Ranking bridge intervention scenarios with a risk-based predictive decision support system

Advancing infrastructure management practices requires innovative decision-support tools to enhance the functionality, safety, and sustainability of infrastructure assets. This paper introduces the fundamentals of a Decision Support System (DSS) that integrates a risk-based prioritization framework with a streamlined probabilistic structural reliability model, providing data-driven and cost-effective operational scenario rankings. By leveraging probabilistic deterioration Markov Chains models, the DSS accounts for correlation effects between several present and potentially new defects, ensuring an accurate representation of the degradation processes and future structural risks. Such, through a streamlined structural reliability assessment methodology, intended to bridge the gap between rigorous and data-hungry structural reliability assessments and real-world decision-making constraints. The DSS also includes key decision-making factors such as the exposure and the operational scenarios costs. The proposed framework empowers infrastructure managers with a scalable and adaptable tool for proactive maintenance strategies, resource allocation optimization and intervention planning.