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Allying topology and shape optimization through machine learning algorithms

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Allying topology and shape optimization through machine learning algorithms

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Muñoz-Pellicer, D.; Nadal, E.; Albelda Vitoria, J.; Chinesta Soria, FJ.; Ródenas, JJ. (2022). Allying topology and shape optimization through machine learning algorithms. Finite Elements in Analysis and Design. 204:1-19. https://doi.org/10.1016/j.finel.2021.103719

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/202262

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Title: Allying topology and shape optimization through machine learning algorithms
Author: Muñoz-Pellicer, David Nadal, Enrique Albelda Vitoria, José CHINESTA SORIA, FRANCISCO JOSE Ródenas, Juan José
UPV Unit: Universitat Politècnica de València. Escuela Técnica Superior de Ingeniería del Diseño - Escola Tècnica Superior d'Enginyeria del Disseny
Issued date:
Abstract:
[EN] Structural optimization is part of the mechanical engineering field and, in most cases, tries to minimize the overall weight of a given design domain, subjected to functionality constraints given in terms of stresses ...[+]
Subjects: Topology optimization , Mesh refinement , H-adaptivity , Shape optimization , Hybrid optimization , Machine learning , Dimensionality reduction , Locally linear embedding
Copyrigths: Cerrado
Source:
Finite Elements in Analysis and Design. (issn: 0168-874X )
DOI: 10.1016/j.finel.2021.103719
Publisher:
Elsevier
Publisher version: https://doi.org/10.1016/j.finel.2021.103719
Project ID:
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/DPI2017-89816-R/ES/MODELADO PERSONALIZADO DE LA RESPUESTA DEL TEJIDO OSEO DE PACIENTES A PARTIR DE IMAGENES 3D MEDIANTE MALLADOS CARTESIANOS DE ELEMENTOS FINITOS/
info:eu-repo/grantAgreement/MECD//FPU16%2F07121/ES/FPU16%2F07121/
info:eu-repo/grantAgreement/GENERALITAT VALENCIANA//PROMETEO%2F2021%2F046//MODELADO NUMÉRICO AVANZADO EN INGENIERÍA MECÁNICA/
Thanks:
The authors gratefully acknowledge the financial support of Ministry of Economy and Competitiveness (project DPI2017-89816-R) and Ministry of Science, Innovation and Universities (FPU16/07121) of the Government of Spain.
Type: Artículo

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