Digital twin assessment and maintenance technology for structural performance

Many large reinforced concrete structures worldwide have been in service for several decades, during which their durability has gradually deteriorated due to environmental influences such as temperature variations, moisture ingress, carbonation, and chloride attack. As a result, the structural reliability of these systems has declined over time. In particular, critical infrastructure—including bridges and tunnels—is continuously subjected to repetitive loading and harsh environmental exposure, leading to progressive performance degradation. However, conventional maintenance and assessment approaches rely heavily on visual inspections, limited experimental data analysis, and empirical judgment, which are insufficient for comprehensively evaluating the overall structural performance. These traditional methods not only lack the capability to accurately predict the long-term behaviour of large-scale structures but also hinder the quantitative determination of appropriate maintenance and strengthening measures. Consequently, a more systematic and quantitative assessment methodology is required to support reliable decision-making for the maintenance and rehabilitation of reinforced concrete infrastructure. Furthermore, modern structural safety standards are becoming increasingly stringent, and many aging structures no longer satisfy current design requirements, necessitating thorough assessment and appropriate retrofitting strategies. Full-scale experimental validation of structural performance is generally impractical due to economic and technological constraints. Therefore, objective analytical methods based on reliability theory and digital twin technology are essential. Reliability-based approaches enable the quantification of uncertainties in structural performance using experimental and monitoring data, while digital twins provide high-fidelity representations of the current structural condition and facilitate the prediction of long-term performance evolution under varying influencing factors. Ensuring the safety of large infrastructure systems is a global challenge rather than a country-specific issue, and reliability assessment and digital twin technologies are actively being investigated worldwide. In regions such as Europe and South Korea, where new construction markets are largely saturated, the maintenance and monitoring of existing structures have become increasingly important. This study forms part of an international research project that utilises monitoring data from the Jauntal Bridge in Austria and aims to contribute to the development of a more reliable structural safety assessment framework through global research collaboration. The outcomes of this research are expected to support both the maintenance and the design of large reinforced concrete structures in Europe and beyond, thereby contributing to the sustainability, safety, and efficiency of infrastructure systems for future generations.