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• W4308690948 abstract "Tree failures under extreme gusts could exacerbate storm damages to critical infrastructures, including the power delivery system, transportation network, or residential buildings. Nevertheless, the effects of tree damages have largely been excluded in existing community resilience assessment frameworks. To this end, presently, a model integrating tree failure consequences with community-level resilience evaluation is proposed for improved damage and recovery projections, considering the interconnected transportation, power delivery, and residential building systems. Tree failure probabilities are estimated based fragility analysis of the tree structural response under gusts. Proximity analysis is conducted to quantify the threat of trees striking critical infrastructures. The tree and wind risk assessments are integrated with fragility analysis of the power distribution system timber utility poles and the vulnerability analysis of low-rise wooden residential buildings. The methodology is carried out on a case study of a community in the northeastern US. The results indicate utility pole failures and roadway debris accumulations and blockages initiate when wind speeds reach around 40 m/s (90 mi/h). Although the inclusion of tree failures increase pole failure probability failure, tree-induced damages to residential buildings were found minimal due to the relatively lower heights of the sparser trees in the studied suburban region. Storm impacts are linked to the household level, including structural damages and their restoration times, increases in travel time to the main road, and probability of losing power. Vegetation management strategies are found to effectively reduce the building and powerline damages and debris buildup on roads." @default.
• W4308690948 created "2022-11-14" @default.
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• W4308690948 date "2023-03-01" @default.
• W4308690948 modified "2023-10-18" @default.
• W4308690948 title "Modeling Tree Damages and Infrastructure Disruptions under Strong Winds for Community Resilience Assessment" @default.
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• W4308690948 doi "https://doi.org/10.1061/ajrua6.rueng-956" @default.
• W4308690948 hasPublicationYear "2023" @default.
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