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Volume :26 Issue : 2 1999      Add To Cart                                                                    Download

Neural networks for calculation of shear strength of reinforced concrete beams

Auther : KHALDOUN N. RAHAL AND MOSTAFA ABU KIEFA

 Department of Civil Engineering, Kuwait University, P.O. Box 5969, Safat, 13060, Kuwait

 

ABSTRACT

This paper investigates the potential of using Artificial Neural Networks to predict the shear strength of longitudinally reinforced concrete beams. The experimental results from two hundreds and eighty three (283) beam tests were used to train the network to learn the relation­ship between the shear strength and four main parameters affecting it. These parameters are the concrete compressive strength, the span to depth ratio, the amount and strength of the reinforcement and the effective depth of the beams.

To check the robustness of the trained network, the calculated strength of the training data sets and another seventy (70) data sets not previously known to the network were compared with the observed strength, and very good agreement was obtained. The trained Neural Network was also used to predict the relationships between the shear strength and each of the four influencing parameters. The results agreed well with the commonly accepted knowledge of shear behavior of reinforced concrete, and the network correctly captured the effect of each of the parameters on the shear strength.

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