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

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, this study considers parameters such as the concrete compressive strength (f′c), the shear span-to-effective depth ratio (av/d), and reinforcement ratios (ps, pv, and ph). Introducing a novel predictive model, this study conducts a rigorous evaluation using a nonlinear regression analysis and statistical metrics (MAE, RMSE, and R2). The proposed model demonstrates a significant reduction in the coefficient of variation (CV) to 27.08%, surpassing existing codes’ limitations. Comparative analyses highlight the model’s robustness, revealing an 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 safety with the efficiency of structural systems.