Prediction of properties of fly ash and cement mixed GBFS compressed bricks

Abstract

In the present study the artificial neural network is used to predict the properties of fly ash and granulated blast furnace slag mixed compressed bricks. Bricks containing fly ash, different proportion of granulated blast furnace slag with constant quantity of cement are fabricated. The bricks are cured by three ways such as, by sprinkling water, by dipping into the alkaline water, and by immersing into the acidic water for 3, 7 and 28 days respectively. After curing, the bricks are tested to determine its compressive strength, water absorption and pH. The results from the experiments were used for the training of the artificial neural network neurons. Using the trained artificial neural network, the values for the composition 0% to 60% were obtained with 5% increment in every interval. It is observed that as the content of granulated blast furnace slag increases than the fly ash content, the compressive strength increases. With the increase in granulated blast furnace slag content the water absorption reduces and pH increases and hence increases the resistance against acid attack.