Please use this identifier to cite or link to this item:
http://repositorio.ufc.br/handle/riufc/61872
Type: | Artigo de Periódico |
Title: | Surrogate based optimization of functionally graded plates using radial basis functions |
Authors: | Ribeiro, Leonardo Gonçalves Maia, Marina Alves Parente Junior, Evandro Melo, Antônio Macário Cartaxo de |
Keywords: | Functionally graded plates;Sequential approximate optimization;Radial basis functions;Surrogate modeling |
Issue Date: | 2020 |
Publisher: | Elsevier Ltd. - https://reader.elsevier.com/ |
Citation: | RIBEIRO, Leonardo Gonçalves ; MAIA, Marina Alves; PARENTE JUNIOR., Evandro; MELO, Antônio Macário Cartaxo de.Surrogate based optimization of functionally graded plates using radial basis functions. Composite Structures, v. 252, p.01-22, 2020. Article 112677. |
Abstract: | This work presents an efficient methodology for optimum design of functionally graded plates. Isogeometric analysis is used to evaluate the structural responses and the material gradation is described using B‐Splines to enhance design flexibility. A constraint is included in the optimization model to ensure a smooth material gradation. In order to improve the computational efficiency of the optimization process, a surrogate model based on Radial Basis Functions is used to accurately approximate the structural responses. Different methods to define the width of basis functions based on analytical and cross‐validation techniques are adopted and compared. Two infill criteria based on the expected improvement technique are used to continuously improve the surrogate model accuracy by balancing both the local and global searches. The accuracy and efficiency of the proposed approaches are assessed through a set of problems involving the maximization of the buckling load and the fundamental frequency of functionally graded plates, showing excellent results. |
URI: | http://www.repositorio.ufc.br/handle/riufc/61872 |
ISSN: | 0263-8223 |
Access Rights: | Acesso Aberto |
Appears in Collections: | DECC - Artigos publicados em revistas científicas |
Files in This Item:
File | Description | Size | Format | |
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2020_art_lgribeiro.pdf | 1,59 MB | Adobe PDF | View/Open |
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