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

Tom Burr, Michael S. Hamada, Larry Ticknor and James Sprinkle
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Tom Burr: Statistical Sciences, F600, Los Alamos National Laboratory, Los Alamos, NM 87545, USA
Michael S. Hamada: Statistical Sciences, F600, Los Alamos National Laboratory, Los Alamos, NM 87545, USA
Larry Ticknor: Statistical Sciences, F600, Los Alamos National Laboratory, Los Alamos, NM 87545, USA
James Sprinkle: Systems Design and Analysis, C921, Los Alamos National Laboratory, Los Alamos, NM 87545, USA

Energies, 2015, vol. 8, issue 1, 1-28

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.

Keywords: data driven; hybrid method; nuclear material accounting; period driven; process monitoring; residuals; statistical methods; time series (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2015
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