Forecasting bridge damage within a predictive Structural Reliability-based DSS

Nowadays there is urgent need for expeditious and efficient approaches to assess the structural reliability of widespread aging bridge stocks. As such, a shift towards predictive maintenance measures is required. This paper addresses such pressing necessity for efficient methods to assess the structural state of aging bridges, centring its research question on developing a Decision Support System (DSS) that integrates an innovative reliability model with Markov Chain projections to prioritize bridge interventions. The proposed DSS effectively forecasts structural risks and computes a Priority Index to guide maintenance decisions. This tool empowers infrastructure managers with timely insights, enhancing bridge safety and optimizing resource allocation. The study's practical example underscores the DSS's applicability, demonstrating its capacity to streamline decision-making in realworld scenarios. By providing a sophisticated yet accessible approach to structural reliability assessment, this research lays the groundwork for future enhancements, including the incorporation of additional risk factors and refined calibration methods.