Bi-level dominance GA for minimum weight and maximum feasibility robustness of composite structures
Autor(a) principal: | |
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Data de Publicação: | 2016 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10400.22/10216 |
Resumo: | In the proposed approach the robust design optimization (RDO) of composite structures is addressed as a bi-objective optimization problem with following objective functions: (1) the weight of the structure which optimality is associated with performance robustness; and (2) the variability of structural response which is associated with feasibility robustness of design constraints. The determinant of the variance–covariance matrix of the response is adopted for feasibility robustness assessment, being the sensitivities calculated by the adjoint variable method. The design and uncertainty rules are controlled by the following classes of variables and parameters: the deterministic design variables, the random design variables, and the random parameters. To solve the RDO of composite structures an evolutionary algorithm, denoted by Bi-level Dominance Multi-Objective Genetic Algorithm (MOGA-2D) is proposed. The Pareto front is built using a hierarchical structure where evolution is based on the exchange data between two populations: a small population using local dominance and elitism and an enlarged population to store the non-dominated solutions. The numerical tests show the capabilities of the approach. Although the optimal Pareto front establishes the trade-off between performance and robustness, knowledge on the importance of each uncertainty source can help the designer to make a decision on design space. |
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Bi-level dominance GA for minimum weight and maximum feasibility robustness of composite structuresMulti-objective optimizationComposite structuresMinimum weightFeasibility robustnessBi-level dominanceIn the proposed approach the robust design optimization (RDO) of composite structures is addressed as a bi-objective optimization problem with following objective functions: (1) the weight of the structure which optimality is associated with performance robustness; and (2) the variability of structural response which is associated with feasibility robustness of design constraints. The determinant of the variance–covariance matrix of the response is adopted for feasibility robustness assessment, being the sensitivities calculated by the adjoint variable method. The design and uncertainty rules are controlled by the following classes of variables and parameters: the deterministic design variables, the random design variables, and the random parameters. To solve the RDO of composite structures an evolutionary algorithm, denoted by Bi-level Dominance Multi-Objective Genetic Algorithm (MOGA-2D) is proposed. The Pareto front is built using a hierarchical structure where evolution is based on the exchange data between two populations: a small population using local dominance and elitism and an enlarged population to store the non-dominated solutions. The numerical tests show the capabilities of the approach. Although the optimal Pareto front establishes the trade-off between performance and robustness, knowledge on the importance of each uncertainty source can help the designer to make a decision on design space.ElsevierRepositório Científico do Instituto Politécnico do PortoAntónio, Carlos ConceiçãoHoffbauer, Luísa Natália20162117-01-01T00:00:00Z2016-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.22/10216eng10.1016/j.compstruct.2015.09.019metadata only accessinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-03-13T12:51:46Zoai:recipp.ipp.pt:10400.22/10216Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:30:41.422386Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Bi-level dominance GA for minimum weight and maximum feasibility robustness of composite structures |
title |
Bi-level dominance GA for minimum weight and maximum feasibility robustness of composite structures |
spellingShingle |
Bi-level dominance GA for minimum weight and maximum feasibility robustness of composite structures António, Carlos Conceição Multi-objective optimization Composite structures Minimum weight Feasibility robustness Bi-level dominance |
title_short |
Bi-level dominance GA for minimum weight and maximum feasibility robustness of composite structures |
title_full |
Bi-level dominance GA for minimum weight and maximum feasibility robustness of composite structures |
title_fullStr |
Bi-level dominance GA for minimum weight and maximum feasibility robustness of composite structures |
title_full_unstemmed |
Bi-level dominance GA for minimum weight and maximum feasibility robustness of composite structures |
title_sort |
Bi-level dominance GA for minimum weight and maximum feasibility robustness of composite structures |
author |
António, Carlos Conceição |
author_facet |
António, Carlos Conceição Hoffbauer, Luísa Natália |
author_role |
author |
author2 |
Hoffbauer, Luísa Natália |
author2_role |
author |
dc.contributor.none.fl_str_mv |
Repositório Científico do Instituto Politécnico do Porto |
dc.contributor.author.fl_str_mv |
António, Carlos Conceição Hoffbauer, Luísa Natália |
dc.subject.por.fl_str_mv |
Multi-objective optimization Composite structures Minimum weight Feasibility robustness Bi-level dominance |
topic |
Multi-objective optimization Composite structures Minimum weight Feasibility robustness Bi-level dominance |
description |
In the proposed approach the robust design optimization (RDO) of composite structures is addressed as a bi-objective optimization problem with following objective functions: (1) the weight of the structure which optimality is associated with performance robustness; and (2) the variability of structural response which is associated with feasibility robustness of design constraints. The determinant of the variance–covariance matrix of the response is adopted for feasibility robustness assessment, being the sensitivities calculated by the adjoint variable method. The design and uncertainty rules are controlled by the following classes of variables and parameters: the deterministic design variables, the random design variables, and the random parameters. To solve the RDO of composite structures an evolutionary algorithm, denoted by Bi-level Dominance Multi-Objective Genetic Algorithm (MOGA-2D) is proposed. The Pareto front is built using a hierarchical structure where evolution is based on the exchange data between two populations: a small population using local dominance and elitism and an enlarged population to store the non-dominated solutions. The numerical tests show the capabilities of the approach. Although the optimal Pareto front establishes the trade-off between performance and robustness, knowledge on the importance of each uncertainty source can help the designer to make a decision on design space. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016 2016-01-01T00:00:00Z 2117-01-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10400.22/10216 |
url |
http://hdl.handle.net/10400.22/10216 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1016/j.compstruct.2015.09.019 |
dc.rights.driver.fl_str_mv |
metadata only access info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
metadata only access |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Elsevier |
publisher.none.fl_str_mv |
Elsevier |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
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1799131402555359232 |