A Hierarchical Bayesian Approach to Neutron Spectrum Unfolding With Organic Scintillators

Zhu, Haonan; Altmann, Yoann; Fulvio, Angela Di; McLaughlin, Stephen; Pozzi, Sara; Hero, Alfred

doi:10.1109/TNS.2019.2941317

Title: A Hierarchical Bayesian Approach to Neutron Spectrum Unfolding With Organic Scintillators

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Abstract

We propose a hierarchical Bayesian model and a state-of-the-art Monte Carlo sampling method to solve the unfolding problem, i.e., to estimate the spectrum of an unknown neutron source from the data detected by an organic scintillator. Inferring neutron spectra is important for several applications, including nonproliferation and nuclear security, as it allows the discrimination of fission sources in special nuclear material (SNM) from other types of neutron sources based on the differences of the emitted neutron spectra. Organic scintillators interact with neutrons mostly via elastic scattering on hydrogen nuclei and therefore partially retain neutron energy information. Consequently, the neutron spectrum can be derived through deconvolution of the measured light-output spectrum and the response functions of the scintillator to monoenergetic neutrons. The proposed approach is compared to three existing methods using the simulated data to enable controlled benchmarks. We consider three sets of detector responses. One set corresponds to a 2.5-MeV monoenergetic neutron source and two sets are associated with (energywise) continuous neutron sources (²⁵²Cf and ²⁴¹AmBe). Our results show that the proposed method has similar or better unfolding performance compared with other iterative or Tikhonov regularization-based approaches in terms of accuracy and robustness against limited detection events while requiring lessmore »« less

Authors:

;

; Hero, Alfred

Publication Date:: Tue Oct 01 00:00:00 EDT 2019

Research Org.:: Univ. of Michigan, Ann Arbor, MI (United States)

Sponsoring Org.:: USDOE National Nuclear Security Administration (NNSA)

OSTI Identifier:: 1812845

Alternate Identifier(s):: OSTI ID: 1798669; OSTI ID: 1861153

Grant/Contract Number:: NA0002534; 31310019M0011

Resource Type:: Published Article

Journal Name:: IEEE Transactions on Nuclear Science

Additional Journal Information:: Journal Name: IEEE Transactions on Nuclear Science Journal Volume: 66 Journal Issue: 10; Journal ID: ISSN 0018-9499

Publisher:: Institute of Electrical and Electronics Engineers

Country of Publication:: United States

Language:: English

Subject:: 73 NUCLEAR PHYSICS AND RADIATION PHYSICS; Bayesian inference; markov chain Monte Carlo (MCMC) methods; organic scintillators; spectral unfolding

Citation Formats


                    Zhu, Haonan, Altmann, Yoann, Fulvio, Angela Di, McLaughlin, Stephen, Pozzi, Sara, and Hero, Alfred. A Hierarchical Bayesian Approach to Neutron Spectrum Unfolding With Organic Scintillators.  United States: N. p., 2019. 
Web.  doi:10.1109/TNS.2019.2941317.

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                    Zhu, Haonan, Altmann, Yoann, Fulvio, Angela Di, McLaughlin, Stephen, Pozzi, Sara, & Hero, Alfred. A Hierarchical Bayesian Approach to Neutron Spectrum Unfolding With Organic Scintillators.  United States.  https://doi.org/10.1109/TNS.2019.2941317

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                    Zhu, Haonan, Altmann, Yoann, Fulvio, Angela Di, McLaughlin, Stephen, Pozzi, Sara, and Hero, Alfred. Tue .  
"A Hierarchical Bayesian Approach to Neutron Spectrum Unfolding With Organic Scintillators".  United States.  https://doi.org/10.1109/TNS.2019.2941317.

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@article{osti_1812845,

  title        = {A Hierarchical Bayesian Approach to Neutron Spectrum Unfolding With Organic Scintillators},

  author       = {Zhu, Haonan and Altmann, Yoann and Fulvio, Angela Di and McLaughlin, Stephen and Pozzi, Sara and Hero, Alfred},

  abstractNote = {We propose a hierarchical Bayesian model and a state-of-the-art Monte Carlo sampling method to solve the unfolding problem, i.e., to estimate the spectrum of an unknown neutron source from the data detected by an organic scintillator. Inferring neutron spectra is important for several applications, including nonproliferation and nuclear security, as it allows the discrimination of fission sources in special nuclear material (SNM) from other types of neutron sources based on the differences of the emitted neutron spectra. Organic scintillators interact with neutrons mostly via elastic scattering on hydrogen nuclei and therefore partially retain neutron energy information. Consequently, the neutron spectrum can be derived through deconvolution of the measured light-output spectrum and the response functions of the scintillator to monoenergetic neutrons. The proposed approach is compared to three existing methods using the simulated data to enable controlled benchmarks. We consider three sets of detector responses. One set corresponds to a 2.5-MeV monoenergetic neutron source and two sets are associated with (energywise) continuous neutron sources (252Cf and 241AmBe). Our results show that the proposed method has similar or better unfolding performance compared with other iterative or Tikhonov regularization-based approaches in terms of accuracy and robustness against limited detection events while requiring less user supervision. The proposed method also provides a posteriori confidence measures, which offers additional information regarding the uncertainty of the measurements and the extracted information.},

  doi          = {10.1109/TNS.2019.2941317},

  journal      = {IEEE Transactions on Nuclear Science},

  number       = 10,

  volume       = 66,

  place        = {United States},

  year         = {Tue Oct 01 00:00:00 EDT 2019},

  month        = {Tue Oct 01 00:00:00 EDT 2019}

}

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