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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 (NA-22)
OSTI Identifier:
1623429
Alternate Identifier(s):
OSTI ID: 1698011; OSTI ID: 1798675
Report Number(s):
LA-UR-19-30505
Journal ID: ISSN 2045-2322; TRN: US2106879
Grant/Contract Number:  
89233218CNA000001; NA0003920; NA0002534
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. 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. 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 = {Wed Apr 22 00:00:00 EDT 2020},
month = {Wed Apr 22 00:00:00 EDT 2020}
}

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Figures / Tables:

Figure 1 Figure 1: Comparison of light output spectra of 201Tl (left) and 99m$Tc$ (right) sources measured using the EJ-309 (blue curves) and the stilbene (red curves) scintillators. For comparison purposes, the spectra have been normalised to integrate to one.

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Works referenced in this record:

A Hierarchical Bayesian Approach to Neutron Spectrum Unfolding With Organic Scintillators
journal, October 2019

  • Zhu, Haonan; Altmann, Yoann; Fulvio, Angela Di
  • IEEE Transactions on Nuclear Science, Vol. 66, Issue 10
  • DOI: 10.1109/TNS.2019.2941317

Expectation propagation in linear regression models with spike-and-slab priors
journal, December 2014

  • Hernández-Lobato, José Miguel; Hernández-Lobato, Daniel; Suárez, Alberto
  • Machine Learning, Vol. 99, Issue 3
  • DOI: 10.1007/s10994-014-5475-7

On expectation propagation for generalised, linear and mixed models
journal, March 2018

  • Kim, Andy S. I.; Wand, Matt P.
  • Australian & New Zealand Journal of Statistics, Vol. 60, Issue 1
  • DOI: 10.1111/anzs.12199

Energy resolution experiments of conical organic scintillators and a comparison with Geant4 simulations
journal, August 2018

  • Sosa, C. S.; Thompson, S. J.; Chichester, D. L.
  • Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, Vol. 898
  • DOI: 10.1016/j.nima.2018.04.058

Bayesian Restoration of High-Dimensional Photon-Starved Images
conference, September 2018


Passive assay of plutonium metal plates using a fast-neutron multiplicity counter
journal, May 2017

  • Di Fulvio, A.; Shin, T. H.; Jordan, T.
  • Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, Vol. 855
  • DOI: 10.1016/j.nima.2017.02.082

Naturally occurring radioactive materials and medical isotopes at border crossings
conference, January 2003

  • Kouzes, R. T.; Ely, J. H.; Geelhood, B. D.
  • 2003 IEEE Nuclear Science Symposium. Conference Record (IEEE Cat. No.03CH37515)
  • DOI: 10.1109/NSSMIC.2003.1351967

A comparison of machine learning methods for automated gamma-ray spectroscopy
journal, February 2020

  • Kamuda, Mark; Zhao, Jifu; Huff, Kathryn
  • Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, Vol. 954
  • DOI: 10.1016/j.nima.2018.10.063

Simultaneous Source Detection and Analysis Using a Zero-inflated Count Rate Model
journal, January 2015


The response of radiation portal monitors to medical radionuclides at border crossings
journal, May 2006


Improved neutron–gammadiscrimination at low-light output events using conical trans-stilbene
journal, February 2019

  • Sosa, C. S.; Thompson, S. J.; Chichester, D. L.
  • Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, Vol. 916
  • DOI: 10.1016/j.nima.2018.10.186

The spectral image processing system (SIPS)—interactive visualization and analysis of imaging spectrometer data
journal, May 1993


Robust Spectral Unmixing of Sparse Multispectral Lidar Waveforms Using Gamma Markov Random Fields
journal, December 2017

  • Altmann, Yoann; Maccarone, Aurora; McCarthy, Aongus
  • IEEE Transactions on Computational Imaging, Vol. 3, Issue 4
  • DOI: 10.1109/TCI.2017.2703144

Warhead verification as inverse problem: Applications of neutron spectrum unfolding from organic-scintillator measurements
journal, August 2016

  • Lawrence, Chris C.; Febbraro, Michael; Flaska, Marek
  • Journal of Applied Physics, Vol. 120, Issue 6
  • DOI: 10.1063/1.4960131

Neutron scintillation detectors for environmental, security and geological studies
conference, October 2007

  • Baker, James H.; Galunov, Nikolai Z.; Tarasenko, Oleg A.
  • 2007 IEEE Nuclear Science Symposium Conference Record
  • DOI: 10.1109/NSSMIC.2007.4437253

Detection of radioactive sources in urban scenes using Bayesian Aggregation of data from mobile spectrometers
journal, April 2016


Overview of portal monitoring at border crossings
conference, January 2003

  • Geelhood, B. D.; Ely, J. H.; Hansen, R. R.
  • 2003 IEEE Nuclear Science Symposium. Conference Record (IEEE Cat. No.03CH37515)
  • DOI: 10.1109/NSSMIC.2003.1352095

A systematic analysis of performance measures for classification tasks
journal, July 2009


Compressible Distributions for High-Dimensional Statistics
journal, August 2012

  • Gribonval, Rémi; Cevher, Volkan; Davies, Mike E.
  • IEEE Transactions on Information Theory, Vol. 58, Issue 8
  • DOI: 10.1109/TIT.2012.2197174

Works referencing / citing this record:

Sparse discriminative latent characteristics for predicting cancer drug sensitivity from genomic features
journal, May 2019