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Abstract Major disasters such as wildfire, tornado, hurricane, tropical storm, and flooding cause disruptions in infrastructure systems such as power and water supply, wastewater management, telecommunication, and transportation facilities. Disruptions in electricity infrastructure have negative impacts on sectors throughout a region, including education, medical services, financial services, and recreation. In this study, we introduced a novel approach to investigate the factors that can be associated with longer restoration time of power service after a hurricane. Considering restoration time as the dependent variable and using a comprehensive set of county-level data, we estimated a generalized accelerated failure time (GAFT) model that accounts for spatial dependence among observations for time to event data. The model fit improved by 12% after considering the effects of spatial correlation in time to event data. Using the GAFT model and Hurricane Irma’s impact on Florida as a case study, we examined: (1) differences in electric power outages and restoration rates among different types of power companies—investor-owned power companies, rural and municipal cooperatives; (2) the relationship between the duration of power outage and power system variables; and (3) the relationship between the duration of power outage and socioeconomic attributes. The findings of this study indicate that counties with a higher percentage of customers served by investor-owned electric companies and lower median household income faced power outage for a longer time. This study identified the key factors to predict restoration time of hurricane-induced power outages, allowing disaster management agencies to adopt strategies required for restoration process.
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Historical Hurricane-Induced US Gulf Coast Petrochemical Infrastructure Disruption Data 2023
In this project we provide downtime and resulting excess emissions data on hurricane-induced disruptions to US Gulf Coast petrochemical complexes as well as corresponding storm and facility characteristics. This data can be used in the regional risk and reliability assessment of petrochemical processing infrastructure subject to hurricane hazard-induced disruptions. This dataset might be applicable to research related to petrochemical infrastructure resilience modeling on local, regional, and global scales.
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- Award ID(s):
- 2227467
- PAR ID:
- 10571729
- Publisher / Repository:
- Designsafe-CI
- Date Published:
- Subject(s) / Keyword(s):
- US Gulf Coast petrochemical processing infrastructure hurricane hazards oil and gas
- Format(s):
- Medium: X
- Institution:
- University of Texas at Austin
- Sponsoring Org:
- National Science Foundation
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