Investigation on Tensile and Flexural Behaviour of Fibre Reinforced Concrete Using Artificial Neural Network

The purpose of this study is to investigate the impact that using marble sludge powder as a partial replacement for cement in concrete can have. Experiments were conducted to investigate a variety of characteristics of fiber-reinforced concrete using both fresh concrete and concrete that had been allowed to solidify. In order to determine the split tensile and flexural property of FRC, two water binder ratios, such as 0.35 and 0.40, as well as percentage re-placements of 0%, 5%, 10%, 15%, 20%, and 25% of marble sludge powder and 0.5% of polypropylene 3S fibre were used. After curing for 7, 14, 28, and 56 days, the samples were put through a battery of mechanical tests to evaluate their qualities. The flexural strength and split tensile strength of the material were evaluated over the course of this investigation. In the end, an artificial neural network, also known as an ANN, was utilised in order to create a prediction model for split tensile and flexural strength. We displayed the experimentally obtained Split Tensile Strength and Flexural Strength against the regression analysis strength after 56 days for ANN. This was done so that we could compare the two. According to the findings of the experiments, using powder made from marble waste might lessen the damage that concrete causes to the environment while also providing economic benefits. In this study, dependable mechanical strength was developed by the use of a feed-forward back-propagation neural network, which consisted of eight input neurons, two hidden neurons, and one output neuron. According to the findings, it was discovered that the mechanical properties of concrete might be improved by using dry marble sludge powder as a substitute for up to 15% of the normal aggregate.