Optimization of slender reinforced concrete columns subjected to biaxial bending using genetic algorithms
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Revista IBRACON de Estruturas e Materiais |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1983-41952021000600204 |
Resumo: | abstract: In this paper, a computational tool was developed to optimize the design of slender reinforced concrete columns subjected to biaxial bending considering the material and geometric nonlinearities rigorously. The optimization process utilizes the technique of genetic algorithms to find the best cross-sectional dimension and the best distribution and amount of reinforcement, to minimize the cost of the column subject to certain constraints of strength, stability, feasibility and regulatory. The analysis applies to rectangular cross-section of columns, and constant and symmetrical distribution of reinforcement. The results obtained by the developed software converge properly to an optimal solution or to a solution around the optimum in a significantly shorter time interval in relation to the results obtained when considering all solutions within the previously established domain. The effect of slenderness on the optimal design of reinforced concrete columns was also analyzed. The results showed that the column cost increases as the slenderness ratio increases, and steel becomes the predominant material to establish the equilibrium of the structural element. |
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Optimization of slender reinforced concrete columns subjected to biaxial bending using genetic algorithmsstructural analysisreinforced concrete designmaterial nonlinearitygeometric nonlinearitysecond order effectsabstract: In this paper, a computational tool was developed to optimize the design of slender reinforced concrete columns subjected to biaxial bending considering the material and geometric nonlinearities rigorously. The optimization process utilizes the technique of genetic algorithms to find the best cross-sectional dimension and the best distribution and amount of reinforcement, to minimize the cost of the column subject to certain constraints of strength, stability, feasibility and regulatory. The analysis applies to rectangular cross-section of columns, and constant and symmetrical distribution of reinforcement. The results obtained by the developed software converge properly to an optimal solution or to a solution around the optimum in a significantly shorter time interval in relation to the results obtained when considering all solutions within the previously established domain. The effect of slenderness on the optimal design of reinforced concrete columns was also analyzed. The results showed that the column cost increases as the slenderness ratio increases, and steel becomes the predominant material to establish the equilibrium of the structural element.IBRACON - Instituto Brasileiro do Concreto2021-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1983-41952021000600204Revista IBRACON de Estruturas e Materiais v.14 n.6 2021reponame:Revista IBRACON de Estruturas e Materiaisinstname:Instituto Brasileiro do Concreto (IBRACON)instacron:IBRACON10.1590/s1983-41952021000600010info:eu-repo/semantics/openAccessPires,Susana de LimaSilva,Maria Cecilia Amorim Teixeira daeng2021-06-29T00:00:00Zoai:scielo:S1983-41952021000600204Revistahttp://www.revistas.ibracon.org.br/index.php/riemhttps://old.scielo.br/oai/scielo-oai.phpeditores.riem@gmail.com||arlene@ibracon.org.br1983-41951983-4195opendoar:2021-06-29T00:00Revista IBRACON de Estruturas e Materiais - Instituto Brasileiro do Concreto (IBRACON)false |
dc.title.none.fl_str_mv |
Optimization of slender reinforced concrete columns subjected to biaxial bending using genetic algorithms |
title |
Optimization of slender reinforced concrete columns subjected to biaxial bending using genetic algorithms |
spellingShingle |
Optimization of slender reinforced concrete columns subjected to biaxial bending using genetic algorithms Pires,Susana de Lima structural analysis reinforced concrete design material nonlinearity geometric nonlinearity second order effects |
title_short |
Optimization of slender reinforced concrete columns subjected to biaxial bending using genetic algorithms |
title_full |
Optimization of slender reinforced concrete columns subjected to biaxial bending using genetic algorithms |
title_fullStr |
Optimization of slender reinforced concrete columns subjected to biaxial bending using genetic algorithms |
title_full_unstemmed |
Optimization of slender reinforced concrete columns subjected to biaxial bending using genetic algorithms |
title_sort |
Optimization of slender reinforced concrete columns subjected to biaxial bending using genetic algorithms |
author |
Pires,Susana de Lima |
author_facet |
Pires,Susana de Lima Silva,Maria Cecilia Amorim Teixeira da |
author_role |
author |
author2 |
Silva,Maria Cecilia Amorim Teixeira da |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Pires,Susana de Lima Silva,Maria Cecilia Amorim Teixeira da |
dc.subject.por.fl_str_mv |
structural analysis reinforced concrete design material nonlinearity geometric nonlinearity second order effects |
topic |
structural analysis reinforced concrete design material nonlinearity geometric nonlinearity second order effects |
description |
abstract: In this paper, a computational tool was developed to optimize the design of slender reinforced concrete columns subjected to biaxial bending considering the material and geometric nonlinearities rigorously. The optimization process utilizes the technique of genetic algorithms to find the best cross-sectional dimension and the best distribution and amount of reinforcement, to minimize the cost of the column subject to certain constraints of strength, stability, feasibility and regulatory. The analysis applies to rectangular cross-section of columns, and constant and symmetrical distribution of reinforcement. The results obtained by the developed software converge properly to an optimal solution or to a solution around the optimum in a significantly shorter time interval in relation to the results obtained when considering all solutions within the previously established domain. The effect of slenderness on the optimal design of reinforced concrete columns was also analyzed. The results showed that the column cost increases as the slenderness ratio increases, and steel becomes the predominant material to establish the equilibrium of the structural element. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-01-01 |
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=S1983-41952021000600204 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1983-41952021000600204 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/s1983-41952021000600010 |
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 |
IBRACON - Instituto Brasileiro do Concreto |
publisher.none.fl_str_mv |
IBRACON - Instituto Brasileiro do Concreto |
dc.source.none.fl_str_mv |
Revista IBRACON de Estruturas e Materiais v.14 n.6 2021 reponame:Revista IBRACON de Estruturas e Materiais instname:Instituto Brasileiro do Concreto (IBRACON) instacron:IBRACON |
instname_str |
Instituto Brasileiro do Concreto (IBRACON) |
instacron_str |
IBRACON |
institution |
IBRACON |
reponame_str |
Revista IBRACON de Estruturas e Materiais |
collection |
Revista IBRACON de Estruturas e Materiais |
repository.name.fl_str_mv |
Revista IBRACON de Estruturas e Materiais - Instituto Brasileiro do Concreto (IBRACON) |
repository.mail.fl_str_mv |
editores.riem@gmail.com||arlene@ibracon.org.br |
_version_ |
1754193606538690560 |