본문 바로가기
KERD
논문KCI 등재

A methodology to quantify effects of constitutive equations on safety analysis using integral effect test data

0

조회

0

다운로드

0

인용

0

참고문헌

키워드

주제분류원자력공학

초록

To improve the predictive capability of a nuclear thermal hydraulic safety analysis code by developing a better constitutive equation for individual phenomenon has been the general research direction until now. This paper proposes a new method to directly use complex experimental data obtained from integral effect test (IET) to improve constitutive models holistically and simultaneously. The method relies on the sensitivity of a simulation result of IET data to the multiple constitutive equations utilized during the simulation, and the sensitivity of individual model determines the direction of modification for the constitutive model. To develop a robust and generalized method, a clustering algorithm using an artificial neural network, sample space size determination using non-parametric statistics, and sampling method of Latin hypercube sampling are used in a combined manner. The value of the proposed methodology is demonstrated by applying the method to the ATLAS DSP-05 IET experiment. A sensitivity of each observation parameter to the constitutive models is analyzed. The new methodology suggested in the study can be used to improve the code prediction results of complex IET data by identifying the direction for constitutive equations to be modified.

Abstract

To improve the predictive capability of a nuclear thermal hydraulic safety analysis code by developing a better constitutive equation for individual phenomenon has been the general research direction until now. This paper proposes a new method to directly use complex experimental data obtained from integral effect test (IET) to improve constitutive models holistically and simultaneously. The method relies on the sensitivity of a simulation result of IET data to the multiple constitutive equations utilized during the simulation, and the sensitivity of individual model determines the direction of modification for the constitutive model. To develop a robust and generalized method, a clustering algorithm using an artificial neural network, sample space size determination using non-parametric statistics, and sampling method of Latin hypercube sampling are used in a combined manner. The value of the proposed methodology is demonstrated by applying the method to the ATLAS DSP-05 IET experiment. A sensitivity of each observation parameter to the constitutive models is analyzed. The new methodology suggested in the study can be used to improve the code prediction results of complex IET data by identifying the direction for constitutive equations to be modified.

참고문헌 (29)

  1. KAERI, "MARS CODE MANUAL Vol, 1 Code Structure, System Models, and Solution Methods", ~ (2009)
  2. KAERI, "MARS CODE MANUAL Vol, 5 Models and Correlations", ~ (2009)
  3. J. C. Chen, "Correlation for boiling heat transfer to saturated fluids in convection flow", Ind. Eng. Chem. Process Des. Dev, 5(3), pp.322~329 (1966)
  4. Y. G. Lee, "Implementation of a new empirical model of steam condensation for the passive containment cooling system into MARS-KS code : application to containment transient analysis", Nucl. Eng. Technol, 53(10), pp.3196~3206 (2021)
  5. J. Y. Lee, "Improvement of the condensation heat transfer model of the MARSKS1. 3 code using a modified diffusion layer model", Prog. Nucl. Energy, 108, pp.260~269 (2018)
  6. C. J. Choi, "Effect of wall friction model on predicting emergency core coolant behavior in upper downcomer with direct vessel safety injection using MARS-KS", Ann. Nucl. Energy, 116, pp.395~406 (2018)
  7. Y. J. Cho, "Assessment of condensation heat transfer model to evaluate performance of the passive auxiliary feedwater system", Nucl. Eng. Technol, 45(6), pp.759~766 (2013)
  8. S. S. Jeon, "Assessment of horizontal in-tube condensation models using MARS code. Part II : annular flow condensation", Nucl. Eng. Des, 262, pp.510~524 (2013)
  9. International Standard Problem No. 38, BETHSY Test 6,9c:Loss of Residual Heat Removal System during Mid-loop Operation, Final Comparison Report, "Kimber George", ~, pp.NEA (1998), CSNI[DOI]
  10. J. Malet, "OECD international standard problem ISP-47 on containment thermal-hydraulics–conclusions of the TOSQAN part", Nucl. Eng. Des, 240(10), pp.3209~3220 (2010)
  11. K. Y. Choi, "A summary of 50th OECD", NEA, Nucl. Eng. Technol, pp.2012, 44(6)[DOI]
  12. Y. S. Kim, "First ATLAS domestic standard problem(DSP-01)for the code assessment", Nucl. Eng. Technol, 43(1), pp.25~44 (2011)
  13. Y. S. Kim, "Second ATLAS domestic standard problem(DSP-02)for a code assessment", Nucl. Eng. Technol, 45(7), pp.871~894 (2013)
  14. K. H. Kang, "Code assessment of ATLAS integral effect test simulating main steam-line break accident of an advanced pressurized water reactor", J. Nucl. Sci. Technol, 55(1), pp.104~112 (2018)
  15. J. Kim, "Comparison of blind and open calculation results for top-slot break LOCA in fourth ATLAS domestic standard problem", Energies, 15(9), pp.3189~ (2022)
  16. Y. S. Park, "Open calculation result of DSP-05 activity utilizing ATLAS test facility with multiple steam generator tube rupture under PAFS operation scenario", Transactions of the Korean Nuclear Society Virtual Spring Meeting (2020)
  17. ChoHwan Oh, "Application of data driven modeling and sensitivity analysis of constitutive equations for improving nuclear power plant safety analysis code", Nucl. Eng. Technol, 55(1), pp.131~143 (2023)
  18. J. Vesanto, "Clustering of the self-organizing map", IEEE Trans. Neural Network, 11(3), pp.586~600 (2000)
  19. P. J. Rousseeuw, "Silhouettes, A graphical aid to the interpretation and validation of cluster analysis", J. Comput. Appl. Math, 20, pp.53~65 (1987)
  20. J. C. Dunn, "A fuzzy relative of the ISODATA process and its use in detecting compact well-separated clusters", J. Cybern, 3(3), pp.32~57 (1973)
  21. N. W. Porter, "Wilks’ formula applied to computational tools : a practical discussion and verification", Ann. Nucl. Energy, 133, pp.129~137 (2019)
  22. M. D. McKay, "A comparison of three methods for selecting values of input variables in the analysis of output from a computer code", Technometrics, 21(2), pp.239~245 (1979)
  23. Description Report of ATLAS Facility and Instrumentation (Second Revision), "Jae Bong Lee", Korea Atomic Energy Research Institute, ~, pp.KAERI (2018), TR7218[DOI]
  24. Insik Kim, "APR1400: evolutionary Korean next generation reactor", 10th International Conference on Nuclear Engineering, ICONE10-22441, pp.845~851 (2009)
  25. Experimental Study on the Multiple Steam Generator Tube Rupture with Passive Auxiliary Feedwater System Operation, "Yusun Park", Korea Atomic Energy Research Institute, ~, pp.KAERI (2020), TR-8010[DOI]
  26. Description Report of ATLAS-PAFS Facility and Instrumentation, "Kyoung-Ho Kang", Korea Atomic Energy Research Institute, ~, pp.KAERI (2014), TR-5545[DOI]
  27. E. Keogh, "Exact indexing of dynamic time warping", Knowl. Inf. Syst, 7(3), pp.358~386 (2005)
  28. Benesty, "Noise Reduction in Speech Processing", pp.1~4 (2009), Springer
  29. C.H. Oh, "Real Time Nuclear Power Plant Operating State Cognitive Algorithm Development Using Dynamic Bayesian Network", Reliability Engineering & System Safety, 198, pp.106879~ (2020)

관련 논문AI추천

Application of data driven modeling and sensitivity analysis of constitutive equations for improving nuclear power plant safety analysis code김도현, 오초환, 이정익한국원자력학회 · Nuclear Engineering and Technology2023 · 제55권 제1호Improvement of the subcooled boiling model using a new net vapor generation correlation inferred from artificial neural networks to predict the void fraction profiles in the vertical channel이태범, 정용훈한국원자력학회 · Nuclear Engineering and Technology2022 · 제54권 제12호Quantitative evaluation of uncertain parameters for thermal-hydraulic experiments based on the COSINE codeFanfan Zhou, Hao Zhang, Lin Chen, Meng Zhao, Yanhua Yang, Yixuan Cheng한국원자력학회 · Nuclear Engineering and Technology2024 · 제56권 제11호Comparative study of constitutive relations implemented in RELAP5 and TRACE – Part I: Methodology & wall friction신성길, 이정익한국원자력학회 · Nuclear Engineering and Technology2022 · 제54권 제9호Application of the machine learning technique for the development of a condensation heat transfer model for a passive containment cooling system김휘융, 유지민, 윤병조, 이동현, 정재준, 홍동진한국원자력학회 · Nuclear Engineering and Technology2022 · 제54권 제6호A machine learning informed prediction of severe accident progressions in nuclear power plants김성중, 송진호한국원자력학회 · Nuclear Engineering and Technology2024 · 제56권 제6호

이 간행물의 다른 논문 (49건)