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Activity Number: 36 - Statistcal Theory and Uncertainty Quantification in Physical Sciences
Type: Contributed
Date/Time: Sunday, July 28, 2019 : 2:00 PM to 3:50 PM
Sponsor: Section on Physical and Engineering Sciences
Abstract #304778 Presentation
Title: An Overview of Statistical Methods Used in Nuclear Safeguards
Author(s): Thomas Burr* and Elisa Bonner and Sarah Michalak and Claude Norman
Companies: Los Alamos National Laboratory and Colorado State University and Los Alamos National Labs and IAEA
Keywords: uncertainty quantification; nuclear safeguards; process monitoring; relative standard deviation
Abstract:

Nuclear safeguards aim to verify that nuclear material (NM) is used only for peaceful purposes. To ensure that States honor safeguards obligations, measurements of NM inventories and flows are needed. Statistical analyses to support conclusions require uncertainty quantification (UQ), usually by estimating the relative standard deviation (RSD) in random and systematic errors of each measurement method. This paper reviews UQ for measurements, construction of tolerance intervals for setting pass/fail criteria for monitored data streams, and estimation of detection probabilities for specified NM misuse scenarios at declared facilities. UQ for measurements is done both empirically using data collected for metrology studies and from applying error variance propagation to all steps in the assay (physics based). Approximate Bayesian computation is used for both the empirical and physics-based UQ. Simple pattern recognition methods are used to detect off-normal operating conditions that could indicate facility misuse. And, NM mass balances (which contain measurement errors) are analyzed sequentially over time.


Authors who are presenting talks have a * after their name.

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