A Decision Support System to Enhance Electricity Grid Resilience against Flooding Disasters

In different areas across the U.S., there are utility poles and other critical infrastructure that are vulnerable to flooding damage. The goal of this multidisciplinary research is to assess and minimize the probability of utility pole failure through conventional hydrological, hydrostatic, and geotechnical calculations embedded to a unique mixed-integer linear programming (MILP) optimization framework. Once the flow rates that cause utility pole overturn are determined, the most cost-efficient subterranean pipe network configuration can be created that will allow for flood waters to be redirected from vulnerable infrastructure elements. The optimization framework was simulated using the Julia scientific programming language, for which the JuMP interface and Gurobi solver package were employed to solve a minimum cost network flow objective function given the numerous decision variables and constraints across the network. We implemented our optimization framework in three different watersheds across the U.S. These watersheds are located near Whittier, NC; Leadville, CO; and London, AR. The implementation of a minimum cost network flow optimization model within these watersheds produced results demonstrating that the necessary amount of flood waters could be conveyed away from utility poles to prevent failure by flooding.

A Full-Scale Experimental Investigation of Utility Poles Made of Glass Fibre Reinforced Polymer

Utility poles made of glass fibre-reinforced polymer (GFRP) are becoming increasingly common in European countries. Therefore, it is necessary to accurately examine their structural properties to ensure the integrity and safety of the poles. The purpose of this article is to compare the bending resistance of GFRP composite lighting columns obtained using European standard procedures with full-scale experimental tests. Several composite lighting columns were tested as part of the research study, and coupon tests were performed to assess the material properties required to calculate their bending resistance according to European Standard (EN) 40-3-3. The results obtained differed significantly. Furthermore, it was observed that the current standard rules for obtaining the resistance of GFRP poles based on the limit state method show a higher load capacity of the column in comparison to the capacity obtained from the tests.

Visualization of 3D cable between utility poles obtained from laser scanning point clouds: a case study

We can automate inspection work of infrastructure facilities by analyzing the characteristics of 3D structure information obtained through 3D structure visualization using a point cloud. The safety level of equipment can then be diagnosed quantitatively. In this paper, we investigate the modeling of wire structures such as overhead communication cables between utility poles, which are close to the ground, have many obstructions, and have a complex structure. We evaluate the accuracy of cable models and compare them to the correct model. We use three modeling methods: a machine-learning method based on the extruded surface of a point cloud as a feature, a rule-based method involving principal component analysis, and models generated from a combination of these models. In addition, we focus on modeling overhead cables from field data (urban and suburban). Results show the practicability of modeling overhead cables with a cable length of 10–70 m regardless of the area type. We find that the best cable modeling rate with the precision and recall of 80.76% and 83.84%, respectively, can be obtained using the machine-learning method and by specifying the cable reproduction rate to be 2 m. Article highlights This study is useful in determining the practicality of 3D visualization of communication cables based on a 3D point cloud. Precision and recall are presented as indices to determine the practicality of 3D cable modeling. This study provides 3D cable modeling for actual field data (in suburban, bridges, and urban areas).