Journal of the Computational Structural Engineering Institute of Korea (한국전산구조공학회논문집)

Computational Structural Engineering Institute of Korea (한국전산구조공학회)
권호 표지
DOI QR코드

DOI QR Code

Suggestions for Enhancing Sampling-Based Approach of Seismic Probabilistic Risk Assessment

샘플링기반 지진 확률론적 리스크평가 접근법 개선을 위한 제언

  • Kwag, Shinyoung (Department of Civil & Environmental Engineering, Hanbat National University) ;
  • Eem, Seunghyun (Department of Convergence and Fusion System Engineering, Kyungpook National University) ;
  • Choi, Eujeong (Structural Safety & Prognosis Research Division, Korea Atomic Energy Research Institute) ;
  • Ha, Jeong Gon (Structural Safety & Prognosis Research Division, Korea Atomic Energy Research Institute) ;
  • Hahm, Daegi (Structural Safety & Prognosis Research Division, Korea Atomic Energy Research Institute)
  • 곽신영 (한밭대학교 건설환경공학과) ;
  • 임승현 (경북대학교 융복합시스템공학과 플랜트시스템전공) ;
  • 최유정 (한국원자력연구원 기기구조예측진단연구부) ;
  • 하정곤 (한국원자력연구원 기기구조예측진단연구부) ;
  • 함대기 (한국원자력연구원 기기구조예측진단연구부)
  • Received : 2020.11.05
  • Accepted : 2020.12.12
  • Published : 2021.04.30
Download PDF
⟨ Previous Next ⟩

Abstract

A sampling-based approach was devised as a nuclear seismic probabilistic risk assessment (SPRA) method to account for the partially correlated relationships between components. However, since this method is based on sampling, there is a limitation that a large number of samples must be extracted to estimate the results accurately. Thus, in this study, we suggest an effective approach to improve the existing sampling method. The main features of this approach are as follows. In place of the existing Monte Carlo sampling (MCS) approach, the Latin hypercube sampling (LHS) method that enables effective sampling in multiple dimensions is introduced to the SPRA method. In addition, the degree of segmentation of the seismic intensity is determined with respect to the final seismic risk result. By applying the suggested approach to an actual nuclear power plant as an example, the accuracy of the results were observed to be almost similar to those of the existing method, but the efficiency was increased by a factor of two in terms of the total number of samples extracted. In addition, it was confirmed that the LHS-based method improves the accuracy of the solution in a small sampling region.

원자력시설 SPRA 방법으로서 기기 사이 부분 종속 관계를 정확하게 고려하기 위하여 샘플링기반접근법이 개발된 바 있다. 그러나 이는 샘플링 기반 방법이므로 정확한 지진 리스크 산정을 위하여 많은 수의 샘플을 추출해야 하는 단점이 있다. 이에 따라 본 연구에서는 기존 방법을 개선하기 위한 효과적인 방법을 제안한다. 본 연구에서 제안한 방법의 주요한 특징은 다음과 같다. 기존 샘플링방법인 몬테카를로샘플링(MCS) 방법을 대신하여 다차원에서 효과적인 샘플링이 가능한 라틴하이퍼큐브샘플링(LHS) 방법을 샘플링기반 SPRA에 도입한다. 또한, 기존 지진세기 세분화 정도를 최종 지진 리스크 결과와 연계하여 결정한다. 제안된 방법이 결합된 샘플링기반 SPRA 접근법을 실제 원전 예제에 적용한 결과, 제안된 방법이 기존의 방법과 비교하여 결과 정확도에 있어서 거의 비슷하나 총 샘플 추출수 기준에서 효율성을 약 2배 가량 높이 것을 확인하였다. 또한, 샘플링 개수가 적은 영역에서 LHS 기반 방법이 MCS 기반 방법보다는 해의 정확도를 높이는 것을 확인할 수 있었다.

Keywords

References

  1. Ebisawa, K., Abe, K., Muramatsu, K., Itoh, M., Kohno, K., Tanaka, T. (1994) Evaluation of Response Factors for Seismic Probabilistic Safety Assessment of Nuclear Power Plants, Nucl. Eng. & Des., 147(2), pp.197~210. https://doi.org/10.1016/0029-5493(94)90206-2
  2. Eem, S., Choi, I.K., Cha, S.L., Kwag, S. (2021) Seismic Response Correlation Coefficient for the Structures, Systems and Components of the Korean Nuclear Power Plant for Seismic Probabilistic Safety Assessment, Ann. Nucl. Energy, 150, p.107759. https://doi.org/10.1016/j.anucene.2020.107759
  3. Ellingwood, B. (1990) Validation Studies of Seismic PRAs, Nucl. Eng. & Des., 123, pp.189~196. https://doi.org/10.1016/0029-5493(90)90237-R
  4. EPRI (2002) Seismic Fragility Application Guide, TR-1002988, Electric Power Research Institute.
  5. EPRI (2003) Seismic Probabilistic Risk Assessment Implementation Guide, TR-1002989, Electric Power Research Institute.
  6. EPRI (2018) Seismic Fragility and Seismic Margin Guidance for Seismic Probabilistic Risk Assessments, 3002012994, Electric Power Research Institute.
  7. Kim, J.H., Choi, I-.K., Park, J-.H. (2011) Uncertainty Analysis of System Fragility for Seismic Safety Evaluation of NPP, Nucl. Eng. & Des., 241, pp.2570~2579. https://doi.org/10.1016/j.nucengdes.2011.04.031
  8. Kim, J.H., Kim, S.Y., Choi, I.K. (2020) Combination Procedure for Seismic Correlation Coefficient in Fragility Curves of Multiple Components, J. Earthq. Eng. Soc. Korea, 24(3), pp.141~148. https://doi.org/10.5000/EESK.2020.24.3.141
  9. Kwag, S., Eem, S., Park, J., Choi, I.K. (2020a) Sampling-based Approach for Seismic Probabilistic Risk Assessment, J. Comput. Struct. Eng. Inst. Korea, 33(2), pp.129~136. https://doi.org/10.7734/COSEIK.2020.33.2.129
  10. Kwag, S., Gupta, A. (2017) Probabilistic Risk Assessment Framework for Structural Systems under Multiple Hazards using Bayesian Statistics, Nucl. Eng. & Des.,, 315(4), pp.20~34. https://doi.org/10.1016/j.nucengdes.2017.02.009
  11. Kwag, S., Ha, J.G., Kim, M.K., Kim, J.H. (2019) Development of Efficient External Multi-Hazard Risk Quantification Methodology for Nuclear Facilities, Energies, 12(20), p.3925. https://doi.org/10.3390/en12203925
  12. Kwag, S., Oh, J., Lee, J.M. (2018) Application of Bayesian Statistics to Seismic Probabilistic Safety Assessment for Research Reactor, Nucl. Eng. & Des., 328, pp.166~181. https://doi.org/10.1016/j.nucengdes.2018.01.022
  13. Kwag, S., Oh, J., Lee, J.M., Ryu, J.S. (2017) Bayesian based Seismic Margin Assessment Approach: Application to Research Reactor System, Earthq. & Struct., 12(6), pp.653~663. https://doi.org/10.12989/eas.2017.12.6.653
  14. Kwag, S., Park, J., Choi, I.K. (2020b) Development of Efficient Complete-Sampling-based Seismic PSA Method for Nuclear Power Plant, Reliab. Eng. & Syst. Saf., 197, p.106824. https://doi.org/10.1016/j.ress.2020.106824
  15. Kwag, S., Ryu, Y., Ju, B.S. (2020c) Efficient Seismic Fragility Analysis for Large-Scale Piping System Utilizing Bayesian Approach, Appl. Sci., 10(4), p.1515. https://doi.org/10.3390/app10041515
  16. Oh, J., Kwag, S. (2018) A Study on Seismic Probabilistic Safety Assessment for a Research Reactor, J. Comput. Struct. Eng. Inst. Korea, 31(1), pp.31~38. https://doi.org/10.7734/COSEIK.2018.31.1.31