Revisiting Statistical Aspects of Nuclear Material Accounting

Abstract

Nuclear material accounting (NMA) is the only safeguards system whose benefits are routinely quantified. Process monitoring (PM) is another safeguards system that is increasingly used, and one challenge is how to quantify its benefit. This paper considers PM in the role of enabling frequent NMA, which is referred to as near-real-time accounting (NRTA). We quantify NRTA benefits using period-driven and data-driven testing. Period-driven testing makes a decision to alarm or not at fixed periods. Data-driven testing decides as the data arrives whether to alarm or continue testing. The difference between period-driven and datad-riven viewpoints is illustrated by using one-year and two-year periods. For both one-year and two-year periods, period-driven NMA using once-per-year cumulative material unaccounted for (CUMUF) testing is compared to more frequent Shewhart and joint sequential cusum testing using either MUF or standardized, independently transformed MUF (SITMUF) data. We show that the data-driven viewpoint is appropriate for NRTA and that it can be used to compare safeguards effectiveness. In addition to providing period-driven and data-driven viewpoints, new features include assessing the impact of uncertainty in the estimated covariance matrix of the MUF sequence and the impact of both random and systematic measurement errors.

The impact of metrology study sample size on uncertainty in IAEA safeguards calculations

“…Because s 2 m is a source of noise in estimating the individual measurement error variances [15], a Bayesian alternative is under investigation to reduce its impact [16]. Also, one could base a statistical test for data falsification based on the relative differences between operator and inspector measurements d = (o À i)/o in which case an alternate expression to equation (2) for s D that does not involve the product variability s 2 m would be used.…”

“…, and s 2 m needed in equation (2). The second sample size n 2 is the number of operator's declared measurements randomly selected for verification by the inspector.…”

“…Avenhaus and Canty [1] describe quantitative diversion detection options for NMA data, which can be regarded as time series of residuals. For example, NMA at large throughput facilities closes the material balance (MB) approximately every 10 to 30 days around an entire material balance area, which typically consists of multiple process stages [2,3].…”

Calibration of Nondestructive Assay Instruments: An Application of Linear Regression and Propagation of Variance

“…Materials control and accounting systems for nuclear safeguards typically estimate random and systematic error variances from either the internals of the measurement process, calibration data (as presented here), measurement control data, or measurement comparison data [2] [5] [13]. We are not aware of published studies showing how such variance estimates vary across the four data sources, but it is usually assumed that measurement comparison data (that provides for inter-comparison of different measurement techniques), are necessary in order to monitor for model departure effects that the three other data sources are unlikely to detect unless experiments are designed and conducted with field conditions in mind.…”

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

“…PM data is often only an indirect measurement of the SNM, or is a direct measurement of bulk mass that includes SNM and non-SNM. PM data is typically used as a qualitative measure to supplement NMA, or to support indirect estimation of difficult-to-measure inventory for NMA [1][2][3][4][5][6][7][8][9][10][11][12].…”