Multi-dimensional modeling of green self-compacting concrete with recycled aggregate through response surface methodology

Abstract

Recycled Aggregate (RA) incorporation to Self-Compacting Concrete (SCC) typically reduces mechanical performance and durability. The aim of this research is to model these variations as a function of RA content using advanced statistical tools such as Central Composite Design (CCD, α = 1) and Response Surface Methodology (RSM) to facilitate the optimization of RA additions. This study examines the behavior of SCC produced with 0 %–100 % recycled aggregate (RA), both coarse and fine, while maintaining 300 kg/m 3 of Portland cement. Five performance dimensions were assessed: fresh properties, compression-related mechanical properties, bending- tensile mechanical properties, durability (effective porosity and water absorption), and eco-environmental indicators (global warming potential and cost). Most resulting models with R 2 values above 0.95 were dependent on the square of the RA contents, and showed minimal interaction between coarse and fine RA. Therefore, their direction of maximum variation was approximately the vector i + j in a Cartesian coordinate system. According to models’ slopes, the greatest property variations occurred above 50 % replacement, but a higher rate for fresh and durability properties. Simultaneous optimization of all the models recommended using 35 %–45 % coarse RA and 30 %–45 % fine RA. Additionally, range optimization yielded specific RA amounts for high-performance SCC, comprising 0 %–20 % coarse RA and 20 %–40 % fine RA, and for conventional-performance SCC, which would admit 60 %–100 % coarse RA and 0 %–70 % fine RA.