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

Author

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  • Benjamin L. Johnson

    (Colorado School of Mines)

  • Aaron T. Porter

    (Colorado School of Mines)

  • Jeffrey C. King

    (Colorado School of Mines)

  • Alexandra M. Newman

    (Colorado School of Mines)

Abstract

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 possibly dangerous nuclear material, such as uranium, in a fuel cycle is important because of its possible loss or diversion. 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 at facilities in the fuel cycle. 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 nuclear fuel cycle measurement systems: (i) given location-dependent device precisions, find the configuration of n devices at n locations ( $$n=3$$ n = 3 ) that provides 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 (given the device accuracy is 100%), and (iii) 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 a fixed, detection threshold in the simulation-optimization algorithm reduces the weighted sum of false positive and false negative probabilities.

Suggested Citation

  • Benjamin L. Johnson & Aaron T. Porter & Jeffrey C. King & Alexandra M. Newman, 2019. "Optimally configuring a measurement system to detect diversions from a nuclear fuel cycle," Annals of Operations Research, Springer, vol. 275(2), pages 393-420, April.
  • Handle: RePEc:spr:annopr:v:275:y:2019:i:2:d:10.1007_s10479-018-2940-x
    DOI: 10.1007/s10479-018-2940-x
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    References listed on IDEAS

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    1. Alberto Alesina & Eliana La Ferrara, 2014. "A Test of Racial Bias in Capital Sentencing," American Economic Review, American Economic Association, vol. 104(11), pages 3397-3433, November.
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    Cited by:

    1. Outi Montonen & Ville-Pekka Eronen & Timo Ranta & Jani A. S. Huttunen & Marko M. Mäkelä, 2020. "Multiobjective Mixed Integer Nonlinear Model to Plan the Schedule for the Final Disposal of the Spent Nuclear Fuel in Finland," Mathematics, MDPI, vol. 8(4), pages 1-29, April.

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