Qualitative and quantitative validation of the SINBAD code on complex HPGe gamma-ray spectra

Conference of 4th International Conference on Advancements in Nuclear Instrumentation Measurement Methods and their Applications, ANIMMA 2015 ; Conference Code:121554; International audience; Radionuclide identification and quantification is a serious concern for many applications as safety or security of nuclear power plant or fuel cycle facility, CBRN risk identification, environmental radioprotection and waste measurements. High resolution gamma-ray spectrometry based on HPGe detectors is a performing solution for all these topics. During last decades, a great number of software has been developed to improve gamma spectra analysis. However, some difficulties remain in the analysis when full energy peaks are folded together with a high ratio between their amplitudes, when the Compton background is much larger compared to the signal of a single peak and when spectra are composed of a great number of peaks. This study deals with the comparison between a conventional analysis method and an innovative approach, called SINBAD ("Spectrométrie par Inférence Non paramétrique BAyesienne Déconvolutive"), for radionuclide identification and quantification. For many years, SINBAD has been developed by the CEA LIST for unfolding complex spectra from HPGe detectors. Contrary to the conventional method using fitting procedures, SINBAD uses a probabilistic approach with nonparametric Bayesian inference to process spectrum data. The conventional fitting method founded for instance in Genie 2000 is compared with the nonparametric SINBAD approach regarding some key figures of merit as the peak centroid estimation (identification step) and net peak area determination (quantification step). Complex cases are studied for nuclide detection with closed gamma-rays energies and high full energy peak intensity differences. Tests are performed with spectra from the International Atomic Energy Agency (IAEA) for gamma spectra analysis software benchmark and with spectra acquired in our laboratory. It appears that SINBAD results are better than GENIE 2000 ones in most of the cases even if hard deconvolutions can be achieved thanks to GENIE 2000 at the cost of expert parameters fine tuning which has to be compared with the user-friendly SINBAD operating.