The present work deals with investigating the effect of marble sludge powder on partially replacing cement in concrete. Various properties of fibre-reinforced concrete were examined experimentally with fresh concrete and hardened concrete. Two water binder ratios were selected, such as 0.35 and 0.40, and percentage replacements of 0, 5, 10, 15, 20, and 25% of marble sludge powder (MSP) and 0.5% of polypropylene 3S fibre were selected to find out the mechanical properties of FRC. The samples were tested after curing for the period of 7, 14, 28, and 56 days for the mechanical properties. Initially, the tests conducted in this work are compressive strength. Finally, an artificial neural network (ANN) was utilized in the process of developing a prediction model for compressive strength. For ANN, we plotted the experimentally determined compressive strength against the regression analysis strength after 56 days. Based on the experimental results, marble sludge powder was found to lessen the environmental impression of concrete and be economically advantageous. Using a feed-forward back-propagation neural network consisting of 8 input neurons, 2 and 1 neurons of hidden and output, respectively, which implies reliable mechanical strength, were introduced in this study. From the results, it was found that the mechanical properties of concrete were enhanced when dry marble sludge powder was incorporated up to 15% as a replacement.
Investigation on Compressive Strength of Fibre-Reinforced Concrete Using Artificial Neural Network
Lecture Notes in Civil Engineering
International Conference on Interdisciplinary Approaches in Civil Engineering for Sustainable Development ; 2023 July 07, 2023 - July 08, 2023
Recent Advances in Civil Engineering for Sustainable Communities ; Chapter : 2 ; 13-24
2024-03-26
12 pages
Article/Chapter (Book)
Electronic Resource
English
Artificial Neural Network (ANN) Models for Prediction of Steel Fibre-Reinforced Concrete Strength
Springer Verlag | 2021
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