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Title: Expectation-propagation for weak radionuclide identification at radiation portal monitors

Abstract

We propose a sparsity-promoting Bayesian algorithm capable of identifying radionuclide signatures from weak sources in the presence of a high radiation background. The proposed method is relevant to radiation identification for security applications. In such scenarios, the background typically consists of terrestrial, cosmic, and cosmogenic radiation that may cause false positive responses. We evaluate the new Bayesian approach using gamma-ray data and are able to identify weapons-grade plutonium, masked by naturally-occurring radioactive material (NORM), in a measurement time of a few seconds. We demonstrate this identification capability using organic scintillators (stilbene crystals and EJ-309 liquid scintillators), which do not provide direct, high-resolution, source spectroscopic information. Compared to the EJ-309 detector, the stilbene-based detector exhibits a lower identification error, on average, owing to its better energy resolution. Organic scintillators are used within radiation portal monitors to detect gamma rays emitted from conveyances crossing ports of entry. The described method is therefore applicable to radiation portal monitors deployed in the field and could improve their threat discrimination capability by minimizing “nuisance” alarms produced either by NORM-bearing materials found in shipped cargoes, such as ceramics and fertilizers, or radionuclides in recently treated nuclear medicine patients.

Authors:
 [1];  [2];  [3];  [4];  [5];  [1];  [6];  [4]
  1. Heriot-Watt Univ., Edinburgh, Scotland (United Kingdom). School of Engineering and Physical Sciences
  2. Univ. of Illinois at Urbana-Champaign, IL (United States). Dept. of Nuclear, Plasma and Radiological Engineering
  3. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  4. Univ. of Michigan, Ann Arbor, MI (United States). Dept. of Nuclear Engineering and Radiological Sciences
  5. Univ. of Edinburgh, Scotland (United Kingdom). School of Engineering
  6. Univ. of Michigan, Ann Arbor, MI (United States). Dept. of Electrical Engineering and Computer Science
Publication Date:
Research Org.:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Univ. of Michigan, Ann Arbor, MI (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA), Office of Nonproliferation and Verification Research and Development
OSTI Identifier:
1623429
Alternate Identifier(s):
OSTI ID: 1698011
Report Number(s):
LA-UR-19-30505
Journal ID: ISSN 2045-2322
Grant/Contract Number:  
89233218CNA000001; NA0003920
Resource Type:
Accepted Manuscript
Journal Name:
Scientific Reports
Additional Journal Information:
Journal Volume: 10; Journal Issue: 1; Journal ID: ISSN 2045-2322
Publisher:
Nature Publishing Group
Country of Publication:
United States
Language:
English
Subject:
38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEAR CHEMISTRY

Citation Formats

Altmann, Yoann, Di Fulvio, Angela, Paff, Marc G., Clarke, Shaun D., Davies, Mike E., McLaughlin, Stephen, Hero, Alfred O., and Pozzi, Sara A. Expectation-propagation for weak radionuclide identification at radiation portal monitors. United States: N. p., 2020. Web. doi:10.1038/s41598-020-62947-3.
Altmann, Yoann, Di Fulvio, Angela, Paff, Marc G., Clarke, Shaun D., Davies, Mike E., McLaughlin, Stephen, Hero, Alfred O., & Pozzi, Sara A. Expectation-propagation for weak radionuclide identification at radiation portal monitors. United States. doi:https://doi.org/10.1038/s41598-020-62947-3
Altmann, Yoann, Di Fulvio, Angela, Paff, Marc G., Clarke, Shaun D., Davies, Mike E., McLaughlin, Stephen, Hero, Alfred O., and Pozzi, Sara A. Wed . "Expectation-propagation for weak radionuclide identification at radiation portal monitors". United States. doi:https://doi.org/10.1038/s41598-020-62947-3. https://www.osti.gov/servlets/purl/1623429.
@article{osti_1623429,
title = {Expectation-propagation for weak radionuclide identification at radiation portal monitors},
author = {Altmann, Yoann and Di Fulvio, Angela and Paff, Marc G. and Clarke, Shaun D. and Davies, Mike E. and McLaughlin, Stephen and Hero, Alfred O. and Pozzi, Sara A.},
abstractNote = {We propose a sparsity-promoting Bayesian algorithm capable of identifying radionuclide signatures from weak sources in the presence of a high radiation background. The proposed method is relevant to radiation identification for security applications. In such scenarios, the background typically consists of terrestrial, cosmic, and cosmogenic radiation that may cause false positive responses. We evaluate the new Bayesian approach using gamma-ray data and are able to identify weapons-grade plutonium, masked by naturally-occurring radioactive material (NORM), in a measurement time of a few seconds. We demonstrate this identification capability using organic scintillators (stilbene crystals and EJ-309 liquid scintillators), which do not provide direct, high-resolution, source spectroscopic information. Compared to the EJ-309 detector, the stilbene-based detector exhibits a lower identification error, on average, owing to its better energy resolution. Organic scintillators are used within radiation portal monitors to detect gamma rays emitted from conveyances crossing ports of entry. The described method is therefore applicable to radiation portal monitors deployed in the field and could improve their threat discrimination capability by minimizing “nuisance” alarms produced either by NORM-bearing materials found in shipped cargoes, such as ceramics and fertilizers, or radionuclides in recently treated nuclear medicine patients.},
doi = {10.1038/s41598-020-62947-3},
journal = {Scientific Reports},
number = 1,
volume = 10,
place = {United States},
year = {2020},
month = {4}
}

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