We have developed radionuclide identification algorithms for radiation portal monitor applications. One algorithm uses a spectral angle mapper to match the power spectral density of modified cumulative distribution functions of measured pulse height distributions to reference spectra, while the others rely on the decomposition of the observed spectrum as a linear mixture of known radionuclide spectra. Three algorithms were then tested for their ability to perform on-the-fly radionuclide identification on datasets acquired with a liquid organic scintillator-based pedestrian radiation portal monitor on moving special nuclear material and industrial radiological sources, as well as common medical isotopes. We quantified and compared the relative efficacies of the algorithms considered using F-score analysis. Measured radiation sources included 51 g of highly enriched uranium, 6.6 g of weapons grade plutonium, 241Am, 133Ba, 57Co and 137Cs sources with activities of several hundred kBq, as well as 260 kBq liquid solution samples of the medical isotopes 99mTc, 111In, 67Ga, 123I, 131I, and 201Tl. We achieved 100% positive identification, for three-second measurements of single sources moving at a source-transit speed of 1.2 m/s. For mixed sources with strongest and weakest sources having no more than a 5:1 ratio of detected counts, encouraging positive identification results were achieved with the un-mixing algorithms. Current radiation portal monitor designs suffer from a high incidence rate of nuisance radiation alarms caused in radiation portal monitor primary screenings by recent nuclear medicine patients and cargo containing large amounts of naturally occurring radioactive materials. Integrating reliable on-the-fly radionuclide identification into the radiation portal monitors could lower the number of nuisance alarms requiring time-consuming secondary inspections.
|Number of pages||10|
|Journal||Journal of Nuclear Materials Management|
|Publication status||Published - 2018|
Paff, M., Di Fulvio, A., Altmann, Y., Clarke, S. D., Hero, A., & Pozzi, S. A. (2018). Identification of mixed sources with an organic scintillator-based radiation portal monitor. Journal of Nuclear Materials Management, 46(4), 48-57.