Prediction of Ultimate Shear Strength of Deep Beams Using Neural Networks

Abstract

This study investigates the feasibility of using neural networks to evaluate the ultimate strength of deep reinforced concrete beams in shear. A neural network is an information processing system whose architecture essentially mimics the biological system of the brain. The neural network is particularly useful for evaluating systems with a multitude of nonlinear variables as in this study, where the critical factors include the strength of the concrete, the beam geometry, and the steel reinforcement in the beam. No predefined mathematical relationship between the variables in assumed. Instead, the neural network learns by example patterns obtained from published experimental data of concrete beams tested to failure. Details of the neural network predictions were more reliable than predictions using other conventional methods