Experimental investigation on utilization of substitute building materials in concrete using neural networks

Abstract

The replacement of cement with sugarcane bagasse ash in concrete is considered due to its rich properties of projecting pozzolanic activity. The availability of aggregates is becoming scarce as a result of the non-renewable characteristic of fine and coarse aggregates. The construction waste end products like demolishing waste also cause the problem of improper disposal. Hence a majority of the construction industries have preferred the usage of construction and demolition (C&D) waste as a replacement for coarse aggregate. Substitution of coarse aggregates by construction and demolition waste and fine aggregates by iron slag ash is considered. The Taguchi method is adopted for the determination of mix combinations. This paper focuses on determining the properties of concrete having pozzolanic properties by replacing the cement with sugarcane bagasse ash (SBA), coarse aggregate with demolished building waste (DBW), and Fine aggregate with iron slag ash (ISA). The experimental investigation proved that SBA, DBW and ISA have a potential sign to be used as an alternative sustainable building material. From the comparative analysis of experimental results with ANN, it is revealed that the concrete show an acceptable prediction of physical and strength properties.