Flexural Strength Prediction of Welded Flange Plate Connections Based on Slenderness Ratios of Beam Elements Using ANN
The present study was aimed to investigate the strength and ductility of welded flange plate (WFP) connections. Using the FE method, 52 WFP connections with different beam overall depths and beam flanges/web slenderness ratios were analyzed. Fragility curves indicated that, for a WFP connection whic...
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2018-01-01
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Series: | Advances in Civil Engineering |
Online Access: | http://dx.doi.org/10.1155/2018/8059190 |
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doaj-343a3b3234b74bcc8b133b16a56bb1262020-11-24T23:01:33ZengHindawi LimitedAdvances in Civil Engineering1687-80861687-80942018-01-01201810.1155/2018/80591908059190Flexural Strength Prediction of Welded Flange Plate Connections Based on Slenderness Ratios of Beam Elements Using ANNAmir A. Hedayat0Ehsan Jazebi1Saman AsadAbadi2Amin Iranpour3Department of Civil Engineering, Islamic Azad University, Kerman Branch, Kerman, IranDepartment of Civil Engineering, Shahid Bahonar University of Kerman, Kerman, IranDepartment of Civil Engineering, Rafsanjan Vali-e-Asr University, Rafsanjan, IranPars Sustainable Seismic Structures Co., Kerman, IranThe present study was aimed to investigate the strength and ductility of welded flange plate (WFP) connections. Using the FE method, 52 WFP connections with different beam overall depths and beam flanges/web slenderness ratios were analyzed. Fragility curves indicated that, for a WFP connection which is designed based on the seismic codes, its strength is of more concern than its ductility. In addition, limiting the width-to-thickness ratios of the beam flanges and web plates to 0.3E/fy and 2.45E/fy, respectively, may not always lead to the achievement of adequate connection’s strength and ductility. Proposed theoretical formulas and artificial neural network- (ANN-) based models developed in this study were able to adequately predict the connection strength.http://dx.doi.org/10.1155/2018/8059190 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Amir A. Hedayat Ehsan Jazebi Saman AsadAbadi Amin Iranpour |
spellingShingle |
Amir A. Hedayat Ehsan Jazebi Saman AsadAbadi Amin Iranpour Flexural Strength Prediction of Welded Flange Plate Connections Based on Slenderness Ratios of Beam Elements Using ANN Advances in Civil Engineering |
author_facet |
Amir A. Hedayat Ehsan Jazebi Saman AsadAbadi Amin Iranpour |
author_sort |
Amir A. Hedayat |
title |
Flexural Strength Prediction of Welded Flange Plate Connections Based on Slenderness Ratios of Beam Elements Using ANN |
title_short |
Flexural Strength Prediction of Welded Flange Plate Connections Based on Slenderness Ratios of Beam Elements Using ANN |
title_full |
Flexural Strength Prediction of Welded Flange Plate Connections Based on Slenderness Ratios of Beam Elements Using ANN |
title_fullStr |
Flexural Strength Prediction of Welded Flange Plate Connections Based on Slenderness Ratios of Beam Elements Using ANN |
title_full_unstemmed |
Flexural Strength Prediction of Welded Flange Plate Connections Based on Slenderness Ratios of Beam Elements Using ANN |
title_sort |
flexural strength prediction of welded flange plate connections based on slenderness ratios of beam elements using ann |
publisher |
Hindawi Limited |
series |
Advances in Civil Engineering |
issn |
1687-8086 1687-8094 |
publishDate |
2018-01-01 |
description |
The present study was aimed to investigate the strength and ductility of welded flange plate (WFP) connections. Using the FE method, 52 WFP connections with different beam overall depths and beam flanges/web slenderness ratios were analyzed. Fragility curves indicated that, for a WFP connection which is designed based on the seismic codes, its strength is of more concern than its ductility. In addition, limiting the width-to-thickness ratios of the beam flanges and web plates to 0.3E/fy and 2.45E/fy, respectively, may not always lead to the achievement of adequate connection’s strength and ductility. Proposed theoretical formulas and artificial neural network- (ANN-) based models developed in this study were able to adequately predict the connection strength. |
url |
http://dx.doi.org/10.1155/2018/8059190 |
work_keys_str_mv |
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