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Modelling the hardened properties of steel fiber reinforced concrete using ANN

Publication Type : Journal Article

Source : Materials Today: Proceedings 49, 2081-2089, 2021

Url : https://www.sciencedirect.com/science/article/pii/S2214785321057564

Keywords : Steel fiber reinforced concrete, Elastic modulus, Compressive Strength

Campus : Coimbatore

School : School of Engineering

Department : Civil

Verified : No

Year : 2021

Abstract : The hardened properties of concrete are one of the most important parameters when considering the sustainability criteria of buildings. Numerous previous studies have established how the Artificial Neural Network is used as an effective statistical data modelling tool. In this study, the prediction of Elastic modulus and Compressive Strength of steel fibre reinforced concrete have been illustrated with a feed-forward backpropagation neural network structure. 158 datasets are used for modelling of elastic modulus and 140 datasets is used for modelling of Compressive Strength. The developed ANN models were able to predict the data within the range of input parameters considered and were having regression coefficients values of 0.96 and 0.97 respectively. A comparison of actual and predicted values has been performed and the results indicated that the ANN performed better in terms of prediction with minimum deviation from original data.

Cite this Research Publication : RR Mahesh, D Sathyan, "Modelling the hardened properties of steel fiber reinforced concrete using ANN", Materials Today: Proceedings 49, 2081-2089, 2021

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