Decision-support tools for Resilience Enhancement of Aging infrastructure under Multi-event Sequences

Aging reinforced concrete (RC) bridge networks in Europe face growing risks from sequential and cascading hazards. Corrosion-induced deterioration progressively reduces structural capacity, while sequential seismic events such as mainshock–aftershock (MS–AS) sequences amplify vulnerabilities and threaten system-wide functionality. The 2016–2017 Central Italy earthquake sequence alone caused an estimated €27 billion in reconstruction costs, underscoring the socio-economic burden of cascading seismic impacts. To address these challenges, DREAMS develops a multi-scale probabilistic framework to quantify the spatiotemporal resilience of deteriorating bridge networks. The framework integrates (a) material-level physics-based deterioration models calibrated against experimental datasets, (b) structure-level state-dependent fragility assessment under MS–AS sequences, and (c) network-level resilience analysis that propagates damage to functionality trajectories, recovery times, and accessibility metrics. Novel contributions also include AI-assisted workflows such as surrogate modeling and active learning for efficient computational simulation, and stochastic treatment of sequential hazards beyond single “worst-case” assumptions. A synthetic testbed of an Italian coastal bridge network will serve as a demonstrator, enabling scenario-based analyses and participatory “what-if” workshops with academic partners and collaborators, practitioners, and stakeholders. Key outcomes include open-source Python libraries and packages, end-to-end reproducible workflows, and an interactive decision-support system with GIS dashboards designed for both scientific advancement and practice-oriented decision-making. By explicitly linking long-term deterioration with sequential hazard impacts, DREAMS provides a robust foundation for resilience-oriented planning, supporting infrastructure robustness, risk-informed policy, and enhanced social preparedness.