Prediction of Micro-Structural Properties of Recycled Aggregate concrete using Artificial Intelligence

Abstract

Methodology using Artificial Intelligence to predict the Interfacial Transition Zone (ITZ) width and the Compressive Strength after 28 days of recycled aggregate concrete is offered in this research paper. Data of the samples collected from earlier studies are used to develop and test Neural model. Eight mix parameters namely Cement , Sand , Coarse aggregates , Recycled aggregates , Specific gravity of sand ,Specific gravity of coarse aggregates ,Water and Micro-Silica are used as the model inputs while the ITZ is output with 28 days Compressive strength . The promoted model can be used to anticipate the ITZ width and 28 days compressive strength of recycled aggregate concrete for various replacement ratios at different water cement ratios .The model developed and proposed in this research paper can be used to predict ITZ width and compressive strength for recycled aggregate concrete with Micro-Silica. It has been affirmed that the accuracy of the model gets enhanced with a larger number of input parameters.