Leveraging sUAS for Infrastructure Network Exploration and Failure Isolation

Lee, Andrew C.; Dahan, Mathieu; Weinert, Andrew; Amin, Saurabh

doi:10.1007/s10846-018-0838-0

Cited by 6 publications

(4 citation statements)

References 26 publications

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“…For locations, their administrative boundaries were sourced from Natural Earth Data at a 1:10m scale. The analysis focused primarily on UAS inspections as long linear infrastructure [14][15][16] and point obstacles. These realistic use cases are some the most mature and well understood UAS operations, as indicated by their evaluation as part of the UAS IPP, FAA UAS test site, or FAA Pathfinder activities.…”

Section: Use Cases and Data Sourcesmentioning

confidence: 99%

Method to Characterize Potential UAS Encounters Using Open Source Data

Weinert

2020

Aerospace

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As unmanned aerial systems (UASs) increasingly integrate into the US national airspace system, there is an increasing need to characterize how commercial and recreational UASs may encounter each other. To inform the development and evaluation of safety critical technologies, we demonstrate a methodology to analytically calculate all potential relative geometries between different UAS operations performing inspection missions. This method is based on a previously demonstrated technique that leverages open source geospatial information to generate representative unmanned aircraft trajectories. Using open source data and parallel processing techniques, we performed trillions of calculations to estimate the relative horizontal distance between geospatial points across sixteen locations.

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Section: Use Cases and Data Sourcesmentioning

confidence: 99%

Method to Characterize Potential UAS Encounters Using Open Source Data

Weinert

2020

Aerospace

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“…However, these models do not generate probabilistic, spatially-varying predictions of damage to infrastructure assets. A lack of adequate damage predictions impedes pre-storm resource allocation, warehouse selection, vehicle eet routing, damage localization, and repair operations (Van Hentenryck, Bent, & Co rin, 2010;Lee, Dahan, Weinert, & Amin, 2019). Slow damage localization and repair result in an increased time duration during which the infrastructure fails to adequately provide service to end-users.…”

Section: Introductionmentioning

confidence: 99%

Probabilistic Modeling of Hurricane Wind-Induced Damage in Infrastructure Systems

Chang¹,

Emanuel²,

Amin³

2021

Preprint

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This paper presents a modeling approach for probabilistic estimation of hurricane wind-induced damage to infrastructural assets. In our approach, we employ a Nonhomogeneous Poisson Process (NHPP) model for estimating spatially-varying probability distributions of damage as a function of hurricane wind eld velocities. Speci cally, we consider a physically-based, quadratic NHPP model for failures of overhead assets in electricity distribution systems. The wind eld velocities are provided by Forecasts of Hurricanes using Large-Ensemble Outputs (FHLO), a framework for generating probabilistic hurricane forecasts. We use FHLO in conjunction with the NHPP model, such that the hurricane forecast uncertainties represented by FHLO are accounted for in estimating the probability distributions of damage. Furthermore, we evaluate the spatial variability and extent of hurricane damage under key wind eld parameters (intensity, size, and asymmetries). By applying our approach to prediction of power outages (loss-of-service) in northwestern Florida due to Hurricane Michael (2018), we demonstrate a statistically signi cant relationship between outage rate and failure rate. Finally, we formulate parametric models that relate total damage and nancial losses to the hurricane parameters of intensity and size. Overall, this paper's ndings suggest that our approach is well-suited to jointly account for spatial variability and forecast uncertainty in the damage estimates, and is readily applicable to prediction of system loss-of-service due to the damage.

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“…However, low altitude airspace is fundamentally evolving with the integration of small unmanned aircraft system (sUAS). Many current and envisioned sUAS operations primarily operate at lower altitudes [1]- [4]. DISTRIBUTION STATEMENT A.…”

Section: Introductionmentioning

confidence: 99%

A Review of Low Altitude Manned Aviation Operations

Weinert¹,

Barrera²

2020

Preprint

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With the integration of small unmanned aircraft systems into the U.S. National Airspace System, low altitude regions are being stressed in historically new ways. The FAA must understand and quantify the risk of collision between unmanned and manned aircraft during desired low altitude unmanned operations in order to produce regulations and standards. It is increasingly important to characterize how manned aircraft operate at these low altitudes, as historical assumptions are insufficient for modeling and simulation to support standards development. Yet technical challenges such as poor low altitude radar coverage and lack of required transponder equipage are significant barriers to characterizing the low altitude environment. In response, we conducted an extensive review of fixedwing and rotary-helicopter manned operations to characterize the low altitude environment.

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Leveraging sUAS for Infrastructure Network Exploration and Failure Isolation

Cited by 6 publications

References 26 publications

Method to Characterize Potential UAS Encounters Using Open Source Data

Method to Characterize Potential UAS Encounters Using Open Source Data

Probabilistic Modeling of Hurricane Wind-Induced Damage in Infrastructure Systems

A Review of Low Altitude Manned Aviation Operations

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