Progress in Computational Modelling for Concrete Durability and Its Integration with Artificial Intelligence and Life-Cycle Assessment

Concrete durability significantly influences a structure’s service life, directly affecting maintenance frequency, repair interventions, and the total embodied carbon of infrastructure. Accurate durability predictions are crucial to avoid both over- and under-design, ensuring timely interventions that prevent premature failures. While computational modelling is essential for predicting long-term concrete behaviour under environmental stressors, challenges remain in aligning these methods with sustainability, decarbonisation goals, and real-world reliability. The fib Model Code 2020 provides a unified framework for durability design and through-life management, but its implementation requires balancing computational complexity with practical constraints. This study comprehensively analyses computational approaches used to model concrete degradation due to carbonation, chloride ingress, freeze-thaw cycles, and chemical attack. Additionally, integrating artificial intelligence and suitable machine and deep learning models with computational models to enhance prediction accuracy and enable adaptive, data-driven durability assessments is explored. A key novelty of this study is the coupling of Life cycle assessment (LCA) with durability modelling to improve the estimation of a structure’s actual service life. Unlike traditional LCA approaches that rely on assumed service life values, this integrated framework allows for a more precise calculation of embodied carbon by accounting for real degradation mechanisms and repair needs. By bridging durability modelling with sustainability considerations, this paper proposes strategies to develop concrete structures that are both low-carbon and highly durable. The findings contribute to advancing performance-based design approaches that optimise material efficiency, extend service life, and reduce environmental impact, ultimately guiding the development of resilient and sustainable infrastructure.