Prediction of Strengths of Remixed Concrete

Abstract

This paper deals with the methodology, related to application of neural network analysis for reuse of partially set old concrete by adding fresh concrete to form usable mix by considering their time lags and blend ratios. When we relate the strength of the freshly prepared concretes the preset concrete obviously gives the reduction in strength. This problem will be overcome by adding a specific quantity of fresh mass to the partially set old concrete mass. The paper focuses on the utilization of neural network (N.N.) for predicting the 28-day strengths of concrete. The complex nonlinear relationship between the responses (factors that influence concrete strength-blend ratio, time lag, strength at initial setting time and final setting time) and the output (concrete strength) can be built by applying N.N. High degree of accuracy is achieved by the model for prediction of strengths.