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

Abstract

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.

Development of prototype induced-fission-based Pu accountancy instrument for safeguards applications

“…Accordingly, nuclear material accountancy (NMA) for the U/TRU product is of great interest in terms of safeguards; however, there are some technical challenges in the nondestructive assay (NDA) of U/TRU products, including high neutron emission yields from spontaneous fission of 244 Cm, neutron multiplication by induced fission from fissile materials ( 235 U, 239 Pu, and 241 Pu), and the complex compositions of U and TRU elements as well as rare earth elements. Because the NDA technique is essential for near-real time accountancy (NRTA) (Pillay, 1989;Burr et al, 2015;Johnson and Ehinger, 2010), a very significant collaborative effort in developing an NDA technique suitable for NMA of the U/TRU product has been made by the Korea Atomic Energy Research Institute in partnership with the Los Alamos National Laboratory. The preferred characteristics of the NDA technique for NMA of the U/ TRU product is (1) a passive method due to the limited availability of the active interrogating source with the higher neutron emission yield than that of the U/TRU product itself and (2) a direct measurement method independent of the Cm ratio technique (Miura and Menlove, 1994) due to the chance of an inconsistent Cm ratio between the input and output materials and the difficulties in measuring the Cm ratio by the NDA technique due to the complex isotopic composition.…”

Comprehensive Uncertainty Quantification in Nuclear Safeguards

“…One common goal is for DP = 1− to be at least 0.95 if ≥ 1 SQ (significant quantity, which is 8 kg for Pu), which is accomplished if ≤ SQ/3.3. If > SQ/3.3, this can be mitigated by reducing measurement errors to achieve ≤ SQ/3.3 (if feasible) and/or by closing the balances more frequently, so there is less nuclear material transferred per balance period, which reduces [38,39]. The DP of other safeguards measures such as enhanced containment and surveillance with smart cameras and/or remote radiation detection is difficult to quantify and is outside the scope of this paper.…”

“…Therefore, one reason for frequent MB accounting is that abrupt diversion over hours or days is very likely to be detected [40]. As a complementary approach that is beyond the scope here, process monitoring [39] methods have the potential to detect off-normal facility operation that could misdirect NM to undeclared locations.…”

“…Recall that NMA evaluates one or more MBs, where the MB is defined for balance period as MB = ( −1 + in, − out, ) − [38,39]. Typically, many measurements are combined to estimate the terms in , begin , out , and end in the MB; therefore, the central limit effect and years of experience suggest that MBs in most facilities will be approximately normally distributed with the mean equal to the true NM loss and standard deviation , which is expressed as ∼ ( , ), where denotes the MB and the notation is a shortened version of MB, .…”

“…Typically, many measurements are combined to estimate the terms in , begin , out , and end in the MB; therefore, the central limit effect and years of experience suggest that MBs in most facilities will be approximately normally distributed with the mean equal to the true NM loss and standard deviation , which is expressed as ∼ ( , ), where denotes the MB and the notation is a shortened version of MB, . A sequence of MBs will be assumed to have approximately a multivariate normal distribution [38][39][40][41][42][43], ( 1 , 2 , . . .…”