Integrated concrete mix design with sustainability, cost and durability based on artificial intelligence

Abstract

Concrete production accounts for a substantial portion of global CO2 emission. One of possible ways to reduce the carbon footprint of concrete is to optimize the concrete mix design approach. This paper investigates the integration of sustainability, cost and durability performance with concrete mix based on artificial neural network. Carbonation-induced corrosion resistance is used for characterizing the durability performance of concrete mix. A dataset on natural carbonation coefficient, compressive strength and concrete mix design of concretes with various supplementary cementitious materials (SCMs) is established. An artificial neural network is trained, and used in designing a concrete mix with optimized sustainability, cost and durability performances given a target compressive strength. The results show that the artificial intelligence is promising in integrated concrete mix design with favorable sustainability, cost and durability performances.