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Optimization of composite stiffened panels under mechanical and hygrothermal loads using neural networks and genetic algorithms

The present work develops an optimization procedure for a geometric design of a composite material stiffened panel with conventional stacking sequence using static analysis and hygrothermal effects. The procedure is based on a global approach strategy, composed by two steps: first, the response of the panel is obtained by a neural network system using the results of finite element analyses and, in a second step, a multi-objective optimization problem is solved using a genetic algorithm. The neural network implemented in the first step uses a sub-problem approach which allows to consider different temperature ranges. The compression load and relative humidity of the air are assumed to be constants throughout the considered temperature range.The mass, the hygrothermal expansion and the stresses between the skin and the stiffeners are defined as the optimality criteria. The presented optimization procedure is shown to yield the optimal structure design without compromising the computational efficiency

The authors acknowledge the financial support of the Spanish Government under the Project DPI2009-08048

Elsevier

Manager: Ministerio de Ciencia e Innovación (Espanya)
Author: Marín Hernández, Lorena
Trias Mansilla, Daniel
Badalló i Cañellas, Pere
Mayugo Majó, Joan Andreu
Abstract: The present work develops an optimization procedure for a geometric design of a composite material stiffened panel with conventional stacking sequence using static analysis and hygrothermal effects. The procedure is based on a global approach strategy, composed by two steps: first, the response of the panel is obtained by a neural network system using the results of finite element analyses and, in a second step, a multi-objective optimization problem is solved using a genetic algorithm. The neural network implemented in the first step uses a sub-problem approach which allows to consider different temperature ranges. The compression load and relative humidity of the air are assumed to be constants throughout the considered temperature range.The mass, the hygrothermal expansion and the stresses between the skin and the stiffeners are defined as the optimality criteria. The presented optimization procedure is shown to yield the optimal structure design without compromising the computational efficiency
The authors acknowledge the financial support of the Spanish Government under the Project DPI2009-08048
Format: application/pdf
Document access: http://hdl.handle.net/10256/13782
Language: eng
Publisher: Elsevier
Collection: info:eu-repo/semantics/altIdentifier/doi/10.1016/j.compstruct.2012.04.024
info:eu-repo/semantics/altIdentifier/issn/0263-8223
info:eu-repo/semantics/altIdentifier/eissn/1879-1085
info:eu-repo/grantAgreement/MICINN//DPI2009-08048/ES/Ensayo Virtual Y Supervision Estructural De Revestimientos De Cfrp Bajo Cargas Mecanicas Y Higrotermicas/
Rights: Tots els drets reservats
Subject: Elements finits, Mètode dels
Finite element method
Algorismes genètics
Optimització matemàtica
Mathematical optimization
Xarxes neuronals (Informàtica)
Neural networks (Computer science)
Genetic algorithms
Anàlisi numèrica
Numerical analysis
Title: Optimization of composite stiffened panels under mechanical and hygrothermal loads using neural networks and genetic algorithms
Type: info:eu-repo/semantics/article
Repository: DUGiDocs

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