ANN model using MATLAB in CFS -concrete

Abstract

This paper presents the ANN studies on concrete by using Cenosphere as a partial replacement of binder and filler addition with foundry sand. This study contains mechanical properties that includes ANN analysis in Cenosphere with Foundry Sand (CFS) Concrete. Cenosphere and waste foundry sand are extensively available in manufacturing industries. The resulting materials have adequate strength and greater durability characteristics. The various proportion of trial mixes are studied with Cenosphere namely 0% 5%, 10%, 15%, and 20% with replacement of OPC 53 grade, and waste foundry sand with 20%, 30%, 40%, 50%, and,60% with partial replacement of sand added to the concrete. The strength and durability were tested for 7, 14, 28, 56 and 91 days. The waste foundry sand is used as alternate for fine aggregate and Cenosphere used as cement partial mixing for the dosages. Since Cenosphere is a very fine material of the colour of cement it can be used in replacing cement instead of PPC. Ash Cenospheres are hollow lightweight microspheres formed from fly ash generated during the burning of pulverised coal for power production. The particle size and characteristics are very similar to the pozzolanas with comparatively low density. It containsSiO2and Al2O3 in larger quantity and the content of components, such as SiO2, Fe2O3, MgO, CaO and K2O,which help for the enhancement of strength. The waste foundry sand is available in greater quantity and so it can be used for making concrete. The test results show good workability and mechanical behavior of concrete. This concrete increases 25 to 50 percentage of strength and have the best workability. It controls pores and crack in concrete. Micro cracks and pores are controlled better compared to conventional mixing concrete. This study includes the Artificial neural network (ANN) to predict the numerical experiments to review the effects of variable proportions on the concrete mix.