Extracting Knowledge of Concrete Shear Strength from Artificial Neural Networks - Young, William A; Weckman, Gary R; Brown, Michael D; Thompson, Jim (International Journal of Industrial Engineering: Theory, Applications and Practice, 2022)
This article introduces an artificial neural network (ANN) to estimate the shear strength of reinforced concrete beams. Current methods for calculating shear strength use a model that is based on engineering mechanics and empirical values determined though testing of a beam failing due to shear. The current methods are intended to provide a conservative lower bound on the strength needed to prevent a shear failure. A database containing the results of over 1200 laboratory shear strength tests was used to train an ANN. The database contained the geometric and material property data from the test specimens and the recorded failure load. The ANN presented in this paper was able to predict the shear strength of reinforced concrete beams more accurately than the current approach. The ANN provides additional insight on the parameters that are most significant in estimating concrete shear strength, which may lead to a better understanding of the mechanism of shear failure.