Risk Informed Decision Making for Maintenance of Deteriorating Distribution Poles Under Extreme Wind Hazard

Risk Informed Decision Making for Maintenance of Deteriorating Distribution Poles Under Extreme Wind Hazard

Co-Project Leaders: Abdollah Shafieezadeh and Sakis Meliopoulos (ECE)
Students (GT): Rajath Bhat
Partner Schools: Ohio State University
The proposed project will advance the state-of-the-knowledge and practice in cost-effective maintenance of distribution poles by developing a risk-informed decision making framework for maintenance of the poles. This framework uses fragility analysis techniques to estimate the conditional probability of failure of various species and classes of distribution poles given the intensity measure of the extreme winds e.g. maximum wind gust speed, age of the pole, and climate and environmental factors such as moisture content and chloride exposure.

Specifically, the proposed research will provide time dependent fragility relationships with consideration of aging and deterioration effects and various modes of failure of the poles through stochastically generated Finite Element (FE) models of the components. In addition, the proposed project will provide a novel method for cost-effective maintenance and reliability enhancement of distribution poles by:
(1) Defining indices that quantify simultaneous effects of the risks of hurricane hazards, aging, and reliability-importance of samples of distribution poles in a network
(2) Generating a risk map of US regions most susceptible to distribution pole damage under extreme wind loads by ranking and color-coding regions using an index developed from hazard risk information
(3) Identifying poles at highest risks of damage for maintenance by evaluating effects of aging on failure probabilities of the poles through stochastic sampling algorithms
(4) Developing effective maintenance strategies for strengthening of at-risk poles by evaluating effects of different maintenance strategies on the reliability of distribution poles
(5) Developing an approach for stochastic optimization of life-cycle cost of distribution poles at the risk of hurricane damage using stochastic sampling techniques where uncertainties in diagnostic accuracy, failure probabilities and service costs are probabilistically defined and updated as new data are acquired.
In all, assuming the developed strategies are applied, the network of distribution poles in the United States will be reasonably fortified against hurricane hazards in optimality of maintenance costs and reliability of the network. The result will be a safer, more reliable network of distribution poles, and a better emergency-prepared electric power system.
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