Title

Comparison of Active Interrogation Methods for Source Location in a Scattering and Absorbing Medium, Consisting of PGNAA, and an AmBe Quasi-Forward Biased Directional Source

Abstract

Source location of Special Nuclear Material (SNM) encompassing 95% 235U and 239Pu is identified by utilizing a directional source from Patent No: US20190013109A1 using Prompt Gamma Neutron Activation Analysis (PGNAA) and neutron spectroscopy simulated with Monte-Carlo N-Particle transport 6.2 (MCNP). BC-408, HPGe, LaBr3 detector arrays were used to identify the location of the SNM using total counts incident on each detector, and PGNAA photopeaks from HPGe and LaBr3 detector arrays in a polyethylene shield. The conducted simulations varied the volume and location of the SNM in the MCNP input files to observe how the source location method behaved. PGNAA photopeaks used for source identification include 61 keV from fission, 2.223 MeV prompt gamma from hydrogen, 511 keV annihilation, and a single and double escape peaks from the prompt gamma interaction from hydrogen. The capabilities of each detector systems to acquire well resolved photopeaks with a 1% relative error or less, and total relative error for F4 and F8 tallies were less than 0.015% relative error. Source predictions of the SNM with uneven amounts of polyethylene shielding between the source and detectors was observed to overpredict and give invalid source location predictions. Source locations of the SNM with even amounts of polyethylene material between the source and each detector were found to be valid. With a 1 Ci 241Am source activity, it was determined that 1630 s were needed to obtain the results for each detector system with the quasi-forward directional AmBe source. Coupling source and material identification together would increase acquisition time but would only require one system to determine.

Department(s)

Mining and Nuclear Engineering

Keywords and Phrases

AmBe; Angular distribution; MCNP; Simulation; Source location

International Standard Serial Number (ISSN)

0969-8043

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2020 Elsevier, All rights reserved.

Publication Date

01 Jun 2020

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