Modeling resilience of civil infrastructure systems

Understanding the impact of disasters to civil infrastructure systems can guide strategic pre-disaster preparedness and mitigation and post-disaster recovery planning. We have developed a resilience quantification framework for simulating post-disaster recovery of residential buildings, schools, bridge networks, and electric power and water networks. Our framework integrates statistical and heuristic methods (e.g., stochastic network analysis, greedy algorithm, probabilistic critical path analysis, multicriteria decision-making analysis) to simulate recovery trajectories under various technical, environmental, socioeconomic, political, and cultural conditions. Our models account for intra-system and inter-system interdependencies. We have applied our framework to both developed and developing countries. Our models can be applied to both single (e.g,, earthquakes, flood, hurricane, tsunami) and multiple hazard events.

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The following papers have been published:

Opabola E.A, and  Galasso, C. (2024) “A probabilistic framework for post-disaster recovery modelling of buildings and utility using stochastic network analysis” Reliability Engineering & System Safety https://doi.org/10.1016/j.ress.2023.109679              

Opabola E.A, and Galasso C., (2024) “Informing disaster-risk management policies for education infrastructure using scenario-based recovery analyses” Nature Communications                                        https://doi.org/10.1038/s41467-023-42407-y

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Other relevant papers are currently under review in reputable journals.