Shear strength estimation of RC deep beams using the ANN and strut-and-tie approaches

Yavuz, Günnur

doi:10.12989/sem.2016.57.4.657

Cited by 11 publications

(6 citation statements)

References 15 publications

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“…Kaya [16] determined the optimum horizontal and vertical reinforcement diameters of five different beams by using genetic algorithms due to the opening/height ratio, loading condition and the presence of spaces in the body. Yavuz [17] investigated the efficiency of artificial neural networks (ANNs) in predicting the shear strength of RC deep beams. He developed an ANN model using experimental data for deep beams from an existing literature database.…”

Section: Smith and Vantsiotismentioning

confidence: 99%

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Analysis of RC Deep Beams Considering the Shear Deformations and Bar-concrete Interaction

Hashemi¹,

Sadeghi²,

Javidi³

et al. 2020

Period. Polytech. Civil Eng.

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In this paper, reinforced concrete (RC) deep beams (DBs) have been analyzed numerically and a new approach is proposed to the nonlinear numerical modeling of such structural members. The effect of shear deformations and the interaction between reinforcing steel bar and concrete are considered in modeling and analysis. In order to consider the effect of shear deformations, the Timoshenko beam theory has been applied to formulate the analysis method. In the modeling, the RC DB is divided into several sub-elements which are composed of concrete and reinforcing steel bars. Individual degrees of freedom have been assigned to each reinforcing steel bar. Thus, each reinforcing steel bar is able to slip relative to its surrounding concrete and the bond effect is simulated by nonlinear springs. To consider the interaction between reinforcing steel bar and concrete, the concrete segment acts as a beam element, and each reinforcing steel bar acts as a truss element. The reliability of this method has been confirmed by comparing the obtained results from the numerical analysis and the results of the experimental pushover test.

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Section: Smith and Vantsiotismentioning

confidence: 99%

“…Thus, it can be written in the form of Eq. (17). (17) where K represents the RC element stiffness matrix, Q represents the resisting force vector of the element, K B and K b represent the element and bond contributions to the stiffness matrix, respectively.…”

mentioning

confidence: 99%

Analysis of RC Deep Beams Considering the Shear Deformations and Bar-concrete Interaction

Hashemi¹,

Sadeghi²,

Javidi³

et al. 2020

Period. Polytech. Civil Eng.

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“…Concrete compressive strength, the provided top/bottom reinforcements, and web reinforcements in terms of amount and spacing all form the shear resistance of these deep beams [1,2,4,5]. In literature, plenty of analytical and numerical studies have been focused on the ultimate shear strength assessment of such beams with large depths compared to their spans [2,3,[6][7][8][9]. Unavoidable discrepancies were found with the implementation of both analytical/numerical methods compared to the experimental results [4].…”

Section: Introductionmentioning

confidence: 99%

Shear Strength Estimation of Reinforced Concrete Deep Beams Using a Novel Hybrid Metaheuristic Optimized SVR Models

et al. 2022

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This study looks to propose a hybrid soft computing approach that can be used to accurately estimate the shear strength of reinforced concrete (RC) deep beams. Support vector regression (SVR) is integrated with three novel metaheuristic optimization algorithms: African Vultures optimization algorithm (AVOA), particle swarm optimization (PSO), and Harris Hawks optimization (HHO). The proposed models, SVR-AVOA, -PSO, and -HHO, are designed and compared to reference existing models. Multi variables are used and evaluated to model and evaluate the deep beam’s shear strength, and the sensitivity of the selected variables in modeling the shear strength is assessed. The results indicate that the SVR-AVOA outperforms other proposed and existing models for the shear strength prediction. The mean absolute error of SVR-AVOA, SVR-PSO, and SVR-HHO are 43.17 kN, 44.09 kN, and 106.95 kN, respectively. The SVR-AVOA can be used as a soft computing technique to estimate the shear strength of the RC deep beam with a maximum error of ±3.39%. Furthermore, the sensitivity analysis shows that the deep beam’s key parameters (shear span to depth ratio, web reinforcement’s yield strength, concrete compressive strength, stirrups spacing, and the main longitudinal bars reinforcement ratio) are efficiently impacted in the shear strength detection of RC deep beam.

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“…Failure in ductility was more likely to occur with an increase in shear span to depth ratio and a decrease in longitudinal reinforcement. Yavuz (2016) took a different approach to investigating STM by calculating the shear strength of an RC deep beam with artificial neural networks (ANNs). Using different parameters affecting shear taken from experimental statistics and the literature database, they concluded that the ANN approach is better for predicting shear strength when compared to STM.…”

Section: Introductionmentioning

confidence: 99%

Modified Strut and Tie Method and Truss Reinforcement for Shear Strengthening of Reinforced Concrete Deep Beams

Harsha¹,

Poluraju²

2021

IJTech

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The aim of this study was to evaluate and test the limitations of the Indian Standard code 456-2000 related to deep beams, given that the code does not have any provisions regarding the use of the strut and tie method (STM)of design. This study validates the use of truss reinforcement and STM-shaped reinforcements as alternatives to STM design. We conclude that horizontal web reinforcement has a greater impact than vertical shear reinforcement. Deep beams with truss reinforcement and STM-based reinforcement were shown to have the highest shear strength capacity of all the deep beams. In the present study, 21 deep beams were cast and used to analyze their shear and flexural behavior. The specimens were divided into four groups based on length, width and depth, percentage of tension reinforcement, and percentage of horizontal and vertical shear reinforcement. The results revealed that truss-type reinforcement configuration is stronger than vertical shear reinforcement, as the former can resist 20% more load than the latter.

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Shear strength estimation of RC deep beams using the ANN and strut-and-tie approaches

Cited by 11 publications

References 15 publications

Analysis of RC Deep Beams Considering the Shear Deformations and Bar-concrete Interaction

Analysis of RC Deep Beams Considering the Shear Deformations and Bar-concrete Interaction

Shear Strength Estimation of Reinforced Concrete Deep Beams Using a Novel Hybrid Metaheuristic Optimized SVR Models

Modified Strut and Tie Method and Truss Reinforcement for Shear Strengthening of Reinforced Concrete Deep Beams

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