Statistical Approach for the Design of Structural Self-Compacting Concrete with Fine Recycled Concrete Aggregate

The compressive strength of recycled concrete is acknowledged to be largely conditioned by the incorporation ratio of Recycled Concrete Aggregate (RCA), although that ratio needs to be carefully assessed to optimize the design of structural applications. In this study, Self-Compacting Concrete (SCC) mixes containing 100% coarse RCA and variable amounts, between 0% and 100%, of fine RCA were manufactured and their compressive strengths were tested in the laboratory for a statistical analysis of their strength variations, which exhibited robustness and normality according to the common statistical procedures. The results of the confidence intervals, the one-factor ANalysis Of VAriance (ANOVA), and the Kruskal–Wallis test showed that an increase in fine RCA content did not necessarily result in a significant decrease in strength, although the addition of fine RCA delayed the development of the final strength. The statistical models presented in this research can be used to define the optimum incorporation ratio that would produce the highest compressive strength. Furthermore, the multiple regression models offered accurate estimations of compressive strength, considering the interaction between the incorporation ratio of fine RCA and the curing age of concrete that the two-factor ANOVA revealed. Lastly, the probability distribution predictions, obtained through a log-likelihood analysis, fitted the results better than the predictions based on current standards, which clearly underestimated the compressive strength of SCC manufactured with fine RCA and require adjustment to take full advantage of these recycled materials. This analysis could be carried out on any type of waste and concrete, which would allow one to evaluate the same aspects as in this research and ensure that the use of recycled concrete maximizes both sustainability and strength.

This research was funded by the following entities and grants: Spanish Ministry MCI, AEI, EU, and ERDF, grants FPU17/03374 and RTI2018-097079-B-C31; the Junta de Castilla y León and ERDF, grant BU119P17 awarded to research group UIC-231; Youth Employment Initiative (JCyL) and ESF, grant UBU05B_1274; the University of Burgos, grant Y135 GI awarded to the SUCONS group; the University of the Basque Country, grant PPGA20/26; the Basque Government research group IT1314-19.