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Hybrid Statistical Testing for Nuclear Material Accounting Data and/or Process Monitoring Data in Nuclear Safeguards

Author

Listed:
  • Tom Burr

    (Statistical Sciences, F600, Los Alamos National Laboratory, Los Alamos, NM 87545, USA
    The authors contributed equally to this work.)

  • Michael S. Hamada

    (Statistical Sciences, F600, Los Alamos National Laboratory, Los Alamos, NM 87545, USA
    The authors contributed equally to this work.)

  • Larry Ticknor

    (Statistical Sciences, F600, Los Alamos National Laboratory, Los Alamos, NM 87545, USA
    The authors contributed equally to this work.)

  • James Sprinkle

    (Systems Design and Analysis, C921, Los Alamos National Laboratory, Los Alamos, NM 87545, USA
    The authors contributed equally to this work.)

Abstract

The aim of nuclear safeguards is to ensure that special nuclear material is used for peaceful purposes. Historically, nuclear material accounting (NMA) has provided the quantitative basis for monitoring for nuclear material loss or diversion, and process monitoring (PM) data is collected by the operator to monitor the process. PM data typically support NMA in various ways, often by providing a basis to estimate some of the in-process nuclear material inventory. We develop options for combining PM residuals and NMA residuals (residual = measurement − prediction), using a hybrid of period-driven and data-driven hypothesis testing. The modified statistical tests can be used on time series of NMA residuals (the NMA residual is the familiar material balance), or on a combination of PM and NMA residuals. The PM residuals can be generated on a fixed time schedule or as events occur.

Suggested Citation

  • Tom Burr & Michael S. Hamada & Larry Ticknor & James Sprinkle, 2015. "Hybrid Statistical Testing for Nuclear Material Accounting Data and/or Process Monitoring Data in Nuclear Safeguards," Energies, MDPI, vol. 8(1), pages 1-28, January.
    • Handle: RePEc:gam:jeners:v:8:y:2015:i:1:p:501-528:d:44642
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