A Novel Algorithm for Solving the True Coincident Counting Issues in Monte Carlo Simulations for Radiation Spectroscopy. Issue 6 (June 2015)

• Record Type: Journal Article
• Authors: Guan, Fada; Johns, Jesse M.; Vasudevan, Latha; Zhang, Guoqing; Tang, Xiaobin; Poston, John W.; Braby, Leslie A.
• Is Part Of: Health physics. Volume 108:Issue 6(2015:Jun.)
• Publication Date: 2015-06
• Subjects: Biophysics -- Periodicals; Health Physics -- periodicals; Radiation Protection -- periodicals; Radiotherapy -- periodicals; Medische fysica; Electronic journals; 612.01448
• DOI: 10.1097/HP.0000000000000185
• Languages: English
• ISSNs: 0017-9078

Abstract

<abstract> <title> <x xml:space="preserve">Abstract</x> </title> <sec> <title>Abstract</title> <p>Coincident counts can be observed in experimental radiation spectroscopy. Accurate quantification of the radiation source requires the detection efficiency of the spectrometer, which is often experimentally determined. However, Monte Carlo analysis can be used to supplement experimental approaches to determine the detection efficiency a priori. The traditional Monte Carlo method overestimates the detection efficiency as a result of omitting coincident counts caused mainly by multiple cascade source particles. In this study, a novel "multi-primary coincident counting" algorithm was developed using the Geant4 Monte Carlo simulation toolkit. A high-purity Germanium detector for ⁶⁰Co gamma-ray spectroscopy problems was accurately modeled to validate the developed algorithm. The simulated pulse height spectrum agreed well qualitatively with the measured spectrum obtained using the high-purity Germanium detector. The developed algorithm can be extended to other applications, with a particular emphasis on challenging radiation fields, such as counting multiple types of coincident radiations released from nuclear fission or used nuclear fuel.</p> </sec> </abstract>