Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/37675
Title: Minimal Detection Time for Localization of Radioactive Hot Spots in Low and Elevated Background Environments Using a CZT Gamma-Ray Spectrometer
Authors: BRABANTS, Lowie 
SIMONS, Mattias 
DE SCHEPPER, David 
DEMEESTER, Eric 
SCHROEYERS, Wouter 
Issue Date: 2022
Publisher: TAYLOR & FRANCIS INC
Source: NUCLEAR TECHNOLOGY, 208 (11) , p. 1681-1695
Abstract: This study determines the minimal detection time (MDT) needed for successful localization of radioactive hot spots during nuclear decommissioning work. An automated XY stage, equipped with a CdZnTe (CZT) spectrometer, was used to identify and localize hot spots of Am-241, Cs-137, and Co-60 in a 1.7 x 1.7-m area. The stage served as a preliminary test platform for the development of an automated robotic characterization platform [Autonomous Robotic platform for CHaractERization (ARCHER) robot]. The dependence of the MDT on the detector efficiency and background (BKG) level was examined. For low BKG environments, the MDT for Cs-137 was 871 ms and resulted in an error of the source localization of 14.21 mm and an error of the activity of 6.85%. For elevated BKG levels, the MDT increased to 15 526 ms. The Cs-137 source was localized with an error of 34.13 mm and an error of the source activity of -7.04%. The MDT determination method used here offers a valuable approach for decreasing total scanning times while avoiding missing the presence of hot spots.
Notes: Brabants, L (corresponding author), Hasselt Univ, Nucl Technol Fac Engn Technol, NuTeC, CMK, Agoralaan Bldg H, B-3590 Diepenbeek, Belgium.
lowie.brabants@uhasselt.be
Keywords: Radiation mapping;radiological hot spot localization;CZT detector;minimal detectable activity;minimal detection time
Document URI: http://hdl.handle.net/1942/37675
ISSN: 0029-5450
e-ISSN: 1943-7471
DOI: 10.1080/00295450.2022.2073950
ISI #: WOS:000817883700001
Rights: 2022 American Nuclear Society
Category: A1
Type: Journal Contribution
Validations: ecoom 2023
Appears in Collections:Research publications

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