Sustainability-driven risk analysis of reinforced concrete structures

The construction sector a critical driver in EU that impacts the environment due to 30% of total energy consumption, considering operational and embodied energy. The thesis focuses on developing a unified framework for evaluating the target reliability of reinforced concrete structures. Traditionally, target reliability has been derived by optimization of cost and safety ignoring the environmental toll. But achieving sustainability in civil infrastructure requires more than just minimizing material usage, it demands a careful trade-off between durability, safety margins, and environmental consequences across a structure’s life cycle. To address this, Fischer et al.’s (2019) monetary optimization model is expanded by introducing environmental costs and two new key variables the environmental class, reflecting the environmental cost relative to the construction cost, and the relative environmental cost, capturing the effect of reliability adjustments on environmental performance. This led to the development of a refined optimization equation that includes fixed and variable environmental costs also incorporating key inputs such as the age-averaged societal discount rate (γ), obsolescence rate (ω), consequence classes (CC1–CC3), and central safety factors (p). Probabilistic methods are employed to compute failure probabilities (Pf (p)), considering lognormal distributions for resistance and action variables (VR, VS). The Malkia Bridge in Finland served as a case study to validate the model. From the life cycle analysis of the bridge, dead loads are calculated based on material volumes and live load distribution using Courbon’s Method. Dead load and live load moments are analyzed using Staad.Pro and resistance moment is calculated using Eurocode 4 as the structure is a concrete-steel composite. The central safety factor is determined by dividing the load and resistance moments. Then monetizing emissions in the LCA of the bridge using values from the EU Environmental Prices Handbook and integrating them into the optimization model, I was able to assess how environmental impacts shift the target reliability levels. For instance, higher environmental costs may justify reduced reliability thresholds to minimize resource use, while severe failure consequences (e.g., clean-up costs) may necessitate stricter target reliability. The results underscore the importance of interdisciplinary collaboration to align structural design with global sustainability goals. This research contributes a scalable, adaptable framework for engineers and policymakers, advancing the integration of environmental metrics into reliability-based design codes such as the fib Model Code 2020. By harmonizing safety, cost, and sustainability, the proposed model paves the way for greener, more resilient infrastructure in the EU and beyond.