Shear strength evaluation of reinforced recycled aggregate concrete beams

A theoretical study is conducted to investigate the shear behaviour of recycled aggregate concrete (RAC) beams with and without shear reinforcements along with the performance evaluation various Code based/other existing equations in predicting shear strength. In addition, three artificial neural network (ANN) models for shear strength prediction of RAC beams with and without shear reinforcements are developed and their performance validated by using 108 beams from available research studies. Most of the Codes and existing methods underestimate the shear capacity of RAC beams with/without shear reinforcement. However, over estimation of shear strength by Codes/existing methods for about 10% RAC beams needs to be addressed when using such Codes/existing methods for shear strength prediction. All three ANN models are found to predict shear strength of RAC beams. Developed ANN models are able to simulate the effect of shear reinforcement on the shear strength of RAC beams.