Evaluation of Shear Reinforcement Design Limits in High-Strength Concrete Beams

Aguilar, Gerardo; Villamizar, Sandra; Ramírez, Julio A.

doi:10.14359/51701132

Cited by 10 publications

(9 citation statements)

References 5 publications

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“…The dataset of the current study, generated from 15 literature references [10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25], consists of 198 simply supported RC deep beam subjected to shear testing. The main variables that imported from these tests including concrete compressive strength (fc'), shear span-to-depth ratio (av/d), web width (bw), ratios of longitudinal (Ps), vertical (Pv), and horizontal (Ph) reinforcement, depth (d), yield strength of vertical stirrups (fyv), and the concrete area (web width × depth (bw×d)), as presented in Table 1.…”

Section: Existing Experimental Investigationsmentioning

confidence: 99%

“…This study offers a thorough examination of deep beams, taking into account pivotal factors that influence the concrete compressive strength (fc'), shear span-to-depth ratio (av/d), web width (bw), ratios of longitudinal (Ps), vertical (Pv), and horizontal (Ph) reinforcement, depth (d), yield strength of vertical stirrups (fyv), and the concrete area (web width × depth (bw×d)). The assessment relies on an extensive dataset comprising 198 deep beams sourced from 15 investigations [10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25]. These studies were chosen for their detailed information on test conditions and material properties, thus forming a robust database conducive to scrutinizing code provisions and affirming the proposed predictive model.…”

Section: Introductionmentioning

confidence: 99%

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Comprehensive Empirical Modeling of Shear Strength Prediction in Reinforced Concrete Deep Beams

Sayhood,

Mohammed,

Hilo

et al. 2024

Preprint

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This paper presents a thorough investigation into the shear strength capacity of reinforced concrete deep beams, with a focus on improving predictive accuracy beyond existing code provisions. Analyzing 198 deep beams from 15 investigations, the study considers parameters such as concrete compressive strength (fc’), shear span to effective depth ratio (av/d), and reinforcement ratios (ρs, ρv, ρh ). Introducing a novel predictive model (Equation 7), the study rigorously evaluates it using nonlinear regression analysis and statistical metrics (MAE, RMSE, R2). The proposed model demonstrates a significant reduction in the coefficient of variation (COV) to 27.08%, surpassing existing codes' limitations. Comparative analyses highlight the model's robustness, revealing improved convergence of data points and minimal sensitivity to variations in key parameters. The findings suggest that the proposed model offers enhanced predictive accuracy across diverse scenarios, making it a valuable tool for structural engineers. This research contributes to advancing the understanding of shear strength in reinforced concrete deep beams, offering a reliable and versatile predictive model with implications for refining design methodologies and enhancing the safety and efficiency of structural systems.

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Section: Existing Experimental Investigationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Comprehensive Empirical Modeling of Shear Strength Prediction in Reinforced Concrete Deep Beams

Sayhood,

Mohammed,

Hilo

et al. 2024

Preprint

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“…A database containing 271 sample data (80% for training and 20% for testing) with 16 different input parameters was considered by the researchers for developing the new models. Sample data were collected from different published experimental results available in the literature by the researchers [18,[93][94][95][96][97][98][99][100][101]. To avoid the scale effect, researchers normalized the input parameters to the range 0-1.…”

Section: Mohammed and Ismailmentioning

confidence: 99%

Shear strength prediction of reinforced concrete beams using machine learning

et al. 2023

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“…Over the decades, several researchers have studied the behaviour of deep RC beams and proposed many design models and empirical formulas, including the STM [5][6][7]. The STM-based methodology was then included in several international codes of practice for the design and analysis of deep RC beams as it represents the actual load-carrying mechanism of deep beams more appropriately at failure [8,9].…”

Section: Introductionmentioning

confidence: 99%

Strength prediction of a bottle-shaped strut for evaluating the shear capacity of reinforced concrete deep beam

Kumar

Jangid

2023

Eng. Res. Express

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For the analysis and design of reinforced concrete (RC) deep beams, the strut-and-tie model is typically employed to simulate the flow of stresses. A bottle-shaped strut develops between the loading point and support, in which compressive stress spreads laterally and induces tensile strain in the transverse direction, which reduces the compressive strength of the strut significantly. Web reinforcements are provided in deep RC beams to prevent splitting of the diagonal strut due to the presence of these transverse strains. In this article, a simplified design procedure based on the strut-and-tie model (STM) is proposed for the evaluation of the shear capacity of deep beams with web reinforcement. The suggested model is based on modified compression field theory and considers the impact of shear reinforcement ratio, transverse tensile strain, post-cracking strength of concrete, and the actual dispersion of compressive stress based on strut geometry (aspect ratio) for strength prediction of bottle-shaped struts. The experimental results of RC panels and deep RC beams reported in the literature are used to validate the results of the suggested model. The findings demonstrate that the proposed STM evaluates the shear capacity of deep RC beams more precisely than capacities estimated by ACI 318-19, AASHTO LRDF, and Eurocode 2 (EC2). In addition, a comprehensive parametric study has been carried out to investigate the effect of various design parameters on the shear capacity of deep RC beams.

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Evaluation of Shear Reinforcement Design Limits in High-Strength Concrete Beams

Cited by 10 publications

References 5 publications

Comprehensive Empirical Modeling of Shear Strength Prediction in Reinforced Concrete Deep Beams

Comprehensive Empirical Modeling of Shear Strength Prediction in Reinforced Concrete Deep Beams

Shear strength prediction of reinforced concrete beams using machine learning

Strength prediction of a bottle-shaped strut for evaluating the shear capacity of reinforced concrete deep beam

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