DOI QR코드

DOI QR Code

Seismic capacity re-evaluation of the 480V motor control center of South Korea NPPs using earthquake experience and experiment data

  • Choi, Eujeong (Structural Safety and Prognosis Research Division, Korea Atomic Energy Research Institute (KAERI)) ;
  • Kim, Min Kyu (Structural Safety and Prognosis Research Division, Korea Atomic Energy Research Institute (KAERI)) ;
  • Choi, In-Kil (Structural Safety and Prognosis Research Division, Korea Atomic Energy Research Institute (KAERI))
  • Received : 2021.06.07
  • Accepted : 2021.10.03
  • Published : 2022.04.25

Abstract

The recent seismic events that occurred in South Korea have increased the interest in the re-evaluation of the seismic capacity of nuclear power plant (NPP) equipment, which is often conservatively estimated. To date, various approaches-including the Bayesian method proposed by the United States (US) Electric Power Research Institute -have been developed to quantify the seismic capacity of NPP equipment. Among these, the Bayesian approach has advantages in accounting for both prior knowledge and new information to update the probabilistic distribution of seismic capacity. However, data availability and region-specific issues exist in applying this Bayesian approach to Korean NPP equipment. Therefore, this paper proposes to construct an earthquake experience database by combining available earthquake records at Korean NPP sites and the general location of equipment within NPPs. Also, for the better representation of the seismic demand of Korean earthquake datasets, which have distinct seismic characteristics from those of the US at a high-frequency range, a broadband frequency range optimization is suggested. The proposed data construction and seismic demand optimization method for seismic capacity re-evaluation are demonstrated and tested on a 480 V motor control center of a South Korea NPP.

Keywords

Acknowledgement

This work was supported by the Korea Institute of Energy Technology Evaluation and Planning (KETEP) and the Ministry of Trade, Industry, and Energy (MOTIE) of the Republic of Korea (No. 20201510100010).

References

  1. E. Choi, J. Ha, D. Hahm, M. Kim, A review of multihazard risk assessment: progress, potential, and challenges in the application to nuclear power plants, International Journal of Disaster Risk Reduction 53 (2020) 101933. https://doi.org/10.1016/j.ijdrr.2020.101933
  2. E. Choi, S. Kwag, J. Ha, D. Hahm, Development of a two-stage DQFM for efficient single- and multi-hazard risk quantification for nuclear facilities, Energies 14 (4) (2021) 1017. https://doi.org/10.3390/en14041017
  3. S. Kwag, S. Eemb, E. Choi, J.G. Ha, D. Hahm, Toward Improvement of Sampling-Based Seismic Probabilistic Safety Assessment Method for Nuclear Facilities Using Composite Distribution and Adaptive Discretization, Reliability Engineering & System Safety (2021) 107809.
  4. M.K. Kim, I.K. Choi, A shaking table test for an Re-evaluation of seismic fragility of electrical cabinet in NPP, Journal of the Computational Structural Engineering Institute of Korea 24 (3) (2011) 295-305.
  5. M.K. Kim, I.K. Choi, J.M. Seo, A shaking table test for an evaluation of seismic behavior of 480V MCC, Nucl. Eng. Des. 24 (3) (2011) 341-355.
  6. D.D. Nguyen, B. Thusa, H. Park, M.S. Azad, T.H. Lee, Efficiency of various structural modeling schemes on evaluating seismic performance and fragility of APR1400 containment building, Nuclear Engineering and Technology (2021).
  7. S. De Grandis, M. Domaneschi, F. Perotti, A numerical procedure for computing the fragility of NPP components under random seismic excitation, Nucl. Eng. Des. 239 (11) (2009) 2491-2499. https://doi.org/10.1016/j.nucengdes.2009.06.027
  8. F. Perotti, M. Domaneschi, S. De Grandis, The numerical computation of seismic fragility of base-isolated nuclear power plants buildings, Nucl. Eng. Des. 262 (2013) 189-200, 2013. https://doi.org/10.1016/j.nucengdes.2013.04.029
  9. S.J. Chang, Y.S. Jeong, S.H. Eem, I.K. Choi, D.U. Park, Evaluation of MCC seismic response according to the frequency contents through the shake table test, Nuclear Engineering and Technology 53 (4) (2021) 1345-1356. https://doi.org/10.1016/j.net.2020.10.002
  10. K. Aida, Y. Owa, K. Suzuki, S. Fujita, Evaluation of aseismic reliability of actual boiler structures and a study on design of seismic ties based on proof tests using a large scaled shaking table, J. Pressure Vessel Technol. 126 (1) (2004) 46-52. https://doi.org/10.1115/1.1637645
  11. M.K. Kim, J.H. Kim, I.K. Choi, Seismic fragility evaluation of a piping system in a nuclear power plant by shaking table test and numerical analysis, in: Proceedings of the 2012 International Congress on Advances in Nuclear Power Plants, 2012.
  12. Y.J. Lee, D.S. Moon, A new methodology of the development of seismic fragility curves, Smart Struct. Syst. 14 (5) (2014) 847-867. https://doi.org/10.12989/sss.2014.14.5.847
  13. D.S. Kim, S.H. Han, J.H. Park, H.G. Lim, J.H. Kim, Multi-unit Level 1 probabilistic safety assessment: approaches and their application to a six-unit nuclear power plant site, Nuclear Engineering and Technology 50 (8) (2018) 1217-1233. https://doi.org/10.1016/j.net.2018.01.006
  14. Y. Yaguang, S. Russell, Reliability estimation for a digital instrument and control system, Nuclear Engineering and Technology 44 (4) (2012) 405-414. https://doi.org/10.5516/NET.04.2012.513
  15. D.A. Fynan, K.I. Ahn, Implicit treatment of technical specification and thermal hydraulic parameter uncertainties in Gaussian process model to estimate safety margin, Nuclear Engineering and Technology 48 (3) (2016) 684-701. https://doi.org/10.1016/j.net.2016.01.016
  16. Electric Power Research Institute, Updated equipment seismic capacities data for use in fragility calculations, 2017. EPRI Report No. 3002011627.
  17. Electric Power Research Institute, Updated equipment seismic capacities data for use in fragility calculations: phase III incorporation of test data pilot, 2019. EPRI Report No. 3002015996.
  18. M. Bayat, F. Daneshjoo, N. Nistico, A novel pro ficient and sufficient intensity measure for probabilistic analysis of skewed highway bridges, Struct. Eng. Mech. 55 (6) (2015) 1177-1202. https://doi.org/10.12989/sem.2015.55.6.1177
  19. E. Koufoudi, O.J. Ktenidou, F. Cotton, F. Dufour, S. Grange, Empirical ground-motion models adapted to the intensity measure ASA 40, Bull. Earthq. Eng. 13 (12) (2015) 3625-3643. https://doi.org/10.1007/s10518-015-9797-z
  20. J. O'Brien, The NRC research program on seismic component fragilities, Trans. Am. Nucl. Soc. 62 (1990) 404-405.
  21. G.S. Johnson, R.E. Sheppard, M.D. Quilici, S.J. Eder, C.R. Scawthorn, Seismic Reliability Assessment of Critical Facilities: A Handbook, Supporting Documentation, and Model Code Provisions, 1999.
  22. IEEE 344-2004 - IEEE Recommended Practice for Seismic Qualification of Class 1E Equipment for Nuclear Power Generating Stations, IEEE, NY, 2005.
  23. K.L. Merz, Generic Seismic Ruggedness of Power Plant Equipment, No. EPRI-NP-5223-M-REV. 1, 1991.
  24. D. Kana, et al., A Research Program for Seismic Qualification of Nuclear Plant Electrical and Mechanical Equipment, NUREG/CR-3892, Southwest Research Institute, 1984 Aug.
  25. P. Ibanez, et al., A comparison of experimental methods for seismic testing of equipment, Nucl. Eng. Des. 25 (1) (1973).
  26. D. Kana, D. Pomerening, Similarity Principle for Equipment Qualification by Experience, NUREG/CR-5012, Southwest Research Institute, 1988 July.
  27. Electric Power Research Institute, eSQUG Seismic Experience Database, 2017, Version 2.7.
  28. K.K. Bandyopadhyay, C.H. Hofmayer, M.K. Kassir, et al., Seismic Fragility of Nuclear Power Plant Components (No. NUREG/CR-4659), Brookhaven National Laboratory, NY, 1987.
  29. Tae Min Heo, et al., Response spectra of 2017 Pohang earthquake and comparison with Korean standard design spectra, Journal of the Earthquake Engineering Society of Korea 22 (3) (2018) 129-137. https://doi.org/10.5000/EESK.2018.22.3.129
  30. P. Congdon, Applied Bayesian Modelling, vol. 595, John Wiley & Sons, 2014.
  31. Electric Power Research Institute, Seismic Fragility Application Guide Update, EPRI Report No, 2009, p. 1019200.
  32. R.M. Neal, Slice sampling, Annals of Statistics (2003) 705-741.
  33. S. Chib, G. Edward, Understanding the metropolis-hastings algorithm, Am. Statistician 49 (4) (1995) 327-335. https://doi.org/10.2307/2684568
  34. Alan E. Gelfand, Gibbs sampling, J. Am. Stat. Assoc. 95 (452) (2000) 1300-1304. https://doi.org/10.1080/01621459.2000.10474335
  35. Gareth O. Roberts, Adrian FM. Smith, Simple conditions for the convergence of the Gibbs sampler and Metropolis-Hastings algorithms, Stoch. Process. their Appl. 49 (2) (1994) 207-216. https://doi.org/10.1016/0304-4149(94)90134-1