본문 바로가기
KERD
논문KCI 등재

Statistical analysis of S-N type environmental fatigue data of Ni-base alloy welds using weibull distribution

1

조회

0

다운로드

0

인용

0

참고문헌

키워드

주제분류원자력공학

초록

In this study, the probabilistic fatigue life model for Ni-base alloys was developed based on the Weibull distribution using statistical analysis of fatigue data reported in NUREG/CR-6909 and the new fatigue data of Alloy 52M/152 and 82/182. The developed Weibull model can consider right-censored data (i.e., non-failed data) and quantify the improved safety (or reliability) based on the level of failure probability. The overall margin in the current fatigue design limit model (ASME design curve þ NUREG/CR-6909 Fen model) is similar to that of the Weibull model with a cumulative failure probability of approximately 2.5%. The margin in the current fatigue design limit model demonstrated inconsistencies for the Ni-base alloy weld data, whereas the Weibull model showed a consistent margin. Therefore, the Weibull model can systematically mitigate the excessive safety margin.

Abstract

In this study, the probabilistic fatigue life model for Ni-base alloys was developed based on the Weibull distribution using statistical analysis of fatigue data reported in NUREG/CR-6909 and the new fatigue data of Alloy 52M/152 and 82/182. The developed Weibull model can consider right-censored data (i.e., non-failed data) and quantify the improved safety (or reliability) based on the level of failure probability. The overall margin in the current fatigue design limit model (ASME design curve þ NUREG/CR-6909 Fen model) is similar to that of the Weibull model with a cumulative failure probability of approximately 2.5%. The margin in the current fatigue design limit model demonstrated inconsistencies for the Ni-base alloy weld data, whereas the Weibull model showed a consistent margin. Therefore, the Weibull model can systematically mitigate the excessive safety margin.

참고문헌 (47)

  1. Effect of LWR Water Environments on the Fatigue Life of Reactor Materials, "O. K. Chopra", United States Nuclear Regulatory Commission, Office of Nuclear Regulatory, ~, pp.NUREG (2018), CR-6909, Rev. 1
  2. Jun Gao, "Environmental fatigue correction factor model for domestic nuclear-grade low-alloy steel", Nuclear Engineering and Technology, 53(8), pp.2600~2609 (2021), 한국원자력학회[DOI]
  3. Rules for Construction on Nuclear Facility Components: Supports. III. Division 1-Subsection NF, "ASME", American Society of Mechanical Engineers, ~ (2013)
  4. Weld Residual Stress Finite Element Analysis Validation: Part 1 e Data Development Effort, "M. Benson", ~, pp.NUREG-2162 (2014)
  5. S. Mohanty, "Tensile behavior of 82", 182filler, butter and heat-affected-zones in a 508 LAS-316 SS dissimilar weld:tensile test, material model and finite element model validation, 2019, ~[DOI]
  6. H. P. Seifert, "Corrosion fatigue crack growth behaviour of austenitic stainless steels under light water reactor conditions", Corrosion Science, 55, pp.61~75 (2012)
  7. H. P. Seifert, "Corrosion fatigue initiation and short crack growth behaviour of austenitic stainless steels under light water reactor conditions", Corros Sci, 59, pp.20~34 (2012)
  8. H. P. Seifert, "Effect of static load hold periods on the corrosion fatigue behavior of austenitic stainless steels in simulated BWR environments", Proceedings of the 15th International Conference on Environmental Degradation of Materials in Nuclear Power SystemsdWater Reactors, pp.547~560 (2011), Springer
  9. C. Jang, "Effects of microstructure and residual stress on fatigue crack growth of stainless steel narrow gap welds", Materials & Design, 31, pp.1862~1870 (2010)
  10. H. Cho, "Fatigue life and crack growth mechanisms of the type 316LN austenitic stainless steel in 310 C deoxygenated water", J Nucl Sci Technol, 44, pp.1007~1014 (2007)
  11. H. Cho, "Low cycle fatigue behaviors of type 316LN austenitic stainless steel in 310 C deaerated waterefatigue life and dislocation structure development", Materials Science and Engineering : A, 476, pp.248~256 (2008)
  12. J. -D. Hong, "Low cycle fatigue behavior of alloy 690 in simulated PWR waterdeffects of dynamic strain aging and hydrogen", Materials Science and Engineering : A, 611, pp.37~44 (2014)
  13. S. Xu, "Crack initiation mechanisms for low cycle fatigue of type 316Ti stainless steel in high temperature water", Materials Science and Engineering : A, 490, pp.16~25 (2008)
  14. X. Wu, "Strain-rate dependence of low cycle fatigue behavior in a simulated BWR environment", Corros Sci, 47, pp.1415~1428 (2005)
  15. Guidelines for evaluating the effects of light-water reactor water environments in fatigue analysis of metal components, "U.S.N.R. Commission", ~, pp.Regulatory Guide 1 (2018)
  16. Environmental Fatigue Evaluation Method for Nuclear Power Plants, , ~, pp.JNES-SS-1005 (2011)
  17. C. Faidy, "Status of French road map to improve environmental fatigue rules", Pressure Vessels and Piping Conference, pp.567~573 (2012)
  18. B. Sudret, "Probabilistic assessment of thermal fatigue in nuclear components", Nuclear Engineering and Design, 235, pp.1819~1835 (2005)
  19. B. Sudret, "Probabilistic assessment of fatigue life including statistical uncertainties in the SN curve", 17th International Conference on Structural Mechanics in Reactor Technology (SMiRT 17), pp.2803~2811 (2003)
  20. J. P. Park, "Weibull and bootstrap-based data-analytics framework for fatigue life prognosis of the pressurized water nuclear reactor component under harsh reactor coolant environment", Journal of Nondestructive Evaluation, Diagnostics and Prognostics of Engineering Systems, 3 (2020)
  21. J.P. Park, "Weibull and bootstrap based probabilistic fatigue life modeling of stainless steel under PWR coolant water environment condition", 19th International Conference on Environmental Degradation of Materials in Nuclear Power Systems - Water Reactors, pp.1036~1042 (2019)
  22. Y. Ai, "Probabilistic modelling of notch and size effect of components under fatigue loadings", Procedia Structural Integrity, 22, pp.70~77 (2019)
  23. J. Ham, "Low cycle fatigue life of alloy 52M weld metal in simulated PWR environment", Transactions of the Korean Nuclear Society Virtual Spring Meeting (2021), Korean Nuclear Society
  24. Tensile and Fatigue Testing and Material Hardening Model Development for 508 LAS Base Metal and 316SS Similar Metal Weld under In-Air and PWR Primary Loop Water Conditions, "S. Mohanty", Argonne National Lab.(ANL), ~, pp.ANL (2015), LWRS-15[DOI]
  25. Development of Digital Twin Predictive Model for PWR Components: Updates on Multi Times Series Temperature Prediction Using Recurrent Neural Network, DMW Fatigue Tests, System Level Thermal-Mechanical-Stress Analysis, "S. Mohanty", Argonne National Lab.(ANL), ~, pp.ANL (2021), LWRS-21[DOI]
  26. Standard Practice for Strain-Controlled Fatigue Testing, "ASTM International", ASTM, ~, pp.E606-04 (2017)
  27. B. V. Gnedenko, "On a local limit theorem of the theory of probability", Uspekhi Matematicheskikh Nauk, 3, pp.187~194 (1948)
  28. R. A. Fisher, "Mathematical Proceedings of the Cambridge Philosophical Society", pp.180~190 (1928), Cambridge University Press
  29. "Extremes" (2014)[URL]
  30. W. Weibull, "Wide applicability", J Appl Mech, 103, pp.293~297 (1951)
  31. Jae Park, "Uncertainty Evaluation of Weibull Estimators through Monte Carlo Simulation: Applications for Crack Initiation Testing", Materials, 9(7), pp.521~ (2016), MDPI AG[DOI]
  32. Jae Park, "Effects of Cracking Test Conditions on Estimation Uncertainty for Weibull Parameters Considering Time-Dependent Censoring Interval", Materials, 10(1), pp.3~ (2016), MDPI AG[DOI]
  33. 박재필, "Statistical analysis of parameter estimation of a probabilistic crack initiation model for alloy 182 weld considering right-censored data and the covariate effect", Nuclear Engineering and Technology, 50(1), pp.107~115 (2018), 한국원자력학회
  34. J. I. McCool, "Using the Weibull Distribution: Reliability, Modeling, and Inference" (2012), John Wiley & Sons
  35. Z. P. Bazant, "Probabilistic Mechanics of Quasibrittle Structures:Strength, Lifetime, and Size Effect" (2017), Cambridge University Press
  36. M. H. Abdallah, "Reliability Analysis of GFRP Pultruded Composite Rods", International Journal of Quality & Reliability Management (1996)
  37. U. A. Khashaba, "Fatigue and reliability analysis of unidirectional GFRP composites under rotating bending loads", J Compos Mater, 37, pp.317~331 (2003)
  38. R. Sakin, "Statistical analysis of bending fatigue life data using Weibull distribution in glass-fiber reinforced polyester composites", Materials & Design, 29, pp.1170~1181 (2008)
  39. M. Goto, "Statistical investigation of the behaviour of small cracks and fatigue life in carbon steels with different ferrite grain sizes", Fatigue & Fracture of Engineering Materials & Structures, 17, pp.635~649 (1994)
  40. M. S. Kumar, "Analytical and experimental studies on fatigue life prediction of steel and composite multi-leaf spring for light passenger vehicles using life data analysis", Materials Science, 13, pp.141~146 (2007)
  41. L. M. Leemis, "Reliability : Probabilistic Models and Statistical Methods" (1995), Prentice-Hall
  42. U. Genschel, "A comparison of maximum likelihood and medianrank regression for Weibull estimation", Quality Engineering, 22, pp.236~255 (2010)
  43. D. Bertsimas, "Simulated annealing", Statistical Science, 8, pp.10~15 (1993)
  44. S.S. Rao, "Engineering Optimization: Theory and Practice" (2019), John Wiley & Sons
  45. Y. Liu, "Practical Applications of Bayesian Reliability" (2019), John Wiley & Sons
  46. J. F. Lawless, "Statistical Models and Methods for Lifetime Data" (2011), John Wiley &Sons
  47. 팔라크 다위 파이지로르, "Bayesian approach for prediction of primary water stress corrosion cracking in Alloy 690 steam generator tubing", Nuclear Engineering and Technology, 54(9), pp.3225~3234 (2022), 한국원자력학회[DOI]

관련 논문AI추천

이 간행물의 다른 논문 (41건)