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Overview of the Tolerance Limit Calculations with Application to TSURFER

Author

Listed:
  • Hany Abdel-Khalik

    (School of Nuclear Engineering, Purdue University, West Lafayette, IN 47906, USA)

  • Dongli Huang

    (School of Nuclear Engineering, Purdue University, West Lafayette, IN 47906, USA)

  • Ugur Mertyurek

    (Oak Ridge National Laboratory, Oak Ridge, TN 37830, USA)

  • William Marshall

    (Oak Ridge National Laboratory, Oak Ridge, TN 37830, USA)

  • William Wieselquist

    (Oak Ridge National Laboratory, Oak Ridge, TN 37830, USA)

Abstract

To establish confidence in the results of computerized physics models, a key regulatory requirement is to develop a scientifically defendable process. The methods employed for confidence, characterization, and consolidation , or C 3 , are statistically involved and are often accessible only to avid statisticians. This manuscript serves as a pedagogical presentation of the C 3 process to all stakeholders—including researchers, industrial practitioners, and regulators—to impart an intuitive understanding of the key concepts and mathematical methods entailed by C 3 . The primary focus is on calculation of tolerance limits, which is the overall goal of the C 3 process. Tolerance limits encode the confidence in the calculation results as communicated to the regulator. Understanding the C 3 process is especially critical today, as the nuclear industry is considering more innovative ways to assess new technologies, including new reactor and fuel concepts, via an integrated approach that optimally combines modeling and simulation and minimal targeted validation experiments. This manuscript employs intuitive, analytical, numerical, and visual representations to explain how tolerance limits may be calculated for a wide range of configurations, and it also describes how their values may be interpreted. Various verification tests have been developed to test the calculated tolerance limits and to help delineate their values. The manuscript demonstrates the calculation of tolerance limits for TSURFER, a computer code developed by the Oak Ridge National Laboratory for criticality safety applications. The goal is to evaluate the tolerance limit for TSURFER-determined criticality biases to support the determination of upper, subcritical limits for regulatory purposes.

Suggested Citation

  • Hany Abdel-Khalik & Dongli Huang & Ugur Mertyurek & William Marshall & William Wieselquist, 2021. "Overview of the Tolerance Limit Calculations with Application to TSURFER," Energies, MDPI, vol. 14(21), pages 1-37, October.
  • Handle: RePEc:gam:jeners:v:14:y:2021:i:21:p:7092-:d:668454
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    References listed on IDEAS

    as
    1. Zimmer, Zachary & Park, DoHwan & Mathew, Thomas, 2016. "Tolerance limits under normal mixtures: Application to the evaluation of nuclear power plant safety and to the assessment of circular error probable," Computational Statistics & Data Analysis, Elsevier, vol. 103(C), pages 304-315.
    2. Russell V. Lenth, 1989. "Cumulative Distribution Function of the Noncentral T Distribution," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 38(1), pages 185-189, March.
    3. G. L. Burrows, 1963. "Statistical Tolerance Limits—What are They?," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 12(2), pages 133-144, June.
    4. John Y. Lu, 1960. "Tolerance Interval for Multiple Regression," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 42(4), pages 910-920.
    Full references (including those not matched with items on IDEAS)

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