4.7 Article

Multi-agent modeling of hazard-household-infrastructure nexus for equitable resilience assessment

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出版社

WILEY
DOI: 10.1111/mice.12818

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资金

  1. National Science Foundation [1846069]
  2. National Academies' Gulf Research Program Early Career Research Fellowship
  3. Div Of Civil, Mechanical, & Manufact Inn
  4. Directorate For Engineering [1846069] Funding Source: National Science Foundation

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This study developed a computational multi-agent simulation model to assess the impact of infrastructure service disruptions on households. The model integrates hazard, infrastructure system, and household elements to examine the interactions and propose strategies for equitable resilience. Improving restoration prioritization strategy to focus on vulnerable populations is found to be effective in reducing societal impacts.
Infrastructure service disruptions impact households in an affected community disproportionally. To enable integrating social equity considerations in infrastructure resilience assessments, this study created a new computational multi-agent simulation model, which enables integrated assessment of hazard, infrastructure system, and household elements and their interactions. With a focus on hurricane-induced power outages, the model consists of three elements: (1) the hazard component simulates exposure of the community to a hurricane with varying intensity levels; (2) the physical infrastructure component simulates the power network and its probabilistic failures and restoration under different hazard scenarios; and (3) the households component captures the dynamic processes related to preparation, information-seeking, and response actions of households facing hurricane-induced power outages. We used empirical data from household surveys from three hurricanes (Harvey, Florence, and Michael) in conjunction with theoretical decision-making models to abstract and simulate the underlying mechanisms affecting the experienced hardship of households when facing power outages. The multi-agent simulation model was then tested in the context of Harris County, Texas, and verified and validated using empirical results from Hurricane Harvey in 2017. Then, the model was used to examine the effects of different factors-such as forewarning durations, social network types, and restoration and resource allocation strategies-on reducing the societal impacts of service disruptions in an equitable manner. The results show that improving the restoration prioritization strategy to focus on vulnerable populations is an effective approach, especially during high-intensity events, to enhance equitable resilience. The results show the capability of the proposed computational model for capturing the dynamic and complex interactions in the nexus of households, hazards, and infrastructure systems to better integrate human-centric aspects in resilience planning and assessment of infrastructure systems in disasters. Hence, the proposed model and its results could provide a new tool for infrastructure managers and operators, as well as for disaster managers, in devising hazard mitigation and response strategies to reduce the societal impacts of power outages in an equitable manner.

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