Strength Analysis of Fly Ash Concrete Based on Mechanical and Durability Properties Using Artificial Neural Network

The cement industry is a non-eco-friendly environment because of CO2 nonstop emission at the raw material production which is based on cement production procedure. This paper analyses the basic mechanical and durability assets of M50 strength score Heavy Weight Concrete (HWC) by the spare of cement through slag at 40-60% and fly ash at 15-35% levels. The flexural, elastic modules, durability assets, split tensile and compressive strength are involved water permeability and drying shrinkage behavior. Through lengthy curing enhances the mechanical and water permeability strength of slag and fly ash HWC. To evaluate the elastic modules of slag and fly ash, a simple connection is employed based on HWC from its compressive strength and density. The slag and fly ash concretes enhanced mechanical assets enhanced and permeable voids volume is minimized. The fly ash concrete has low resistance to chloride penetration because its high permeable voids volume. Based on these mechanical and durable properties of concrete which is considered as data is used to evaluate the compressive strength of concrete efficiently. To predict the compressive strength, an Weight update strategy based Artificial Neural network (W-ANN) The results show a long-tern drying shrinkage strain for every fly ash based on 15-35% of HWC is smaller than 100% of Ordinary Portland Cement (OPC). It is tough density variations of slag and fly ash concretes shows to long-term managed environment and it is used to measure the HWC members shielding thickness among ionizing radiations. Also, the proposed Weight update strategy based ANN which is used for the evaluation of compressive strength of concrete precisely which achieved less error when compared existing prediction models such as ANN.