Shear Capacity Prediction of FRP Reinforced Concrete Beams Using Hybrid GMDH–GA

In recent years, the use of composite rebars in reinforced concrete structures has received much attention due to its high corrosion resistance, significant tensile strength, and appropriate non-magnetization characteristics. Due to the lower modulus of elasticity of composite rebars than steel reb...

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Autores principales:	Masoud Ahmadi, Hosein Naderpour, Pouyan Fakharian, Danial Rezazadeh Eidgahee
Formato:	article
Lenguaje:	FA
Publicado:	Iranian Society of Structrual Engineering (ISSE) 2021
Materias:	frp bar shear capacity gmdh genetic algorithm empirical model Bridge engineering TG1-470 Building construction TH1-9745
Acceso en línea:	https://doaj.org/article/375309aa72df4d5681e6bb22de00b0af
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id	oai:doaj.org-article:375309aa72df4d5681e6bb22de00b0af
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spelling	oai:doaj.org-article:375309aa72df4d5681e6bb22de00b0af2021-11-08T15:55:01ZShear Capacity Prediction of FRP Reinforced Concrete Beams Using Hybrid GMDH–GA2476-39772538-261610.22065/jsce.2021.284971.2445https://doaj.org/article/375309aa72df4d5681e6bb22de00b0af2021-08-01T00:00:00Zhttps://www.jsce.ir/article_134566_b3f8cbe3be2494f66dada04088631375.pdfhttps://doaj.org/toc/2476-3977https://doaj.org/toc/2538-2616In recent years, the use of composite rebars in reinforced concrete structures has received much attention due to its high corrosion resistance, significant tensile strength, and appropriate non-magnetization characteristics. Due to the lower modulus of elasticity of composite rebars than steel rebars, concrete beams reinforced with composite rebars have relatively lower shear strength compared to beams reinforced with steel rebars. On the other hand, shear failure in concrete beams reinforced with composite rebars is generally brittle and requires accurate prediction of the behavior of these members. Therefore, in this study, the shear strength of concrete beams reinforced with composite rebars is predicted using a combination of GMDH type neural networks and genetic algorithms based on a wide range of experimental results. The key effective parameters that consider in this study are the width of the web, effective depth of the beam, shear span to depth ratio, concrete compressive strength, modulus of elasticity of FRP longitudinal bars, and longitudinal reinforcement ratio. The accuracy of the proposed method has been verified by comparing the model predictions with the collected experimental results and existing shear design equations. The results show that the proposed model has more accurate results in calculating the shear strength of concrete beams than other existing relationships. A sensitivity analysis is also performed to assess the effect of the input parameters on the shear strength of FRP-reinforced concrete beams.Masoud AhmadiHosein NaderpourPouyan FakharianDanial Rezazadeh EidgaheeIranian Society of Structrual Engineering (ISSE)articlefrp barshear capacitygmdhgenetic algorithmempirical modelBridge engineeringTG1-470Building constructionTH1-9745FAJournal of Structural and Construction Engineering, Vol 8, Iss 6, Pp 24-42 (2021)
institution	DOAJ
collection	DOAJ
language	FA
topic	frp bar shear capacity gmdh genetic algorithm empirical model Bridge engineering TG1-470 Building construction TH1-9745
spellingShingle	frp bar shear capacity gmdh genetic algorithm empirical model Bridge engineering TG1-470 Building construction TH1-9745 Masoud Ahmadi Hosein Naderpour Pouyan Fakharian Danial Rezazadeh Eidgahee Shear Capacity Prediction of FRP Reinforced Concrete Beams Using Hybrid GMDH–GA
description	In recent years, the use of composite rebars in reinforced concrete structures has received much attention due to its high corrosion resistance, significant tensile strength, and appropriate non-magnetization characteristics. Due to the lower modulus of elasticity of composite rebars than steel rebars, concrete beams reinforced with composite rebars have relatively lower shear strength compared to beams reinforced with steel rebars. On the other hand, shear failure in concrete beams reinforced with composite rebars is generally brittle and requires accurate prediction of the behavior of these members. Therefore, in this study, the shear strength of concrete beams reinforced with composite rebars is predicted using a combination of GMDH type neural networks and genetic algorithms based on a wide range of experimental results. The key effective parameters that consider in this study are the width of the web, effective depth of the beam, shear span to depth ratio, concrete compressive strength, modulus of elasticity of FRP longitudinal bars, and longitudinal reinforcement ratio. The accuracy of the proposed method has been verified by comparing the model predictions with the collected experimental results and existing shear design equations. The results show that the proposed model has more accurate results in calculating the shear strength of concrete beams than other existing relationships. A sensitivity analysis is also performed to assess the effect of the input parameters on the shear strength of FRP-reinforced concrete beams.
format	article
author	Masoud Ahmadi Hosein Naderpour Pouyan Fakharian Danial Rezazadeh Eidgahee
author_facet	Masoud Ahmadi Hosein Naderpour Pouyan Fakharian Danial Rezazadeh Eidgahee
author_sort	Masoud Ahmadi
title	Shear Capacity Prediction of FRP Reinforced Concrete Beams Using Hybrid GMDH–GA
title_short	Shear Capacity Prediction of FRP Reinforced Concrete Beams Using Hybrid GMDH–GA
title_full	Shear Capacity Prediction of FRP Reinforced Concrete Beams Using Hybrid GMDH–GA
title_fullStr	Shear Capacity Prediction of FRP Reinforced Concrete Beams Using Hybrid GMDH–GA
title_full_unstemmed	Shear Capacity Prediction of FRP Reinforced Concrete Beams Using Hybrid GMDH–GA
title_sort	shear capacity prediction of frp reinforced concrete beams using hybrid gmdh–ga
publisher	Iranian Society of Structrual Engineering (ISSE)
publishDate	2021
url	https://doaj.org/article/375309aa72df4d5681e6bb22de00b0af
work_keys_str_mv	AT masoudahmadi shearcapacitypredictionoffrpreinforcedconcretebeamsusinghybridgmdhga AT hoseinnaderpour shearcapacitypredictionoffrpreinforcedconcretebeamsusinghybridgmdhga AT pouyanfakharian shearcapacitypredictionoffrpreinforcedconcretebeamsusinghybridgmdhga AT danialrezazadeheidgahee shearcapacitypredictionoffrpreinforcedconcretebeamsusinghybridgmdhga
_version_	1718441557634318336

Shear Capacity Prediction of FRP Reinforced Concrete Beams Using Hybrid GMDH–GA

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