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        Application of peak based-Bayesian statistical method for isotope identification and categorization of depleted, natural and low enriched uranium measured by LaBr3:Ce scintillation detector

        Yücel Haluk,Tüzüner Selin Saatcı,Massey Charles 한국원자력학회 2023 Nuclear Engineering and Technology Vol.55 No.10

        Todays, medium energy resolution detectors are preferably used in radioisotope identification devices( RID) in nuclear and radioactive material categorization. However, there is still a need to develop or enhance « automated identifiers » for the useful RID algorithms. To decide whether any material is SNM or NORM, a key parameter is the better energy resolution of the detector. Although masking, shielding and gain shift/stabilization and other affecting parameters on site are also important for successful operations, the suitability of the RID algorithm is also a critical point to enhance the identification reliability while extracting the features from the spectral analysis. In this study, a RID algorithm based on Bayesian statistical method has been modified for medium energy resolution detectors and applied to the uranium gamma-ray spectra taken by a LaBr3:Ce detector. The present Bayesian RID algorithm covers up to 2000 keV energy range. It uses the peak centroids, the peak areas from the measured gamma-ray spectra. The extraction features are derived from the peak-based Bayesian classifiers to estimate a posterior probability for each isotope in the ANSI library. The program operations were tested under a MATLAB platform. The present peak based Bayesian RID algorithm was validated by using single isotopes(241Am, 57Co, 137Cs, 54Mn, 60Co), and then applied to five standard nuclear materials(0.32e4.51% at.235U), as well as natural U- and Th-ores. The ID performance of the RID algorithm was quantified in terms of F-score for each isotope. The posterior probability is calculated to be 54.5e74.4% for 238U and 4.7e10.5% for 235U in EC-NRM171 uranium materials. For the case of the more complex gamma-ray spectra from CRMs, the total scoring (ST) method was preferred for its ID performance evaluation. It was shown that the present peak based Bayesian RID algorithm can be applied to identify 235U and 238U isotopes in LEU or natural U eTh samples if a medium energy resolution detector is was in the measurements.

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        Evaluation of the Experimental np-Angular Distribution at 14.1 MeV Neutron Energy

        N. V. Kornilov,T. Massey,S. Grimes 한국물리학회 2011 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.59 No.23

        The total cross section and angular distribution of the (n,p) scattering reaction is an object for detailed experimental and theoretical investigations as a primary standard. In spite of many years efforts these data, in particular the angular distribution are not known with required accuracy. We analyzed available experimental data at ∼14 MeV and concluded that the big data spread is connected mainly with data normalization. We renormalize the original data using the following procedure. All data sets were fit by different polynomial expansions. The data of independent experiments were normalized to reach minimum χ^2. The beginning value was χ^2 = 1.47 and final value χ^2 = 0.41. The data corrections were <5%. The final result is insensitive to the order of polynomial expansion. The final χ^2 of 0.41 indicates that we have reduced systematic errors in the data sets, so we have reduced the error bars by a factor of 1.6. ENDF/B-7 data are in reasonable agreement with evaluated experimental data. But some problem became more visible - it seems that experimental data require stronger angular asymmetry.

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