Evolutionary and Deterministic Methods for Design, Optimization and Control with Applications to Industrial and Societal Problems
local.citation.publicationNameEvolutionary and Deterministic Methods for Design Optimization and Control With Applications to Industrial and Societal Problems
local.citation.startingPage419
local.citation.endingPage436


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