Abstract

Wood poles are among key components of the overhead grid infrastructure that are highly vulnerable to wind hazards. In coastal regions where hurricanes are often accompanied with a storm surge, in addition to high wind pressure, poles may experience significant surge and wave loads with the potential of triggering multiple failure mechanisms. However, multihazard pole fragility models that consider various modes of failure are lacking. This paper proposed a set of parameterized fragility models that are a function of wind-, surge-, and wave-related intensity measures and properties of poles. For this purpose, a design of experiment was conducted to generate realizations of intensity measures and pole-specific deterministic and uncertain parameters. For each realization, the state of survival/failure of pole was estimated for each mode of failure. Subsequently, for each class of pole and soil type, a logistic regression was carried out to generate fragility models for pole rupture at the ground line and pole overturning due to foundation failure. The results indicated that both pole rupture and foundation failure can be significant modes of failure conditioned on the type of soil. For example, for medium-strength cohesive soils, both modes of failure were significant, whereas for very-stiff-strength cohesive soils, pole rupture was the dominant mode of failure. The results of this study are key for risk and resilience analysis of coastal electric power systems and provide useful insights for decision making and risk management processes.

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Data Availability Statement

Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.

Acknowledgments

This research was conducted as part of the National Institute of Standards and Technology (NIST) Center of Excellence for Risk-Based Community Resilience Planning under Cooperative Agreement 70NANB15H044 and 70NANB20H008 between the NIST and Colorado State University. The content expressed in this paper are the views of the authors and do not necessarily represent the opinions or views of NIST. The third author was supported in part by Lichtenstein endowment at the Ohio State University.

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Go to Journal of Structural Engineering
Journal of Structural Engineering
Volume 148Issue 6June 2022

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Received: Aug 10, 2021
Accepted: Dec 8, 2021
Published online: Mar 31, 2022
Published in print: Jun 1, 2022
Discussion open until: Aug 31, 2022

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Research Assistant Professor, Dept. of Civil, Environmental, and Geospatial Engineering, Michigan Technological Univ., 811 Dow Environmental Sciences, 1400 Townsend Dr., Houghton, MI 49931 (corresponding author). ORCID: https://orcid.org/0000-0003-4896-2535. Email: [email protected]
Jamie Padgett, M.ASCE [email protected]
Stanley C. Moore Professor, Dept. of Civil and Environmental Engineering, Rice Univ., 214 Ryon Lab, 6100 Main St., MS-318, Houston, TX 77005. Email: [email protected]
Lichtenstein Associate Professor, Dept. of Civil, Environmental, and Geodetic Engineering, Ohio State Univ., 214B Bolz Hall, 2036 Neil Ave., Columbus, OH 43210. ORCID: https://orcid.org/0000-0001-6768-8522. Email: [email protected]

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Cited by

  • 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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  • Risk-Informed and Life-Cycle Analyses of Structures and Infrastructures, Journal of Structural Engineering, 10.1061/(ASCE)ST.1943-541X.0003495, 148, 12, (2022).

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