2021/06/06 by Amir Esmalian, Esmalian, Amir, Wanqiu Wang +3 · 1 citation
Engineering · Environmental Science · Social Sciences · #Computational Engineering #Disaster Management and Resilience #FOS: Computer and information sciences #Finance #Flood Risk Assessment and Management #Infrastructure Resilience and Vulnerability Analysis #and Science (cs.CE)
paper · pdf · doi:10.48550/arxiv.2106.03160
openalex publication_date 2021/06/06 · openalex created_date 2022/07/25 · openalex updated_date 2026/07/28
To enable integrating social equity considerations in infrastructure\nresilience assessments, this study created a new computational multi-agent\nsimulation model which enables integrated assessment of hazard, infrastructure\nsystem, and household elements and their interactions. With a focus on\nhurricane-induced power outages, the model consists of three elements: 1) the\nhazard component simulates exposure of the community to a hurricane with\nvarying intensity levels; 2) the physical infrastructure component simulates\nthe power network and its probabilistic failures and restoration under\ndifferent hazard scenarios; and 3) the households component captures the\ndynamic processes related to preparation, information seeking, and response\nactions of households facing hurricane-induced power outages. We used empirical\ndata from household surveys in conjunction with theoretical decision-making\nmodels to abstract and simulate the underlying mechanisms affecting experienced\nhardship of households. The multi-agent simulation model was then tested in the\ncontext of Harris County, Texas, and verified and validated using empirical\nresults from Hurricane Harvey in 2017. Then, the model was used to examine\neffects of different factors such as forewarning durations, social network\ntypes, and restoration and resource allocation strategies on reducing the\nsocietal impacts of service disruptions in an equitable manner. The results\nshow that improving the restoration prioritization strategy to focus on\nvulnerable populations is an effective approach, especially during\nhigh-intensity events. The results show the capability of the proposed\ncomputational model for capturing the dynamic and complex interactions in the\nnexus of humans, hazards, and infrastructure systems to better integrate\nhuman-centric aspects in resilience planning and into assessment of\ninfrastructure systems in disasters.\n