Predictive model to the bond strength of FRP-to-concrete under direct pullout using gene expression programming

Gene expression programming (GEP) is used in this research to develop an empirical model that predicts the bond strength between the concrete surface and carbon fiber reinforced polymer (CFRP) sheets under direct pull out. Therefore, a large and reliable database containing 770 test specimens is co...

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Main Authors: Yasmin Murad, Ahmed Ashteyat, Rozan Hunaifat
Format: Article
Language:English
Published: Vilnius Gediminas Technical University 2019-08-01
Series:Journal of Civil Engineering and Management
Subjects:
FRP
Online Access:https://mma.vgtu.lt/index.php/JCEM/article/view/10798
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spelling doaj-43b199bee41f4209afc795927ea1f1532021-07-02T06:12:50ZengVilnius Gediminas Technical UniversityJournal of Civil Engineering and Management1392-37301822-36052019-08-0110.3846/jcem.2019.10798Predictive model to the bond strength of FRP-to-concrete under direct pullout using gene expression programmingYasmin Murad0Ahmed Ashteyat1Rozan Hunaifat2University of Jordan, Queen Rania str., Amman, JordanUniversity of Jordan, Queen Rania str., Amman, JordanUniversity of Jordan, Queen Rania str., Amman, Jordan Gene expression programming (GEP) is used in this research to develop an empirical model that predicts the bond strength between the concrete surface and carbon fiber reinforced polymer (CFRP) sheets under direct pull out. Therefore, a large and reliable database containing 770 test specimens is collected from the literature. The gene expression programming model is developed using eight parameters that predominantly control the bond strength. These parameters are concrete compressive strength, maximum aggregate size, fiber reinforced polymer (FRP) tensile strength, FRP thickness, FRP modulus of elasticity, adhesive tensile strength, FRP length, and FRP width. The model is validated using the experimental results and a statistical assessment is implemented to evaluate the performance of the proposed GEP model. Furthermore, the predicted bond results, obtained using the GEP model, are compared to the results obtained from several analytical models available in the literature and a parametric study is conducted to further ensure the consistency of the model by checking the trends between the input parameters and the predicted bond strength. The proposed model can reasonably predict the bond strength that is most fitting to the experimental database compared to the analytical models and the trends of the GEP model are in agreement with the overall trends of the analytical models and experimental tests. First published online 30 August 2019 https://mma.vgtu.lt/index.php/JCEM/article/view/10798bond strengthgene expression programmingFRPconcretelarge data base
collection DOAJ
language English
format Article
sources DOAJ
author Yasmin Murad
Ahmed Ashteyat
Rozan Hunaifat
spellingShingle Yasmin Murad
Ahmed Ashteyat
Rozan Hunaifat
Predictive model to the bond strength of FRP-to-concrete under direct pullout using gene expression programming
Journal of Civil Engineering and Management
bond strength
gene expression programming
FRP
concrete
large data base
author_facet Yasmin Murad
Ahmed Ashteyat
Rozan Hunaifat
author_sort Yasmin Murad
title Predictive model to the bond strength of FRP-to-concrete under direct pullout using gene expression programming
title_short Predictive model to the bond strength of FRP-to-concrete under direct pullout using gene expression programming
title_full Predictive model to the bond strength of FRP-to-concrete under direct pullout using gene expression programming
title_fullStr Predictive model to the bond strength of FRP-to-concrete under direct pullout using gene expression programming
title_full_unstemmed Predictive model to the bond strength of FRP-to-concrete under direct pullout using gene expression programming
title_sort predictive model to the bond strength of frp-to-concrete under direct pullout using gene expression programming
publisher Vilnius Gediminas Technical University
series Journal of Civil Engineering and Management
issn 1392-3730
1822-3605
publishDate 2019-08-01
description Gene expression programming (GEP) is used in this research to develop an empirical model that predicts the bond strength between the concrete surface and carbon fiber reinforced polymer (CFRP) sheets under direct pull out. Therefore, a large and reliable database containing 770 test specimens is collected from the literature. The gene expression programming model is developed using eight parameters that predominantly control the bond strength. These parameters are concrete compressive strength, maximum aggregate size, fiber reinforced polymer (FRP) tensile strength, FRP thickness, FRP modulus of elasticity, adhesive tensile strength, FRP length, and FRP width. The model is validated using the experimental results and a statistical assessment is implemented to evaluate the performance of the proposed GEP model. Furthermore, the predicted bond results, obtained using the GEP model, are compared to the results obtained from several analytical models available in the literature and a parametric study is conducted to further ensure the consistency of the model by checking the trends between the input parameters and the predicted bond strength. The proposed model can reasonably predict the bond strength that is most fitting to the experimental database compared to the analytical models and the trends of the GEP model are in agreement with the overall trends of the analytical models and experimental tests. First published online 30 August 2019
topic bond strength
gene expression programming
FRP
concrete
large data base
url https://mma.vgtu.lt/index.php/JCEM/article/view/10798
work_keys_str_mv AT yasminmurad predictivemodeltothebondstrengthoffrptoconcreteunderdirectpulloutusinggeneexpressionprogramming
AT ahmedashteyat predictivemodeltothebondstrengthoffrptoconcreteunderdirectpulloutusinggeneexpressionprogramming
AT rozanhunaifat predictivemodeltothebondstrengthoffrptoconcreteunderdirectpulloutusinggeneexpressionprogramming
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