An Implementation of Self-Organizing Maps for Airfoil Design Exploration via Multi-Objective Optimization Technique
| Autor(a) principal: | |
|---|---|
| Data de Publicação: | 2016 |
| Outros Autores: | , , |
| Tipo de documento: | Artigo |
| Idioma: | eng |
| Título da fonte: | Journal of Aerospace Technology and Management (Online) |
| Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2175-91462016000200193 |
Resumo: | ABSTRACT Design candidates obtained from optimization techniques may have meaningful information, which provides not only the best solution, but also a relationship between object functions and design variables. In particular, trade-off studies for optimum airfoil shape design involving various objectives and design variables require the effective analysis tool to take into account a complexity between objectives and design variables. In this study, for the multiple-conflicting objectives that need to be simultaneously fulfilled, the real-coded Adaptive Range Multi-Objective Genetic Algorithm code, which represents the global and stochastic multi-objective evolutionary algorithm, was developed for an airfoil shape design. Furthermore, the PARSEC method reflecting geometrical properties of airfoil is adopted to generate airfoil shapes. In addition, the Self-Organizing Maps, based on the neural network, are used to visualize trade-offs of a relationship between the objective function space and the design variable space obtained by evolutionary computation. The Self-Organizing Maps that can be considered as data mining of the engineering design generate clusters of object functions and design variables as an essential role of trade-off studies. The aerodynamic data for all candidate airfoils is obtained through Computational Fluid Dynamics. Lastly, the relationship between the maximum lift coefficient and maximum lift-to-drag ratio as object functions and 12 airfoil design parameters based on the PARSEC method is investigated using the Self-Organizing Maps method. |
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An Implementation of Self-Organizing Maps for Airfoil Design Exploration via Multi-Objective Optimization TechniqueAerodynamicsAdaptive Range Multi-Object Genetic AlgorithmPARSECSelf-Organizing MapComputational Fluid DynamicsABSTRACT Design candidates obtained from optimization techniques may have meaningful information, which provides not only the best solution, but also a relationship between object functions and design variables. In particular, trade-off studies for optimum airfoil shape design involving various objectives and design variables require the effective analysis tool to take into account a complexity between objectives and design variables. In this study, for the multiple-conflicting objectives that need to be simultaneously fulfilled, the real-coded Adaptive Range Multi-Objective Genetic Algorithm code, which represents the global and stochastic multi-objective evolutionary algorithm, was developed for an airfoil shape design. Furthermore, the PARSEC method reflecting geometrical properties of airfoil is adopted to generate airfoil shapes. In addition, the Self-Organizing Maps, based on the neural network, are used to visualize trade-offs of a relationship between the objective function space and the design variable space obtained by evolutionary computation. The Self-Organizing Maps that can be considered as data mining of the engineering design generate clusters of object functions and design variables as an essential role of trade-off studies. The aerodynamic data for all candidate airfoils is obtained through Computational Fluid Dynamics. Lastly, the relationship between the maximum lift coefficient and maximum lift-to-drag ratio as object functions and 12 airfoil design parameters based on the PARSEC method is investigated using the Self-Organizing Maps method.Departamento de Ciência e Tecnologia Aeroespacial2016-06-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S2175-91462016000200193Journal of Aerospace Technology and Management v.8 n.2 2016reponame:Journal of Aerospace Technology and Management (Online)instname:Departamento de Ciência e Tecnologia Aeroespacial (DCTA)instacron:DCTA10.5028/jatm.v8i2.585info:eu-repo/semantics/openAccessJung,SungKiChoi,WonMartins-Filho,Luiz S.Madeira,Fernandoeng2016-08-02T00:00:00Zoai:scielo:S2175-91462016000200193Revistahttp://www.jatm.com.br/ONGhttps://old.scielo.br/oai/scielo-oai.php||secretary@jatm.com.br2175-91461984-9648opendoar:2016-08-02T00:00Journal of Aerospace Technology and Management (Online) - Departamento de Ciência e Tecnologia Aeroespacial (DCTA)false |
| dc.title.none.fl_str_mv |
An Implementation of Self-Organizing Maps for Airfoil Design Exploration via Multi-Objective Optimization Technique |
| title |
An Implementation of Self-Organizing Maps for Airfoil Design Exploration via Multi-Objective Optimization Technique |
| spellingShingle |
An Implementation of Self-Organizing Maps for Airfoil Design Exploration via Multi-Objective Optimization Technique Jung,SungKi Aerodynamics Adaptive Range Multi-Object Genetic Algorithm PARSEC Self-Organizing Map Computational Fluid Dynamics |
| title_short |
An Implementation of Self-Organizing Maps for Airfoil Design Exploration via Multi-Objective Optimization Technique |
| title_full |
An Implementation of Self-Organizing Maps for Airfoil Design Exploration via Multi-Objective Optimization Technique |
| title_fullStr |
An Implementation of Self-Organizing Maps for Airfoil Design Exploration via Multi-Objective Optimization Technique |
| title_full_unstemmed |
An Implementation of Self-Organizing Maps for Airfoil Design Exploration via Multi-Objective Optimization Technique |
| title_sort |
An Implementation of Self-Organizing Maps for Airfoil Design Exploration via Multi-Objective Optimization Technique |
| author |
Jung,SungKi |
| author_facet |
Jung,SungKi Choi,Won Martins-Filho,Luiz S. Madeira,Fernando |
| author_role |
author |
| author2 |
Choi,Won Martins-Filho,Luiz S. Madeira,Fernando |
| author2_role |
author author author |
| dc.contributor.author.fl_str_mv |
Jung,SungKi Choi,Won Martins-Filho,Luiz S. Madeira,Fernando |
| dc.subject.por.fl_str_mv |
Aerodynamics Adaptive Range Multi-Object Genetic Algorithm PARSEC Self-Organizing Map Computational Fluid Dynamics |
| topic |
Aerodynamics Adaptive Range Multi-Object Genetic Algorithm PARSEC Self-Organizing Map Computational Fluid Dynamics |
| description |
ABSTRACT Design candidates obtained from optimization techniques may have meaningful information, which provides not only the best solution, but also a relationship between object functions and design variables. In particular, trade-off studies for optimum airfoil shape design involving various objectives and design variables require the effective analysis tool to take into account a complexity between objectives and design variables. In this study, for the multiple-conflicting objectives that need to be simultaneously fulfilled, the real-coded Adaptive Range Multi-Objective Genetic Algorithm code, which represents the global and stochastic multi-objective evolutionary algorithm, was developed for an airfoil shape design. Furthermore, the PARSEC method reflecting geometrical properties of airfoil is adopted to generate airfoil shapes. In addition, the Self-Organizing Maps, based on the neural network, are used to visualize trade-offs of a relationship between the objective function space and the design variable space obtained by evolutionary computation. The Self-Organizing Maps that can be considered as data mining of the engineering design generate clusters of object functions and design variables as an essential role of trade-off studies. The aerodynamic data for all candidate airfoils is obtained through Computational Fluid Dynamics. Lastly, the relationship between the maximum lift coefficient and maximum lift-to-drag ratio as object functions and 12 airfoil design parameters based on the PARSEC method is investigated using the Self-Organizing Maps method. |
| publishDate |
2016 |
| dc.date.none.fl_str_mv |
2016-06-01 |
| dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
| dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
| format |
article |
| status_str |
publishedVersion |
| dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2175-91462016000200193 |
| url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2175-91462016000200193 |
| dc.language.iso.fl_str_mv |
eng |
| language |
eng |
| dc.relation.none.fl_str_mv |
10.5028/jatm.v8i2.585 |
| dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
| eu_rights_str_mv |
openAccess |
| dc.format.none.fl_str_mv |
text/html |
| dc.publisher.none.fl_str_mv |
Departamento de Ciência e Tecnologia Aeroespacial |
| publisher.none.fl_str_mv |
Departamento de Ciência e Tecnologia Aeroespacial |
| dc.source.none.fl_str_mv |
Journal of Aerospace Technology and Management v.8 n.2 2016 reponame:Journal of Aerospace Technology and Management (Online) instname:Departamento de Ciência e Tecnologia Aeroespacial (DCTA) instacron:DCTA |
| instname_str |
Departamento de Ciência e Tecnologia Aeroespacial (DCTA) |
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DCTA |
| institution |
DCTA |
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Journal of Aerospace Technology and Management (Online) |
| collection |
Journal of Aerospace Technology and Management (Online) |
| repository.name.fl_str_mv |
Journal of Aerospace Technology and Management (Online) - Departamento de Ciência e Tecnologia Aeroespacial (DCTA) |
| repository.mail.fl_str_mv |
||secretary@jatm.com.br |
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1754732531304890368 |