Regression models to predict workability and strength of flowable concrete containing recycled aggregates. (2020)

• Record Type: Journal Article
• Authors: Saba, Marianne; Homsi, Farah; Gerges, Najib; Assaad, Joseph
• Is Part Of: Materials today. Volume 27:Part 1(2020)
• Page Start: 68
• Page End: 71
• Publication Date: 2020
• Subjects: Self-consolidating concrete -- Stability -- Regression models -- Recycled aggregates, Rheology; Materials science -- Congresses -- Periodicals; 620.1
• DOI: 10.1016/j.matpr.2019.08.238
• Languages: English
• ISSNs: 2214-7853

Abstract

Abstract: Regression models are rigorous computational techniques for developing and optimizing performance of cementitious-based concrete materials used for civil and infrastructure engineering works. This paper is part of a comprehensive research program undertaken to develop regression models that predict the behavior of self-consolidating concrete (SCC) containing recycled aggregates, for given proportioning constraints while minimizing the number of trials. Two series of SCC mixtures prepared with 375 and 450 kg/m 3 cement are tested. The water-to-cement ratios varied from 0.5 to 0.38, while the natural coarse aggregates were partially substituted by recycled ones at different rates varying from 0% to 100%. Tested properties include the rheology, passing ability, segregation, bleeding, surface settlement, and 28-days compressive strength. Reported regression models can be of particular interest to concrete researchers and engineering seeking for higher recycling technologies and improved sustainability in construction through conservation of virgin aggregate resources, energy savings, landfill reduction, and reduced CO2 emissions.