Bayesian model for sustainable, resilient, and cost-effective concrete mixtures

ABSTRACT This work develops a Bayesian model that can be used to proportion sustainable, resilient, and cost-effective concrete mixtures based on stakeholder preferences. Traditionally, the decision-making process for proportioning concrete mixtures is centered around meeting target specifications, such as slump and compressive strength, and attributes such as sustainability and durability are given minimal importance. However, in the global push towards green infrastructure, sustainability plays a major role and must be considered to the same degree as engineering attributes. The model developed herein accounts for embodied carbon footprint, cost, and time to corrosion initiation, apart from the target specifications commonly used to proportion concrete mixtures. The developed model is demonstrated through two case studies: one targeting the average industrial embodied carbon footprint for a concrete mixture and the other targeting a reduction of 40% from the industry’s carbon footprint average. This model can also be used to perform data visualization and sensitivity analyses.