Corrigendum: Radiological Mapping of Post-Disaster Nuclear Environments Using Fixed-Wing Unmanned Aerial Systems: A Study From Chornobyl

Gamma ray detection performance of newly developed MAPD-3NM-II photosensor with LaBr3(Ce) crystal

This paper presents the gamma-ray detection performance of the newly developed MAPD-3NM-II type SiPM sensor array (4 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\times$$\end{document}× 4) with \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\hbox {LaBr}_3$$\end{document}LaBr3(Ce) scintillator. The gamma-ray spectra of various sources have been measured in the energy range from 26 keV up to 1332 keV. The newly developed array based on MAPD-3NM-II sensors proved \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\sim$$\end{document}∼ 22% enhancement in energy resolution in comparison to the former MAPD-3NM-I based array. The energy resolution of 662 keV gamma-rays measured by MAPD-3NM-II was 3.3% while clearly surpassing 4.25% resolution of MAPD-3NM-I predecessor. The enhancement is related to the high PDE of the new MAPD-3NM-II. Obtained results show that the new MAPD-3NM-II demonstrated good energy resolution and linearity in the studied energy region. The energy resolution of the new detector developed based on MAPD-3NM-II was better than all previous products of MAPD.

Use of Gaussian process regression for radiation mapping of a nuclear reactor with a mobile robot

Collection and interpolation of radiation observations is of vital importance to support routine operations in the nuclear sector globally, as well as for completing surveys during crisis response. To reduce exposure to ionizing radiation that human workers can be subjected to during such surveys, there is a strong desire to utilise robotic systems. Previous approaches to interpolate measurements taken from nuclear facilities to reconstruct radiological maps of an environment cannot be applied accurately to data collected from a robotic survey as they are unable to cope well with irregularly spaced, noisy, low count data. In this work, a novel approach to interpolating radiation measurements collected from a robot is proposed that overcomes the problems associated with sparse and noisy measurements. The proposed method integrates an appropriate kernel, benchmarked against the radiation transport code MCNP6, into the Gaussian Process Regression technique. The suitability of the proposed technique is demonstrated through its application to data collected from a bespoke robotic system used to conduct a survey of the Joz̆ef Stefan Institute TRIGA Mark II nuclear reactor during steady state operation, where it is shown to successfully reconstruct gamma dosimetry estimates in the reactor hall and aid in identifying sources of ionizing radiation.