Development of an open optimization framework for aeronautical applications
Autor(a) principal: | |
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Data de Publicação: | 2014 |
Tipo de documento: | Tese |
Idioma: | eng |
Título da fonte: | Biblioteca Digital de Teses e Dissertações do ITA |
Texto Completo: | http://www.bd.bibl.ita.br/tde_busca/arquivo.php?codArquivo=3082 |
Resumo: | The aeronautical industry, more precisely the aircraft manufacturing sector, is a demanding business area in which the design development cycles are continuously shrinking whilst the technical requirements are becoming more stringent due to the fierce competition. The present work considers the adoption of the multidisciplinary design optimization concept, which is also known by the MDO acronym, as a way of adapting to this new reality. In the MDO concept, the design is performed in a concurrent fashion through the integration of the engineering processes in environments know as ``frameworks';';. The work presents the development of a set of tools that can be adopted as numerical procedures inside existing frameworks or they can be coupled to create the basic structure of an open MDO framework, focused in aeronautical engineering and with special attention to aerodynamic design problems. These tools are embedded in different modules and they are employed in a series of study cases focused in aeronautical applications. These studies have shown how aspects associated with the choice of the geometrical parameterization and the upper and lower range limits of the parametric variables can yield different geometries during the optimization process. Moreover, the present work shows that only those geometric parameterizations that consider high order polynomials can guarantee that the same final geometry is achieved at the end of the optimization process. The increase in the polynomial order leads to optimized solutions with lower drag coefficients. The aerodynamic optimizations performed with a neural network have shown the benefits that the approximation methods can provide in terms of computational cost. The complete set of tools developed during this work can contribute to improve the capability of the Computational Fluid Dynamics group at Instituto de Aeronáutica e Espaço (IAE) and at Instituto Tecnológico de Aeronáutica (ITA) by the incorporation of this open environment for analysis and multidisciplinary optimizations. These tools can become an initial structure focused in a collaborative research activity between academia and industry. |
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Development of an open optimization framework for aeronautical applicationsProjeto de aeronavesAlgoritmos genéticosEstrutura de aeronaves e HelicópterosRedes neuraisConfigurações aerodinâmicasFabricação de aeronavesEngenharia aeronáuticaThe aeronautical industry, more precisely the aircraft manufacturing sector, is a demanding business area in which the design development cycles are continuously shrinking whilst the technical requirements are becoming more stringent due to the fierce competition. The present work considers the adoption of the multidisciplinary design optimization concept, which is also known by the MDO acronym, as a way of adapting to this new reality. In the MDO concept, the design is performed in a concurrent fashion through the integration of the engineering processes in environments know as ``frameworks';';. The work presents the development of a set of tools that can be adopted as numerical procedures inside existing frameworks or they can be coupled to create the basic structure of an open MDO framework, focused in aeronautical engineering and with special attention to aerodynamic design problems. These tools are embedded in different modules and they are employed in a series of study cases focused in aeronautical applications. These studies have shown how aspects associated with the choice of the geometrical parameterization and the upper and lower range limits of the parametric variables can yield different geometries during the optimization process. Moreover, the present work shows that only those geometric parameterizations that consider high order polynomials can guarantee that the same final geometry is achieved at the end of the optimization process. The increase in the polynomial order leads to optimized solutions with lower drag coefficients. The aerodynamic optimizations performed with a neural network have shown the benefits that the approximation methods can provide in terms of computational cost. The complete set of tools developed during this work can contribute to improve the capability of the Computational Fluid Dynamics group at Instituto de Aeronáutica e Espaço (IAE) and at Instituto Tecnológico de Aeronáutica (ITA) by the incorporation of this open environment for analysis and multidisciplinary optimizations. These tools can become an initial structure focused in a collaborative research activity between academia and industry.Instituto Tecnológico de AeronáuticaJoão Luiz Filgueiras de AzevedoAlexandre Pequeno Antunes2014-08-28info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesishttp://www.bd.bibl.ita.br/tde_busca/arquivo.php?codArquivo=3082reponame:Biblioteca Digital de Teses e Dissertações do ITAinstname:Instituto Tecnológico de Aeronáuticainstacron:ITAenginfo:eu-repo/semantics/openAccessapplication/pdf2019-02-02T14:05:03Zoai:agregador.ibict.br.BDTD_ITA:oai:ita.br:3082http://oai.bdtd.ibict.br/requestopendoar:null2020-05-28 19:41:00.025Biblioteca Digital de Teses e Dissertações do ITA - Instituto Tecnológico de Aeronáuticatrue |
dc.title.none.fl_str_mv |
Development of an open optimization framework for aeronautical applications |
title |
Development of an open optimization framework for aeronautical applications |
spellingShingle |
Development of an open optimization framework for aeronautical applications Alexandre Pequeno Antunes Projeto de aeronaves Algoritmos genéticos Estrutura de aeronaves e Helicópteros Redes neurais Configurações aerodinâmicas Fabricação de aeronaves Engenharia aeronáutica |
title_short |
Development of an open optimization framework for aeronautical applications |
title_full |
Development of an open optimization framework for aeronautical applications |
title_fullStr |
Development of an open optimization framework for aeronautical applications |
title_full_unstemmed |
Development of an open optimization framework for aeronautical applications |
title_sort |
Development of an open optimization framework for aeronautical applications |
author |
Alexandre Pequeno Antunes |
author_facet |
Alexandre Pequeno Antunes |
author_role |
author |
dc.contributor.none.fl_str_mv |
João Luiz Filgueiras de Azevedo |
dc.contributor.author.fl_str_mv |
Alexandre Pequeno Antunes |
dc.subject.por.fl_str_mv |
Projeto de aeronaves Algoritmos genéticos Estrutura de aeronaves e Helicópteros Redes neurais Configurações aerodinâmicas Fabricação de aeronaves Engenharia aeronáutica |
topic |
Projeto de aeronaves Algoritmos genéticos Estrutura de aeronaves e Helicópteros Redes neurais Configurações aerodinâmicas Fabricação de aeronaves Engenharia aeronáutica |
dc.description.none.fl_txt_mv |
The aeronautical industry, more precisely the aircraft manufacturing sector, is a demanding business area in which the design development cycles are continuously shrinking whilst the technical requirements are becoming more stringent due to the fierce competition. The present work considers the adoption of the multidisciplinary design optimization concept, which is also known by the MDO acronym, as a way of adapting to this new reality. In the MDO concept, the design is performed in a concurrent fashion through the integration of the engineering processes in environments know as ``frameworks';';. The work presents the development of a set of tools that can be adopted as numerical procedures inside existing frameworks or they can be coupled to create the basic structure of an open MDO framework, focused in aeronautical engineering and with special attention to aerodynamic design problems. These tools are embedded in different modules and they are employed in a series of study cases focused in aeronautical applications. These studies have shown how aspects associated with the choice of the geometrical parameterization and the upper and lower range limits of the parametric variables can yield different geometries during the optimization process. Moreover, the present work shows that only those geometric parameterizations that consider high order polynomials can guarantee that the same final geometry is achieved at the end of the optimization process. The increase in the polynomial order leads to optimized solutions with lower drag coefficients. The aerodynamic optimizations performed with a neural network have shown the benefits that the approximation methods can provide in terms of computational cost. The complete set of tools developed during this work can contribute to improve the capability of the Computational Fluid Dynamics group at Instituto de Aeronáutica e Espaço (IAE) and at Instituto Tecnológico de Aeronáutica (ITA) by the incorporation of this open environment for analysis and multidisciplinary optimizations. These tools can become an initial structure focused in a collaborative research activity between academia and industry. |
description |
The aeronautical industry, more precisely the aircraft manufacturing sector, is a demanding business area in which the design development cycles are continuously shrinking whilst the technical requirements are becoming more stringent due to the fierce competition. The present work considers the adoption of the multidisciplinary design optimization concept, which is also known by the MDO acronym, as a way of adapting to this new reality. In the MDO concept, the design is performed in a concurrent fashion through the integration of the engineering processes in environments know as ``frameworks';';. The work presents the development of a set of tools that can be adopted as numerical procedures inside existing frameworks or they can be coupled to create the basic structure of an open MDO framework, focused in aeronautical engineering and with special attention to aerodynamic design problems. These tools are embedded in different modules and they are employed in a series of study cases focused in aeronautical applications. These studies have shown how aspects associated with the choice of the geometrical parameterization and the upper and lower range limits of the parametric variables can yield different geometries during the optimization process. Moreover, the present work shows that only those geometric parameterizations that consider high order polynomials can guarantee that the same final geometry is achieved at the end of the optimization process. The increase in the polynomial order leads to optimized solutions with lower drag coefficients. The aerodynamic optimizations performed with a neural network have shown the benefits that the approximation methods can provide in terms of computational cost. The complete set of tools developed during this work can contribute to improve the capability of the Computational Fluid Dynamics group at Instituto de Aeronáutica e Espaço (IAE) and at Instituto Tecnológico de Aeronáutica (ITA) by the incorporation of this open environment for analysis and multidisciplinary optimizations. These tools can become an initial structure focused in a collaborative research activity between academia and industry. |
publishDate |
2014 |
dc.date.none.fl_str_mv |
2014-08-28 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/doctoralThesis |
status_str |
publishedVersion |
format |
doctoralThesis |
dc.identifier.uri.fl_str_mv |
http://www.bd.bibl.ita.br/tde_busca/arquivo.php?codArquivo=3082 |
url |
http://www.bd.bibl.ita.br/tde_busca/arquivo.php?codArquivo=3082 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Instituto Tecnológico de Aeronáutica |
publisher.none.fl_str_mv |
Instituto Tecnológico de Aeronáutica |
dc.source.none.fl_str_mv |
reponame:Biblioteca Digital de Teses e Dissertações do ITA instname:Instituto Tecnológico de Aeronáutica instacron:ITA |
reponame_str |
Biblioteca Digital de Teses e Dissertações do ITA |
collection |
Biblioteca Digital de Teses e Dissertações do ITA |
instname_str |
Instituto Tecnológico de Aeronáutica |
instacron_str |
ITA |
institution |
ITA |
repository.name.fl_str_mv |
Biblioteca Digital de Teses e Dissertações do ITA - Instituto Tecnológico de Aeronáutica |
repository.mail.fl_str_mv |
|
subject_por_txtF_mv |
Projeto de aeronaves Algoritmos genéticos Estrutura de aeronaves e Helicópteros Redes neurais Configurações aerodinâmicas Fabricação de aeronaves Engenharia aeronáutica |
_version_ |
1706809294965440512 |