Data for: Shear-Torsion-Bending Interaction in RC Beams according to NBR 6118/2014 and AASHTO LRFD 2014
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Tipo de documento: | Conjunto de dados |
Título da fonte: | SciELO Data |
Texto Completo: | https://doi.org/10.48331/scielodata.ZGNEIO |
Resumo: | Reinforced concrete beams are subjected to bending, torsion and shear simultaneously. The interaction of combined loading is complex and demands a unified model for analysis and design. Using the models from NBR 6118/2014 (variable angle truss model with parallel chords) and AASHTO LRFD Bridge Design Specifications 2014 (Modified Compression Field Theory), an algorithm was created, converting the resistance problem into a constrained optimization problem and generating an interaction surface that also displays the active constraints for each degree of interaction. Applying it to three beams previously tested, the experimental data was plotted against the surface obtained by the standards. The procedure and its optimization approach were efficient and effective in predicting the beams’ resistance. Comparison between the interaction surfaces, empirical data and existing literature showed the procedure and the standards were consistent and its application simple and practical. This dataset contains the optimization algothims and post-processing algorithms, including colormaps used for generating the surfaces and experimental data used for validation. |
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https://doi.org/10.48331/scielodata.ZGNEIOBelarmino Almeida, ViníciusData for: Shear-Torsion-Bending Interaction in RC Beams according to NBR 6118/2014 and AASHTO LRFD 2014SciELO DataReinforced concrete beams are subjected to bending, torsion and shear simultaneously. The interaction of combined loading is complex and demands a unified model for analysis and design. Using the models from NBR 6118/2014 (variable angle truss model with parallel chords) and AASHTO LRFD Bridge Design Specifications 2014 (Modified Compression Field Theory), an algorithm was created, converting the resistance problem into a constrained optimization problem and generating an interaction surface that also displays the active constraints for each degree of interaction. Applying it to three beams previously tested, the experimental data was plotted against the surface obtained by the standards. The procedure and its optimization approach were efficient and effective in predicting the beams’ resistance. Comparison between the interaction surfaces, empirical data and existing literature showed the procedure and the standards were consistent and its application simple and practical. This dataset contains the optimization algothims and post-processing algorithms, including colormaps used for generating the surfaces and experimental data used for validation.2022-03-29info:eu-repo/semantics/openAccesshttp://creativecommons.org/publicdomain/zero/1.0Engineeringreinforced concretebendingtorsionshearinteractionoptimizationNBR 6118AASHTO LRFDinfo:eu-repo/semantics/datasetinfo:eu-repo/semantics/datasetinfo:eu-repo/semantics/publishedVersionDatasetreponame:SciELO Datainstname:Scientific Electronic Library Online (SCIELO)instacron:SCIRepositório de Dados de PesquisaONGhttps://data.scielo.org/oai/requestdata@scielo.orgopendoar:2024-04-11T06:11:21SciELO Data - Scientific Electronic Library Online (SCIELO)falsedoi:10.48331/scielodata.ZGNEIO |
dc.title.none.fl_str_mv |
Data for: Shear-Torsion-Bending Interaction in RC Beams according to NBR 6118/2014 and AASHTO LRFD 2014 |
title |
Data for: Shear-Torsion-Bending Interaction in RC Beams according to NBR 6118/2014 and AASHTO LRFD 2014 |
spellingShingle |
Data for: Shear-Torsion-Bending Interaction in RC Beams according to NBR 6118/2014 and AASHTO LRFD 2014 Belarmino Almeida, Vinícius Engineering reinforced concrete bending torsion shear interaction optimization NBR 6118 AASHTO LRFD |
title_short |
Data for: Shear-Torsion-Bending Interaction in RC Beams according to NBR 6118/2014 and AASHTO LRFD 2014 |
title_full |
Data for: Shear-Torsion-Bending Interaction in RC Beams according to NBR 6118/2014 and AASHTO LRFD 2014 |
title_fullStr |
Data for: Shear-Torsion-Bending Interaction in RC Beams according to NBR 6118/2014 and AASHTO LRFD 2014 |
title_full_unstemmed |
Data for: Shear-Torsion-Bending Interaction in RC Beams according to NBR 6118/2014 and AASHTO LRFD 2014 |
title_sort |
Data for: Shear-Torsion-Bending Interaction in RC Beams according to NBR 6118/2014 and AASHTO LRFD 2014 |
author |
Belarmino Almeida, Vinícius |
author_facet |
Belarmino Almeida, Vinícius |
author_role |
author |
dc.contributor.author.fl_str_mv |
Belarmino Almeida, Vinícius |
dc.subject.none.fl_str_mv |
Engineering reinforced concrete bending torsion shear interaction optimization NBR 6118 AASHTO LRFD |
topic |
Engineering reinforced concrete bending torsion shear interaction optimization NBR 6118 AASHTO LRFD |
description |
Reinforced concrete beams are subjected to bending, torsion and shear simultaneously. The interaction of combined loading is complex and demands a unified model for analysis and design. Using the models from NBR 6118/2014 (variable angle truss model with parallel chords) and AASHTO LRFD Bridge Design Specifications 2014 (Modified Compression Field Theory), an algorithm was created, converting the resistance problem into a constrained optimization problem and generating an interaction surface that also displays the active constraints for each degree of interaction. Applying it to three beams previously tested, the experimental data was plotted against the surface obtained by the standards. The procedure and its optimization approach were efficient and effective in predicting the beams’ resistance. Comparison between the interaction surfaces, empirical data and existing literature showed the procedure and the standards were consistent and its application simple and practical. This dataset contains the optimization algothims and post-processing algorithms, including colormaps used for generating the surfaces and experimental data used for validation. |
publishDate |
2022 |
dc.date.issued.fl_str_mv |
2022-03-29 |
dc.type.openaire.fl_str_mv |
info:eu-repo/semantics/dataset |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.none.fl_str_mv |
info:eu-repo/semantics/dataset |
format |
dataset |
status_str |
publishedVersion |
dc.identifier.url.fl_str_mv |
https://doi.org/10.48331/scielodata.ZGNEIO |
url |
https://doi.org/10.48331/scielodata.ZGNEIO |
dc.rights.openaire.fl_str_mv |
info:eu-repo/semantics/openAccess http://creativecommons.org/publicdomain/zero/1.0 |
eu_rights_str_mv |
openAccess |
rights_invalid_str_mv |
http://creativecommons.org/publicdomain/zero/1.0 |
dc.format.none.fl_str_mv |
Dataset |
dc.publisher.none.fl_str_mv |
SciELO Data |
publisher.none.fl_str_mv |
SciELO Data |
dc.source.none.fl_str_mv |
reponame:SciELO Data instname:Scientific Electronic Library Online (SCIELO) instacron:SCI |
instname_str |
Scientific Electronic Library Online (SCIELO) |
instacron_str |
SCI |
institution |
SCI |
reponame_str |
SciELO Data |
collection |
SciELO Data |
repository.name.fl_str_mv |
SciELO Data - Scientific Electronic Library Online (SCIELO) |
repository.mail.fl_str_mv |
data@scielo.org |
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1797042024896004096 |