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

Project description

New life for ageing European RC bridge networks

Throughout Europe, ageing reinforced concrete (RC) bridge networks play an important role in infrastructure that is crucial to everyday lives and to the smooth operation of industries. However, many of these networks are facing increasing risks resulting from corrosion-induced deterioration or mainshock-aftershock (MS-AS) seismic sequences. With the support of the Marie Skłodowska-Curie Actions programme, the DREAMS project will develop a multi-scale probabilistic framework to quantify the spatiotemporal resilience of deteriorating bridge networks. This framework will use new technologies, including AI-assisted workflows, material-level physics-based deterioration models, network-level resilience analysis and structure-level state-dependent fragility assessments for MS-AS sequences. It will also demonstrate this solution on a synthetic testbed of an Italian coastal bridge network.

Objective

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.

Fields of science (EuroSciVoc)

Keywords

Programme(s)

Topic(s)

Funding Scheme

HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships

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Call for proposal

(opens in new window) HORIZON-MSCA-2025-PF

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Coordinator

UNIVERSITY COLLEGE LONDON
Net EU contribution
€ 260 347,92
Address
GOWER STREET
WC1E 6BT London
United Kingdom
Region
London Inner London — West Camden and City of London
Activity type
Higher or Secondary Education Establishments
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Total cost
No data