An Intercomparison of Monte Carlo Codes Used in Gamma-Ray Spectrometry

In an intercomparison exercise, the Monte Carlo codes most commonly used in gamma-ray spectrometry today were compared with each other in order to gauge the differences between them in terms of typical applications. No reference was made to experimental data, instead, the aim was to confront the codes with each other, as they were applied to the calculation of full energy peak and total efficiencies. Surprising differences between the results of different codes were revealed.JRC.D.4-Isotope measurement

An intercomparison of Monte Carlo codes used in gamma-ray spectrometry

In an intercomparison exercise, the Monte Carlo codes most commonly used in gamma-ray spectrometry today were compared with each other in order to gauge the differences between them in terms of typical applications. No reference was made to experimental data; instead, the aim was to confront the codes with each other, as they were applied to the calculation of full-energy-peak and total efficiencies. Surprising differences between the results of different codes were revealed

Determination of the probability for locating peaks by computerised peak location methods in gamma-ray spectra as a function of the relative peak area uncertainty

22nd International Confeence on Radionuclide Metrology and its Applications; Salamanca, 2019

Determining the probability of locating peaks using computerized peak-location methods in gamma-ray spectra as a function of the relative peak-area uncertainty

The probabilities of locating peaks with a high relative peak-area uncertainty were determined empirically with nine types of peak-location software used in laboratories engaged in gamma-ray spectrometry measurements. It was found that it is not possible to locate peaks with a probability of 0.95, when they have a relative peak-area uncertainty in excess of 50%. Locating peaks at these relatively high peak-area uncertainties with a probability greater than 0.95 is only possible in the library-driven mode, where the peak positions are supposed a-priori. The deficiencies of the library-driven mode and the possibilities to improve the probabilities of locating peaks are briefly discussed. © 2019 Elsevier Lt