Zamzamian, S.M., Hosseini, S.A., Feghhi, S.A. and Samadfam, M. (2020) Determining of the Optimized Dimensions of the Marinelli Beaker Containing Source with Inhomogeneous Emission Rate by Using Genetic Algorithm Coupled with MCNP and Determining Distribution Type by Neural Networks. Applied Radiation and Isotopes, 157, Article No. 109039.
https://doi.org/10.1016/j.apradiso.2020.109039

has been cited by the following article:

• TITLE: Monte Carlo Simulation Study of Hot-Particle Detection in Voluminous Samples by Gamma Spectrometry

  AUTHORS: Liang T. Chu, Adam G. Burn, Clayton J. Bradt, Thomas M. Semkow

  KEYWORDS: Chernobyl, Fukushima, Peak Efficiency, Total Efficiency, Signal Detection Theory

  JOURNAL NAME: Journal of Applied Mathematics and Physics, Vol.9 No.7, July 22, 2021

  ABSTRACT: In this work, we addressed the inhomogeneity problem in gamma spectrometry caused by hot particles, which are dispersed into environment from large nuclear reactor accidents such as at Chernobyl and Fukushima. Using Monte Carlo simulation, we have determined the response of a gamma spectrometer to individual and grouped hot particles randomly distributed in a soil matrix of 1-L and 0.6-L sample containers. By exploring the fact that the peak-to-total ratio of efficiencies in gamma spectrometry is an empirical parameter, we derived and verified a power-law relationship between the peak efficiency and peak-to-total ratio. This enabled creation of a novel calibration model which was demonstrated to reduce the bias range and bias standard deviation, caused by measuring hot particles, by several times, as compared with the homogeneous calibration. The new model is independent of the number, location, and distribution of hot particles in the samples. In this work, we demonstrated successful performance of the model for a single-peak 137Cs radionuclide. An extension to multi-peak radionuclide was also derived.