Monte Carlo simulation of a BEGe 6530 detector in GAMOS

Woodroof, TF, Boston, AJ and Judson, DS (2022) Monte Carlo simulation of a BEGe 6530 detector in GAMOS. NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT, 1034. p. 166726.

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Official URL: http://dx.doi.org/10.1016/j.nima.2022.166726

Abstract

A Mirion Technologies BEGe 6530 detector was used to validate the use of the GEANT4 scripting language GAMOS for performing source-less full-energy gamma ray photopeak efficiency calibrations. The detector model was developed using a combination of manufacturer specifications, experimental measurements of the detector's physical dimensions and comparisons of experimental and simulated response to a 137Cs point source. The resulting simulation files were short and concise (containing only eighty lines of code in total), reflecting the user-friendliness of GAMOS. Experimental efficiency data were then collected from point sources emitting gamma rays spanning an energy range of 26.3 keV to 1408.0 keV at a distance of 250 mm, corresponding to a typical in-situ measurement geometry. These data were used as the basis of a three-way comparison with GAMOS estimates and Mirion Technologies’ proprietary LabSOCS source-less efficiency calibration software. GAMOS was able to reproduce experimental efficiency values to within about 1% across the entire energy range (the same accuracy achieved by LabSOCS), whilst providing insights into model limitations that are not available from LabSOCS outputs. This study demonstrates that GAMOS can produce reliable source-less efficiency calibrations for industry-relevant measurement geometries whilst offering a unique combination of ease-of-use and extensive user control over the simulation process and outputs.

Item Type:	Article
Uncontrolled Keywords:	Gamma spectrometry, BEGe 6530, Efficiency calibration, GEANT4, GAMOS, Validation
Divisions:	Faculty of Science and Engineering > School of Physical Sciences
Depositing User:	Symplectic Admin
Date Deposited:	28 Jun 2022 11:39
Last Modified:	18 Jan 2023 20:56
DOI:	10.1016/j.nima.2022.166726
Open Access URL:	https://doi.org/10.1016/j.nima.2022.166726
Related URLs:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3157385