Predictive Model to the Bond Strength of FRP-to-Concrete Under Direct Pullout Using Gene Expression Programming

Murad, Yasmin; Ashteyat, Ahmed M.; Hunaifat, Rozan

doi:10.3846/jcem.2019.10798

Cited by 35 publications

(6 citation statements)

References 54 publications

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“…Murad [31] also proposed a GEP model to estimate the compressive strength of concrete modified with nanomaterials where code guidelines are lacking in these three cases. Several researchers [10,14,[32][33][34][35][36][37][38][39][40][41] have proved that GEP is a powerful tool for creating accurate models for solving various problems in the civil engineering field.…”

Section: Overview Of Gene Expression Programmingmentioning

confidence: 99%

Shear Strength Prediction of Concrete Beams Reinforced with FRP Bars and Stirrups Using Gene Expression Programming

et al. 2023

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Existing reinforced concrete (RC) structures in humid regions suffer from deterioration due to the corrosion of ordinary reinforcement bars damaging the whole system. The deterioration of the transverse reinforcement leads to shear failure, which is one of the most dangerous failure modes. Therefore, researchers suggested using fiber-reinforced polymer (FRP) bars as a replacement for reinforcement bars in humid regions to integrate sustainability and improve their serviceability and durability. A simple model that can accurately estimate the shear strength of concrete beams designed with FRP longitudinal bars and stirrups is lacking. This research proposed a simplified Gene expression programming (GEP) based model to estimate the shear strength of FRP concrete beams. Seven parameters that principally dominate the shear behavior of FRP beams were utilized to create the GEP model. The parameters are the beam width, beam depth, concrete compressive strength, FRP tensile longitudinal reinforcement ratio, area of stirrups, spacing between the stirrups, and the ultimate FRP strength of stirrups. A comparison was made between the GEP and ACI-440 models; the R2 values of the total database were 92% and 54% for the GEP and ACI models, respectively. The R2 of the GEP model is considerably higher than that measured for the ACI model, and the errors of the GEP model are low, which affirms that the GEP is superior to the ACI model in estimating the shear strength of FRP beams. The trends of the GEP and ACI-440 models and the empirical results are similar, confirming the GEP model’s consistency. Using the GEP model to estimate the shear strength of concrete beams designed with FRP longitudinal bars and stirrups is recommended.

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Section: Overview Of Gene Expression Programmingmentioning

confidence: 99%

Shear Strength Prediction of Concrete Beams Reinforced with FRP Bars and Stirrups Using Gene Expression Programming

et al. 2023

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“…Gandomi et al (2014) predict the shear strength of slender RC beams using gene expression programing. Murad et al (2019a) proposed a GEP model to predict the bond strength of FRP-to-concrete under direct pullout.…”

Section: Overview Of Genetic Programmingmentioning

confidence: 99%

Compressive Strength Prediction of Lightweight Short Columns at Elevated Temperature Using Gene Expression Programing and Artificial Neural Network

Ashteyat

Obaidat

Murad

et al. 2020

Journal of Civil Engineering and Management

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The experimental behavior of reinforced concrete elements exposed to fire is limited in the literature. Although there are few experimental programs that investigate the behavior of lightweight short columns, there is still a lack of formulation that can accurately predict their ultimate load at elevated temperature. Thus, new equations are proposed in this study to predict the compressive strength of the lightweight short column using Gene Expression Programming (GEP) and Artificial neural networks (ANN). A total of 83 data set is used to establish GEP and ANN models where 70% of the data are used for training and 30% of the data are used for validation and testing. The predicting variables are temperature, concrete compressive strength, steel yield strength, and spacing between stirrups. The developed models are compared with the ACI equation for short columns. The results have shown that the GEP and ANN models have a strong potential to predict the compressive strength of the lightweight short column. The predicted compressive strengths of short lightweight columns using the GEP and ANN models are closer to the experimental results than that obtained using the ACI equations.

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“…These fibres are a viable alternative to reinforcing steel structures and are also employed in the manufacturing of continuous fibres (Yap et al, 2014). The process of fracture in FC is a multi-scale process, beginning with the initiation and propagation of micro-cracks and progressing all the way up to macro-cracks (Murad et al, 2019;Al-Faqra et al, 2021). The inclusion of synthetic fibres that have a diameter that is on the smaller side and an aspect ratio that is on the larger side has a greater impact on limiting the initiation, extension, and coalescence of micro-cracks that occur as a result of stress.…”

Section: Introductionmentioning

confidence: 99%

Mechanical, durability and thermal properties of foamed concrete reinforced with synthetic twisted bundle macro-fibers

et al. 2023

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The use of foamed concrete (FC) in the construction sector has been rapidly growing over the past few years as a result of the several advantages it possesses in comparison to traditional high-strength concrete. FC, on the other hand, suffers from a number of deficiencies, such as brittleness, limited ductility, high porosity, excessive drying shrinkage, little resistance to cracking and deformation. To improve the tensile strength and fracture resistance of FC, engineers usually opt for steel fibre or polymer fibre as the reinforcement material of choice. Hence this research aims to investigate the potential utilization of synthetic twisted bundle macro-fibers (SF) in FC to enhance its durability, mechanical and thermal properties. The SF were included in the FC in varied amounts of weight fractions, including 0%, 1%, 2%, 3%, 4%, and 5% respectively. FC was produced at three low densities, precisely 1,000, 1,300, and 1,600 kg/m3, which were all prepared. Compression, flexural, splitting tensile, flow table, porosity, water absorption and thermal conductivity tests were conducted to establish the thermal, mechanical and durability properties of SF-reinforced FC. The findings imply that the integration of SF into FC results in a significant enhancement of the material’s strength and thermal conductivity properties while simultaneously lowering the material’s capacity for water absorption and porosity. For the purpose of improving the material’s mechanical, durability and thermal properties, the weight percentage of SF that was ideal ranged from 3% to 4%. The incorporation of SF into FC resulted in a rise in the material’s ductility, and the specimens maintained their integrity from the loading stage to failure. The SF is able to lessen the cracks that were already present in the FC and prevent the formation of additional cracks in the FC.

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Predictive Model to the Bond Strength of FRP-to-Concrete Under Direct Pullout Using Gene Expression Programming

Cited by 35 publications

References 54 publications

Shear Strength Prediction of Concrete Beams Reinforced with FRP Bars and Stirrups Using Gene Expression Programming

Shear Strength Prediction of Concrete Beams Reinforced with FRP Bars and Stirrups Using Gene Expression Programming

Compressive Strength Prediction of Lightweight Short Columns at Elevated Temperature Using Gene Expression Programing and Artificial Neural Network

Mechanical, durability and thermal properties of foamed concrete reinforced with synthetic twisted bundle macro-fibers

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