Effect of Stirrups on the Contribution of Concrete Compressive Strength and Tensile Steel to the Shear Strength of RC Beams Using Artificial Neural Networks

Current shear design procedures calculate the nominal shear capacity, V_n of reinforced concrete (RC) slender beams with shear reinforcement (stirrups) by simply superimposing the shear capacity carried by concrete, V_c to that carried by stirrups, V_s. Previous studies concluded that current shear design equations do not only underestimate the resistance of concrete to shear, they also assume that the addition of stirrups does not alter the shear behaviour of RC slender beams. The addition of stirrups is known to provide confinement to concrete and therefore enhances the contribution of basic shear mechanisms to V_c. Current shear design provisions are yet to account for such enhancement and they simply calculate concrete contribution to V_n assuming that stirrups do not exist. In this paper, a previously developed artificial neural network (ANN) model trained on shear database of normal and high-strength concrete beams was used to investigate the effect of stirrups on the contribution of several basic shear design parameters to the overall shear capacity of RC beams. A sensitivity analysis was also carried out to evaluate the performance of several existing shear provisions in calculating the nominal shear capacity of reinforced concrete slender beams.