ANN-based feasibility analysis of granite powder and fly ash as partial cement replacements for predicting concrete strength

The increasing demand for cement in the construction field has led to higher energy consumption and carbon emissions. To promote sustainable concrete production, industrial by-products such as granite powder and Class F fly ash are being explored as partial cement replacement materials due to their pozzolanic and filler properties, which can improve concrete performance while reducing environmental impact. This study examines the combined use of fly ash and granite powder as partial substitutions for cement in concrete mixtures. Experimental work was carried out by incorporating varying proportions of fly ash (0%, 10%, 20%, and 30%) and granite powder (0%, 5%, 10%, and 15%) to evaluate their influence on mechanical properties. The results indicate that appropriate substitution levels can enhance compressive strength, split tensile strength, and flexural performance. Overall, the best performance was achieved at the ideal mix percentage of 20% fly ash and 10% granite powder. An Artificial Neural Network (ANN) model was created in addition to the experimental study in order to forecast the strength characteristics using the optimised input parameters. The efficacy of the method was demonstrated by the ANN forecasts’ strong agreement with the experimental findings. Additionally, using fly ash and granite powder promotes sustainable building methods by reducing waste and conserving natural resources.