Literature DB >> 30986718

Optimizing UAV-based radiation sensor systems for aerial surveys.

Chanki Lee1, Hee Reyoung Kim2.   

Abstract

In this study, we qualitatively and quantitatively analyzed unmanned aerial vehicle (UAV)-based radiation sensor systems suitable for specific survey missions. We examined a variety of UAVs, radiation sensors, and radiological survey missions; after reviewing previous studies that developed and conducted field tests, we categorized them by mission and suggested suitable types of UAVs and radiation sensors for each mission. To quantitatively analyze various system designs previously suggested, we proposed a new figure of merit (FOM) formula that can explain the mutual effects of parameters of both radiation sensors and UAVs on system performance. After targeting a radiological survey mission, we selected UAV and radiation sensor types qualitatively. Then, the quantitative FOM formula can be employed to efficiently assess whether the system achieves the required minimum detectable activity (MDA) without field test, while keeping the error of the MDA values in the order of 100. After defining the constraints including the proposed FOM formula, we replicated a severe nuclear power plant accident scenario. We found that one fixed-wing UAV and multiple rotary-wing UAVs are the minimum number of UAVs, and thus the optimal system for timely achievement of a satisfactory MDA and estimation of the three-dimensional radiation distribution contributed by both ground radiation and an atmospheric radioactive plume.
Copyright © 2019. Published by Elsevier Ltd.

Entities:  

Keywords:  Figure of merit; Minimum detectable activity; Optimization; Power consumption; Radiation sensor; Unmanned aerial vehicle

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Year:  2019        PMID: 30986718     DOI: 10.1016/j.jenvrad.2019.04.002

Source DB:  PubMed          Journal:  J Environ Radioact        ISSN: 0265-931X            Impact factor:   2.674


  1 in total

1.  Radiological Scouting, Monitoring and Inspection Using Drones.

Authors:  Luís Ramos Pinto; Alberto Vale; Yoeri Brouwer; Jorge Borbinha; José Corisco; Rodrigo Ventura; Ana Margarida Silva; André Mourato; Gonçalo Marques; Yuri Romanets; Susana Sargento; Bruno Gonçalves
Journal:  Sensors (Basel)       Date:  2021-04-30       Impact factor: 3.576

  1 in total

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