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DOE OSTI · 1873834

Maximum Likelihood Spectrum Decomposition for Isotope Identification and Quantification

Matta, J. T.·Rowe, A. J.·Dion, M. P.·Willis, M. J.·Nicholson, A. D.·Archer, D. E.·Wightman, H. H.
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Abstract

A spectral decomposition method has been implemented to identify and quantify isotopic source terms in high-resolution gamma-ray spectroscopy in static geometry and shielding scenarios. Monte Carlo simulations were used to build the response matrix of a shielded high-purity germanium detector monitoring an effluent stream with a Marinelli configuration. The decomposition technique was applied to a series of calibration spectra taken with the detector using a multi-nuclide standard. These results are compared with decay-corrected values from the calibration certificate. For most nuclei in the standard ( 241 Am, 109 Cd, 137 Cs, and 60 Co), the deviations from the certificate values were generally no more than 6% with a few outliers as high as 10%. Furthermore, for 57 Co, the radionuclide with the lowest activity, the deviations from the standard reached as high as 25%, driven by the meager statistics in the calibration spectra. In addition, a complete treatment of error propagation for the technique is presented.

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73 NUCLEAR PHYSICS AND RADIATION PHYSICSMonte Carlo methodscalibrationdetectorsgamma-ray detectiongamma-ray detectorsgamma-ray spectroscopygovernmentinverse problemsisotope identificationisotopesmaximum likelihood expectation maximization (MLEM)monitoringnuclear measurementsnuclide identificationradioactive decaysemiconductor radiation detectorsspectral analysisspectral decompositionstandards

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Matta, J. T., Rowe, A. J., Dion, M. P., Willis, M. J., Nicholson, A. D., Archer, D. E., Wightman, H. H.. 2022-03-28. Maximum Likelihood Spectrum Decomposition for Isotope Identification and Quantification. https://doi.org/10.1109/tns.2022.3162986

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