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Practical metamodel-assisted multi-objective design optimization for improved sustainability and buildability of wind turbine foundations

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Practical metamodel-assisted multi-objective design optimization for improved sustainability and buildability of wind turbine foundations

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dc.contributor.author Mathern, Alexandre es_ES
dc.contributor.author Penadés-Plà, Vicent es_ES
dc.contributor.author Armesto Barros, Jesús es_ES
dc.contributor.author Yepes, V. es_ES
dc.date.accessioned 2022-01-24T19:29:42Z
dc.date.available 2022-01-24T19:29:42Z
dc.date.issued 2022-01-18 es_ES
dc.identifier.issn 1615-147X es_ES
dc.identifier.uri http://hdl.handle.net/10251/180137
dc.description.abstract [EN] In this work, we study the potential of using kriging metamodelling to perform multi-objective structural design optimization using finite element analysis software and design standards while keeping the computational efforts low. A method is proposed, which includes sustainability and buildability objectives, and it is applied to a case study of reinforced concrete foundations for wind turbines based on data from a large Swedish wind farm project. Sensitivity analyses are conducted to investigate the influence of the penalty factor applied to unfeasible solutions and the size of the initial sample generated by Latin hypercube sampling. A multi-objective optimization is then performed to obtain the optimum designs for different weight combinations for the four objectives considered. Results show that the kriging-obtained designs from samples of 20 designs outperform the best designs in the samples of 1000 designs. The optimum designs obtained by the proposed method have a sustainability impact 8¿15% lower than the designs developed by traditional methods. es_ES
dc.description.sponsorship Open access funding provided by Chalmers University of Technology. This work was fnancially supported by Sweden's Innovation Agency (Grant Number: 2017-03312), the Swedish Transport Administration (Grant Number: BBT-2017- 037), the Swedish Wind Power Technology Centre (SWPTC), NCC, and Grant PID2020-117056RB-I00 funded by MCIN/AEI/ 10.13039/501100011033 and by ERDF A way of making Europe. es_ES
dc.language Inglés es_ES
dc.publisher Springer-Verlag es_ES
dc.relation.ispartof Structural and Multidisciplinary Optimization es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Multidisciplinary design optimization es_ES
dc.subject Structural design es_ES
dc.subject Kriging surrogate model es_ES
dc.subject Reinforced concrete structures es_ES
dc.subject Multi-criteria decision making es_ES
dc.subject Parametric design es_ES
dc.subject.classification INGENIERIA DE LA CONSTRUCCION es_ES
dc.title Practical metamodel-assisted multi-objective design optimization for improved sustainability and buildability of wind turbine foundations es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1007/s00158-021-03154-0 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-117056RB-I00/ES/OPTIMIZACION HIBRIDA DEL CICLO DE VIDA DE PUENTES Y ESTRUCTURAS MIXTAS Y MODULARES DE ALTA EFICIENCIA SOCIAL Y MEDIOAMBIENTAL BAJO PRESUPUESTOS RESTRICTIVOS/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/VINNOVA//2017-03312/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/Swedish Transport Administration//BBT-2017-037/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Instituto de Ciencia y Tecnología del Hormigón - Institut de Ciència i Tecnologia del Formigó es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería de la Construcción y de Proyectos de Ingeniería Civil - Departament d'Enginyeria de la Construcció i de Projectes d'Enginyeria Civil es_ES
dc.description.bibliographicCitation Mathern, A.; Penadés-Plà, V.; Armesto Barros, J.; Yepes, V. (2022). Practical metamodel-assisted multi-objective design optimization for improved sustainability and buildability of wind turbine foundations. Structural and Multidisciplinary Optimization. 65(46):1-16. https://doi.org/10.1007/s00158-021-03154-0 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1007/s00158-021-03154-0 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 16 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 65 es_ES
dc.description.issue 46 es_ES
dc.relation.pasarela S\453455 es_ES
dc.contributor.funder AGENCIA ESTATAL DE INVESTIGACION es_ES
dc.contributor.funder Swedish Transport Administration es_ES
dc.contributor.funder European Regional Development Fund es_ES
dc.contributor.funder Swedish Wind Power Technology Centre es_ES
dc.contributor.funder Swedish Governmental Agency for Innovation Systems es_ES
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dc.subject.ods 07.- Asegurar el acceso a energías asequibles, fiables, sostenibles y modernas para todos es_ES
dc.subject.ods 09.- Desarrollar infraestructuras resilientes, promover la industrialización inclusiva y sostenible, y fomentar la innovación es_ES


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