Active Interrogation of Special Nuclear Material Containers using AmBe Quasi-Forward Biased Directional Source and PGNAA
Abstract
Special Nuclear Material (SNM) including 95% 235U and 239Pu is capable of being identified by utilizing a quasi-forward directional AmBe source from Patent No: US20190013109A1 using Prompt Gamma Neutron Activation Analysis (PGNAA) simulated with Monte-Carlo N-Particle transport 6.2 (MCNP). HPGe and LaBr3 detector arrays were used to identify and quantify the peak-to-background and peak-to-total ratios of the associated photon spectra from the SNM encased in a polyethylene shield. The conducted simulations varied the volume of the SNM and neutron source strength in the MCNP data card to conduct an uncertainty analysis. Photopeaks identified include K-shell X-rays from 235U and 239Pu, 61 keV from fission, 2.223 MeV prompt gamma from hydrogen, 511 keV annihilation, and a single and double escape peak from the prompt gamma interaction from hydrogen. Relationships between peak-to-total and peak-to-background as a function of SNM and particle history were investigated to aid in the analysis. The capabilities of both detector systems to acquire well resolved photopeak with a 5% relative error or less, with a 1 Ci source activity, and a peak-to-background ratio of 1.15. This was determined to take 326 s for LaBr3 and 163 s for HPGe which is comparable to current methods for material detection which take between 100 and 900 s to acquire.
Recommended Citation
K. M. Paaren et al., "Active Interrogation of Special Nuclear Material Containers using AmBe Quasi-Forward Biased Directional Source and PGNAA," Applied Radiation and Isotopes, vol. 156, Elsevier Ltd, Feb 2020.
The definitive version is available at https://doi.org/10.1016/j.apradiso.2019.108974
Department(s)
Nuclear Engineering and Radiation Science
Research Center/Lab(s)
Center for Research in Energy and Environment (CREE)
Keywords and Phrases
AmBe; Angular Distribution; MCNP; NJOY; Simulation; TENDL
International Standard Serial Number (ISSN)
0969-8043
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2020 Elsevier Ltd, All rights reserved.
Publication Date
01 Feb 2020
Comments
This work is funded by the DOE NEUP Fellowship.