Modeling Tree Damages and Infrastructure Disruptions under Strong Winds for Community Resilience Assessment
Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 9, Issue 1
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 (). 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.
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Data Availability Statement
Some data and models used during the study (building locations and models, and pole locations) were provided by a third party. Direct request for these materials may be made to the provider as indicated in the Acknowledgments. The remaining data, codes, and models that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
The work was funded in part by the Graduate Assistance in Areas of National Need (GAANN fellowship). Further, data on the buildings and powerlines were provided by the town of Fairfield and United Illuminating, respectively. Their support is greatly appreciated. The paper reflects the views of only the authors.
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Information & Authors
Information
Published In
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 9 • Issue 1 • March 2023
Copyright
© 2022 American Society of Civil Engineers.
History
Received: Jun 13, 2022
Accepted: Sep 8, 2022
Published online: Nov 10, 2022
Published in print: Mar 1, 2023
Discussion open until: Apr 10, 2023
ASCE Technical Topics:
- Analysis (by type)
- Buildings
- Ecosystems
- Energy engineering
- Energy infrastructure
- Energy sources (by type)
- Engineering fundamentals
- Environmental engineering
- Failure analysis
- Infrastructure
- Infrastructure resilience
- Lifeline systems
- Power transmission poles
- Renewable energy
- Residential buildings
- Structural engineering
- Structures (by type)
- Trees
- Vegetation
- Wind power
Authors
Metrics & Citations
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- William Hughes, Sita Nyame, William Taylor, Aaron Spaulding, Mingguo Hong, Xiaochuan Luo, Slava Maslennikov, Diego Cerrai, Emmanouil Anagnostou, Wei Zhang, A Probabilistic Method for Integrating Physics-Based and Data-Driven Storm Outage Prediction Models for Power Systems, ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 10.1061/AJRUA6.RUENG-1171, 10, 2, (2024).
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