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This content will become publicly available on June 28, 2019

Title: Optimally configuring a measurement system to detect diversions from a nuclear fuel cycle

The civilian nuclear fuel cycle is an industrial process that produces electrical power from the nuclear fission of uranium. Using a measurement system to accurately account for nuclear material, such as uranium, in a fuel cycle is important because of the possible loss or diversion of this potentially dangerous material. A measurement system is defined by a set of measurement methods, or “devices,” used to account for material flows and inventory values at specific locations in the fuel cycle. Here, we develop a simulation-optimization algorithm and an integer-programming model to find the best, or near-best, resource-limited measurement system with a high degree of confidence. The simulation-optimization algorithm minimizes a weighted sum of false positive and false negative diversion-detection probabilities while accounting for material quantities and measurement errors across a finite, discrete time horizon in hypothetical non-diversion and diversion contexts. In each time period, the estimated cumulative material unaccounted for is compared to a fixed or an optimized threshold value to assess if a “significant amount of material” is lost from a measurement system. The integer-programming model minimizes the population variance of the estimated material loss, i.e., material unaccounted for, in a measurement system. We analyze three potential problems in nuclearmore » fuel cycle measurement systems: (i) given location-dependent device precisions, find the configuration of n devices at n locations ( n = 3) that gives the lowest corresponding objective values using the simulation-optimization algorithm and integer-programming model, (ii) find the location at which improving device precision reduces objective values the most using the simulation-optimization algorithm, and determine the effect of measurement frequency on measurement system configurations and objective values using the simulation-optimization algorithm. We obtain comparable results for each problem at least an order of magnitude faster than existing methods do. Using an optimized, rather than fixed, detection threshold in the simulation-optimization algorithm reduces the weighted sum of false positive and false negative probabilities.« less
 [1] ;  [2] ; ORCiD logo [3] ;  [1]
  1. Colorado School of Mines, Golden, CO (United States). Operations Research with Engineering Program
  2. Colorado School of Mines, Golden, CO (United States). Dept. of Applied Mathematics and Statistics
  3. Colorado School of Mines, Golden, CO (United States). Nuclear Engineering Program
Publication Date:
Grant/Contract Number:
Accepted Manuscript
Journal Name:
Annals of Operations Research
Additional Journal Information:
Journal Name: Annals of Operations Research; Journal ID: ISSN 0254-5330
Research Org:
Colorado School of Mines, Golden, CO (United States)
Sponsoring Org:
USDOE National Nuclear Security Administration (NNSA)
Country of Publication:
United States
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS; 98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL PROTECTION; Integer programming; Simulation optimization; Resource allocation; Nuclear safeguards
OSTI Identifier: