Optimum design of steel columns filled with concrete via genetic algorithm: environmental impact and cost analysis

Detalhes bibliográficos
Autor(a) principal: Guimarães,Sane Alves
Data de Publicação: 2022
Outros Autores: Klein,Diego, Calenzani,Adenilcia Fernanda Grobério, Alves,Élcio Cassimiro
Tipo de documento: Artigo
Idioma: eng
Título da fonte: REM - International Engineering Journal
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2448-167X2022000200117
Resumo: Abstract The use of concrete-filled tubular columns as part of structural systems has steadily increased throughout the years. The growing demand for structural elements of this nature is a direct result of the possibility to use various cross-section shapes that have increased strength, along with resistance to fire and other corrosive agents. The main objective of this article is to present the formulation for optimizing the design of composite columns in accordance with prescriptions from ABNT NBR 16239: 2013, considering financial cost and CO2 emission during manufacturing as objective functions. A Genetic Algorithm was used to solve three examples of composite tubular columns subjected to combined bending and compression, considering major axis and unsymmetrical bending. The financial cost in Brazilian currency and the CO2 emission in kilograms attributed to manufacturing concrete-filled composite columns were calculated and the optimization procedure was implemented on composite columns featuring CHS, RHS and SHS steel members. This study also considers the different concrete strengths and the optional inclusion of longitudinal rebar. For the cases analyzed, the financially and environmentally optimum design corresponds to a CHS composite column with no longitudinal rebar and the highest concrete strength tested, except when unsymmetrical bending is applied, in which case the optimum solution includes longitudinal rebar. Furthermore, results indicate that structural steel has the highest impact on the CO2 emission of the optimal designs. For the column with longitudinal rebar, the reinforcement steel presents the second highest financial impact, while concrete is responsible for the highest influence on CO2 emission.
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spelling Optimum design of steel columns filled with concrete via genetic algorithm: environmental impact and cost analysissteel columns filled with concreteoptimizationcost analysisCO2 emissiongenetic algorithmAbstract The use of concrete-filled tubular columns as part of structural systems has steadily increased throughout the years. The growing demand for structural elements of this nature is a direct result of the possibility to use various cross-section shapes that have increased strength, along with resistance to fire and other corrosive agents. The main objective of this article is to present the formulation for optimizing the design of composite columns in accordance with prescriptions from ABNT NBR 16239: 2013, considering financial cost and CO2 emission during manufacturing as objective functions. A Genetic Algorithm was used to solve three examples of composite tubular columns subjected to combined bending and compression, considering major axis and unsymmetrical bending. The financial cost in Brazilian currency and the CO2 emission in kilograms attributed to manufacturing concrete-filled composite columns were calculated and the optimization procedure was implemented on composite columns featuring CHS, RHS and SHS steel members. This study also considers the different concrete strengths and the optional inclusion of longitudinal rebar. For the cases analyzed, the financially and environmentally optimum design corresponds to a CHS composite column with no longitudinal rebar and the highest concrete strength tested, except when unsymmetrical bending is applied, in which case the optimum solution includes longitudinal rebar. Furthermore, results indicate that structural steel has the highest impact on the CO2 emission of the optimal designs. For the column with longitudinal rebar, the reinforcement steel presents the second highest financial impact, while concrete is responsible for the highest influence on CO2 emission.Fundação Gorceix2022-04-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S2448-167X2022000200117REM - International Engineering Journal v.75 n.2 2022reponame:REM - International Engineering Journalinstname:Fundação Gorceix (FG)instacron:FG10.1590/0370-44672021750034info:eu-repo/semantics/openAccessGuimarães,Sane AlvesKlein,DiegoCalenzani,Adenilcia Fernanda GrobérioAlves,Élcio Cassimiroeng2022-03-30T00:00:00Zoai:scielo:S2448-167X2022000200117Revistahttps://www.rem.com.br/?lang=pt-brPRIhttps://old.scielo.br/oai/scielo-oai.php||editor@rem.com.br2448-167X2448-167Xopendoar:2022-03-30T00:00REM - International Engineering Journal - Fundação Gorceix (FG)false
dc.title.none.fl_str_mv Optimum design of steel columns filled with concrete via genetic algorithm: environmental impact and cost analysis
title Optimum design of steel columns filled with concrete via genetic algorithm: environmental impact and cost analysis
spellingShingle Optimum design of steel columns filled with concrete via genetic algorithm: environmental impact and cost analysis
Guimarães,Sane Alves
steel columns filled with concrete
optimization
cost analysis
CO2 emission
genetic algorithm
title_short Optimum design of steel columns filled with concrete via genetic algorithm: environmental impact and cost analysis
title_full Optimum design of steel columns filled with concrete via genetic algorithm: environmental impact and cost analysis
title_fullStr Optimum design of steel columns filled with concrete via genetic algorithm: environmental impact and cost analysis
title_full_unstemmed Optimum design of steel columns filled with concrete via genetic algorithm: environmental impact and cost analysis
title_sort Optimum design of steel columns filled with concrete via genetic algorithm: environmental impact and cost analysis
author Guimarães,Sane Alves
author_facet Guimarães,Sane Alves
Klein,Diego
Calenzani,Adenilcia Fernanda Grobério
Alves,Élcio Cassimiro
author_role author
author2 Klein,Diego
Calenzani,Adenilcia Fernanda Grobério
Alves,Élcio Cassimiro
author2_role author
author
author
dc.contributor.author.fl_str_mv Guimarães,Sane Alves
Klein,Diego
Calenzani,Adenilcia Fernanda Grobério
Alves,Élcio Cassimiro
dc.subject.por.fl_str_mv steel columns filled with concrete
optimization
cost analysis
CO2 emission
genetic algorithm
topic steel columns filled with concrete
optimization
cost analysis
CO2 emission
genetic algorithm
description Abstract The use of concrete-filled tubular columns as part of structural systems has steadily increased throughout the years. The growing demand for structural elements of this nature is a direct result of the possibility to use various cross-section shapes that have increased strength, along with resistance to fire and other corrosive agents. The main objective of this article is to present the formulation for optimizing the design of composite columns in accordance with prescriptions from ABNT NBR 16239: 2013, considering financial cost and CO2 emission during manufacturing as objective functions. A Genetic Algorithm was used to solve three examples of composite tubular columns subjected to combined bending and compression, considering major axis and unsymmetrical bending. The financial cost in Brazilian currency and the CO2 emission in kilograms attributed to manufacturing concrete-filled composite columns were calculated and the optimization procedure was implemented on composite columns featuring CHS, RHS and SHS steel members. This study also considers the different concrete strengths and the optional inclusion of longitudinal rebar. For the cases analyzed, the financially and environmentally optimum design corresponds to a CHS composite column with no longitudinal rebar and the highest concrete strength tested, except when unsymmetrical bending is applied, in which case the optimum solution includes longitudinal rebar. Furthermore, results indicate that structural steel has the highest impact on the CO2 emission of the optimal designs. For the column with longitudinal rebar, the reinforcement steel presents the second highest financial impact, while concrete is responsible for the highest influence on CO2 emission.
publishDate 2022
dc.date.none.fl_str_mv 2022-04-01
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=S2448-167X2022000200117
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2448-167X2022000200117
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/0370-44672021750034
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 Fundação Gorceix
publisher.none.fl_str_mv Fundação Gorceix
dc.source.none.fl_str_mv REM - International Engineering Journal v.75 n.2 2022
reponame:REM - International Engineering Journal
instname:Fundação Gorceix (FG)
instacron:FG
instname_str Fundação Gorceix (FG)
instacron_str FG
institution FG
reponame_str REM - International Engineering Journal
collection REM - International Engineering Journal
repository.name.fl_str_mv REM - International Engineering Journal - Fundação Gorceix (FG)
repository.mail.fl_str_mv ||editor@rem.com.br
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