Mix design optimization of concrete containing fly ash and slag for global warming potential and cost reduction

Abstract

Mix design optimization is challenging because the properties of concrete depend on both the chemical and physical properties of the components and their relative proportions. In this paper a mix design optimization approach based on the application of artificial intelligence, genetic algorithm optimisation, life-cycle assessment to quantify global warming potential (GWP) and simple economic modeling is developed and applied to identify the optimal use of fly ash and granulated blast furnace slag (GGBFS) in concretes with blended binders. A database including 892 mixes with supplementary cementitious materials (SCMs) is used to predict the concrete compressive strength and slump. Five case studies are presented investigating the influence of: chemical makeup of cement and SCMs, minimum cement content, regional transportation, emissions allocation, and binder type on the GWP and cost of optimal mix designs. The results show that the tool developed can reduce GWP by up to 60% and cost by up to 40% when compared to experimental results with equivalent strength.

Keywords

• Supplementary cementitious materials
• Mix optimization
• Carbon dioxide emissions
• Mix cost
• Industrial waste