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A study on the uncertainty of setpoint for reactor trip system of NPPs considering rectangular distributions

  • Youngho Jin (Global Institute for Nuclear Initiative Strategy) ;
  • Jae-Yong Lee (Department of Quantum and Nuclear Engineering, Sejong University) ;
  • Oon-Pyo Zhu (Global Institute for Nuclear Initiative Strategy)
  • Received : 2023.04.19
  • Accepted : 2023.12.18
  • Published : 2024.05.25

Abstract

The setpoint of the reactor trip system shall be set to consider the measurement uncertainty of the instrument channel and provide a reasonable and sufficient margin between the analytical limit and the trip setpoint. A comparative analysis was conducted to find out an appropriate uncertainty combination method through an example problem. The four methods were evaluated; 1) ISA-67.04.01 method, 2) the GUM95 method, 3) the modified GUM method developed by Fotowicz, and 4) the modified IEC61888 method proposed by authors for the pressure instrument channel presented in ISA-RP67.04.02 example. The appropriateness of each method was validated by comparing it with the result of Monte Carlo simulation. As a result of the evaluation, all methods are appropriate when all measurement uncertainty elements are normally distributed as expected. But ISA-67.04 method and GUM95 method overestimated the channel uncertainty if there is a dominant input element with rectangular distribution among the uncertainty input elements. Modified GUM95 methods developed by Fotowicz and modified IEC61888 method by authors are able to produce almost the same level of channel uncertainty as the Monte Carlo method, even when there is a dominant rectangular distribution among the uncertainty components, without computer-assisted simulations.

Keywords

Acknowledgement

This research was supported by Development of Core Technology to improve Nuclear Power Plant Safety Operation Program (Grant No 20224B10100090) funded by Ministry of Trade, Industry and Energy (MOTIE).).

References

  1. IEC 61888, Nuclear Power Plants - Instrumentation Important to Safety - Determination and Maintenance of Trip Setpoints, 2002.
  2. ANSI/ISA, Standard 67.04.01-2018, "Setpoints for Nuclear Safety-Related Instrumentation,", ISA, Research Triangle Park, NC, 2018.
  3. ISO/IEC Guide 98-3, "Uncertainty of Measurement - Part 3: Guide to the Expression of Uncertainty in Measurement" (GUM 95) - and as a JCGM (Joint Committee for Guides in Metrology) Guide (JCGM 100:2008), 2008.
  4. LAC-P14:09, ILAC(International Laboratory Accreditation Cooperation) Policy for Measurement Uncertainty in Calibration, 2020.
  5. ISO/IEC 17025:2017, General Requirements for the Competence of Testing and Calibration Laboratories, 2017.
  6. IEC 115, Application of Uncertainty of Measurement to Conformity Assessment Activities in the Electrotechnical Sector, 2021.
  7. W. Woeger, Probability assignment to systematic deviations by the principle of maximum entropy, IEEE Trans. Instrum. Meas. IM-36 (No.2) (June 1987).
  8. S. Finlayson. https://sgfin.github.io/2017/03/16/Deriving-probability-distributions-using-the-Principle-of-Maximum-Entropy/, 2017.
  9. P. Fotowicz, An analytical method for calculating a coverage interval, Metrologia 43 (2006) 42-45. https://doi.org/10.1088/0026-1394/43/1/006
  10. L. Moszczynski, T. Bielski, Development of analytical method for calculation the expanded uncertainty in convolution of Rectangular and Gaussian distribution, Measurement 46 (2013) 1896-1903. https://doi.org/10.1016/j.measurement.2013.02.013
  11. P. Fotowicz, Methods for calculating the coverage interval based on the Flatten-Gaussian distribution, Measurement 55 (2014) 272-275. https://doi.org/10.1016/j.measurement.2014.05.006
  12. U.S.NRC, Regulatory Guide 1.105, Revision 4, Setpoints for Safety-related Instrumentation, 2021.
  13. ISO/IEC GUIDE 98-3/Suppl, 1 Uncertainty of Measurement Part 3: Guide to the Expression of Uncertainty in Measurement (GUM95) Supplement 1: Propagation of Distributions Using a Monte Carlo Method, 2008.
  14. R.G. Paulo, Guto, et al., Theory and application of Monte Carlo simulation, in: Victor (Wai Kin) Chan (Ed.), Monte Carlo Simulations Applied to Uncertainty in Measurement, Ch.2, 2013, p. 32, https://doi.org/10.5772/53014.
  15. ISA, ISA-RP67.04.02-2010 Methodologies for the Determination of Setpoints for Nuclear Safety-Related Instrumentation, 2010.
  16. C.F. Dietrich, Uncertainty, Calibration and Probability, second ed., Adam Hilger, 1991, pp. 237-239.