Prediction of compressive strength in sustainable concrete using regression analysis

Abstract

This study focuses on the essential task of monitoring the strength of structural concrete in construction and rehabilitation projects. The conventional non-destructive testing (NDT) approach offers an indirect estimation of concrete compressive strength. However, the existing models lack the ability to address the estimation of compressive strength in concrete mixtures containing bottom ash (BA) and recycled coarse aggregate (RCA). This study aims to bridge this gap by accurately estimating the compressive strength of such concrete using the ultrasonic pulse velocity (UPV) technique. To achieve this objective, various concrete specimens with different cement content, water–cement ratios (w/c), recycled coarse aggregate, and bottom ash contents through weight batching, were prepared. UPV and compressive strength measurements were taken on cylindrical concrete specimens after 28 and 90 days of curing. The analysis revealed an exponential relationship between the compressive strength and UPV, with a high correlation coefficient across the evaluated concrete mixes, independent of the curing time. Ultimately, two robust models were developed to predict the compressive strength of concrete mixes containing different percentages of RCA and BA, respectively, at 28 and 90 days of curing. These models offer valuable insights and practical tools for ensuring the structural integrity of concrete in construction and rehabilitation projects involving bottom ash and recycled coarse aggregate.