Mechanical strength prediction of steel fiber-reinforced recycled aggregate concrete: model accuracy and key influencing parameters

Abstract

Recycled coarse aggregate (RCA) can reduce natural-resource consumption and construction-waste disposal. However, adhered mortar, high porosity, and weak interfacial transition zones may impair the mechanical performance of recycled aggregate concrete. Steel fibers can partially offset these deficiencies by improving crack control and post-cracking resistance. This study evaluates the applicability of existing empirical equations for predicting the mechanical properties of steel fiber-reinforced recycled aggregate concrete (SFRAC). An experimental database was compiled from published studies covering the compressive, splitting tensile, and flexural strengths of SFRAC. The predictive performance of the selected equations was evaluated using the mean experimental-to-predicted (Exp./Pred.) strength ratio, standard deviation, coefficient of variation, mean absolute percentage error, root mean square error, parity plots, and prediction-error-band distributions. The effects of the RCA replacement level and fiber reinforcement index (RI) on prediction accuracy were also examined. The compressive-strength equations exhibited the highest overall predictive accuracy. The model proposed by Ezeldin et al. produced the lowest prediction error, whereas the model of Ou et al. exhibited the lowest scatter. For splitting tensile strength, the Thomas and Ramaswamy equation provided the most balanced predictions. The Swamy and Mangat equation demonstrated the best performance for flexural strength. Prediction accuracy generally declined for tensile-dominated properties and was strongly influenced by full RCA replacement and RI. The results indicate that equations developed for conventional steel fiber-reinforced concrete do not consistently account for the effects of RCA on strength development and fiber contribution. Accordingly, RCA-sensitive modifications incorporating aggregate replacement level and fiber reinforcement characteristics are required before these equations can be reliably applied to SFRAC mixtures.