Acknowledgement
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT: Ministry of Science and ICT) (No. 2019M2A8A100064013) and also supported by the Korea Institute of Energy Technology Evaluation and Planning (KETEP) and the Ministry of Trade, Industry & Energy (MOTIE) of the Republic of Korea (No. 20214000000410). Part of the reported work was also supported through INERI and U.S. Department of Energy's Light Water Reactor Sustainability program under the work package of environmental fatigue study. Part of the reported work has been created by UChicago Argonne, LLC, Operator of Argonne National Laboratory ("Argonne"). Argonne, a U.S. Department of Energy Office of Science laboratory, is operated under Contract No. DE-AC02-06CH11357. The U.S. Government retains for itself, and others acting on its behalf, a paid-up nonexclusive, irrevocable worldwide license in said article to reproduce, prepare derivative works, distribute copies to the public, and perform publicly and display publicly, by or on behalf of the Government.
References
- O.K. Chopra, G.L. Stevens, Effect of LWR Water Environments on the Fatigue Life of Reactor Materials (NUREG/CR-6909, Rev. 1), United States Nuclear Regulatory Commission, Office of Nuclear Regulatory, 2018.
- J. Gao, C. Liu, J. Tan, Z. Zhang, X. Wu, E.H. Han, R. Shen, B. Wang, W. Ke, Environmental fatigue correction factor model for domestic nuclear-grade low-alloy steel, Nuclear Engineering and Technology 53 (2021) 2600-2609, https://doi.org/10.1016/J.NET.2021.02.014.
- ASME, Rules for Construction on Nuclear Facility Components: Supports. III. Division 1-Subsection NF, American Society of Mechanical Engineers, 2013.
- M. Benson, D. Rudland, A. Csontos, Weld Residual Stress Finite Element Analysis Validation: Part 1 - Data Development Effort (NUREG-2162), 2014.
- S. Mohanty, J. Listwan, S. Majumdar, K. Natesan, Tensile behavior of 82/182 filler, butter and heat-affected-zones in a 508 LAS-316 SS dissimilar weld: tensile test, material model and finite element model validation, in: Pressure Vessels and Piping Conference, American Society of Mechanical Engineers, 2019, V001T01A024.
- H.P. Seifert, S. Ritter, H.J. Leber, Corrosion fatigue crack growth behaviour of austenitic stainless steels under light water reactor conditions, Corrosion Science 55 (2012) 61-75.
- H.P. Seifert, S. Ritter, H.J. Leber, Corrosion fatigue initiation and short crack growth behaviour of austenitic stainless steels under light water reactor conditions, Corros Sci 59 (2012) 20-34. https://doi.org/10.1016/j.corsci.2012.02.008
- H.P. Seifert, S. Ritter, H. Leber, Effect of static load hold periods on the corrosion fatigue behavior of austenitic stainless steels in simulated BWR environments, in: Proceedings of the 15th International Conference on Environmental Degradation of Materials in Nuclear Power Systems-Water Reactors, Springer, 2011, pp. 547-560.
- C. Jang, P.-Y. Cho, M. Kim, S.-J. Oh, J.-S. Yang, Effects of microstructure and residual stress on fatigue crack growth of stainless steel narrow gap welds, Materials & Design 31 (2010) 1862-1870. https://doi.org/10.1016/j.matdes.2009.10.062
- H. Cho, B.K. Kim, I.S. Kim, C. Jang, D.Y. Jung, Fatigue life and crack growth mechanisms of the type 316LN austenitic stainless steel in 310℃ deoxygenated water, J Nucl Sci Technol 44 (2007) 1007-1014. https://doi.org/10.1080/18811248.2007.9711340
- H. Cho, B.K. Kim, I.S. Kim, C. Jang, Low cycle fatigue behaviors of type 316LN austenitic stainless steel in 310 ℃ deaerated water-fatigue life and dislocation structure development, Materials Science and Engineering: A 476 (2008) 248-256. https://doi.org/10.1016/j.msea.2007.07.023
- J.-D. Hong, J. Lee, C. Jang, T.S. Kim, Low cycle fatigue behavior of alloy 690 in simulated PWR water-effects of dynamic strain aging and hydrogen, Materials Science and Engineering: A 611 (2014) 37-44. https://doi.org/10.1016/j.msea.2014.05.069
- S. Xu, X.Q. Wu, E.H. Han, W. Ke, Y. Katada, Crack initiation mechanisms for low cycle fatigue of type 316Ti stainless steel in high temperature water, Materials Science and Engineering: A 490 (2008) 16-25. https://doi.org/10.1016/j.msea.2007.12.043
- X. Wu, Y. Katada, Strain-rate dependence of low cycle fatigue behavior in a simulated BWR environment, Corros Sci 47 (2005) 1415-1428. https://doi.org/10.1016/j.corsci.2004.07.037
- U.S.N.R. Commission, Guidelines for evaluating the effects of light-water reactor water environments in fatigue analysis of metal components, Regulatory Guide 1 (2018).
- Environmental Fatigue Evaluation Method for Nuclear Power Plants, JNES-SS1005), 2011.
- C. Faidy, Status of French road map to improve environmental fatigue rules, in: Pressure Vessels and Piping Conference, Citeseer, 2012, pp. 567-573.
- B. Sudret, Z. Guede, Probabilistic assessment of thermal fatigue in nuclear components, Nuclear Engineering and Design 235 (2005) 1819-1835. https://doi.org/10.1016/j.nucengdes.2005.05.016
- B. Sudret, P. Hornet, J.-M. Stephan, Z. Guede, M. Lemaire, Probabilistic assessment of fatigue life including statistical uncertainties in the SN curve, in: 17th International Conference on Structural Mechanics in Reactor Technology (SMiRT 17)), 2003, pp. 2803-2811. Prague, Czech Republic.
- J.P. Park, S. Mohanty, C.B. Bahn, S. Majumdar, K. Natesan, 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).
- J.P. Park, S. Mohanty, C.B. Bahn, Weibull and bootstrap based probabilistic fatigue life modeling of stainless steel under PWR coolant water environment condition, in: 19th International Conference on Environmental Degradation of Materials in Nuclear Power Systems - Water Reactors, 2019, pp. 1036-1042. Boston, USA.
- Y. Ai, S.-P. Zhu, D. Liao, Probabilistic modelling of notch and size effect of components under fatigue loadings, Procedia Structural Integrity 22 (2019) 70-77. https://doi.org/10.1016/j.prostr.2020.01.010
- J. Ham, S.C. Yoo, Y. Lee, D. Park, J.H. Kim, Low cycle fatigue life of alloy 52M weld metal in simulated PWR environment, in: Transactions of the Korean Nuclear Society Virtual Spring Meeting, Korean Nuclear Society, 2021.
- S. Mohanty, W. Soppet, S. Majumdar, K. Natesan, Tensile and Fatigue Testing and Material Hardening Model Development for 508 LAS Base Metal and 316 SS Similar Metal Weld under In-Air and PWR Primary Loop Water Conditions (ANL/LWRS-15/02), Argonne National Lab.(ANL), Argonne, IL (United States), IL, USA, 2015.
- S. Mohanty, J. Listwan, 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 (ANL/LWRS-21/02), Argonne National Lab.(ANL), Argonne, IL (United States), 2021.
- ASTM International, Standard Practice for Strain-Controlled Fatigue Testing, ASTM, 2017. E606-04).
- B.V. Gnedenko, On a local limit theorem of the theory of probability, Uspekhi Matematicheskikh Nauk 3 (1948) 187-194.
- R.A. Fisher, L.H.C. Tippett, Limiting forms of the frequency distribution of the largest or smallest member of a sample, in: Mathematical Proceedings of the Cambridge Philosophical Society, Cambridge University Press, 1928, pp. 180-190.
- R.L. Wolpert, Extremes, Department of Statistical Science, Duke University, 2014. https://www2.stat.duke.edu/courses/Fall15/sta711/lec/topics/extremes.pdf. (Accessed 15 December 2021). accessed.
- W. Weibull, Wide applicability, J Appl Mech 103 (1951) 293-297. https://doi.org/10.1115/1.4010337
- J.P. Park, C.B. Bahn, Uncertainty evaluation of weibull estimators through Monte Carlo simulation: applications for crack initiation testing, Materials 9 (2016), https://doi.org/10.3390/ma9070521.
- J.P. Park, C. Park, J. Cho, C.B. Bahn, Effects of cracking test conditions on estimation uncertainty for weibull parameters considering time-dependent censoring interval, Materials 10 (2017), https://doi.org/10.3390/ma10010003.
- J.P. Park, C. Park, Y.-J. Oh, J.H. Kim, C.B. Bahn, 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 (2018) 50, https://doi.org/10.1016/j.net.2017.09.005.
- J.I. McCool, Using the Weibull Distribution: Reliability, Modeling, and Inference, John Wiley & Sons, 2012.
- Z.P. Bazant, J.-L. Le, Probabilistic Mechanics of Quasibrittle Structures: Strength, Lifetime, and Size Effect, Cambridge University Press, 2017.
- M.H. Abdallah, E.M. Abdin, A.I. Selmy, U.A. Khashaba, Reliability Analysis of GFRP Pultruded Composite Rods, International Journal of Quality & Reliability Management, 1996.
- U.A. Khashaba, Fatigue and reliability analysis of unidirectional GFRP composites under rotating bending loads, J Compos Mater 37 (2003) 317-331. https://doi.org/10.1177/0021998303037004680
- R. Sakin, I. Ay, Statistical analysis of bending fatigue life data using Weibull distribution in glass-fiber reinforced polyester composites, Materials & Design 29 (2008) 1170-1181. https://doi.org/10.1016/j.matdes.2007.05.005
- 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 (1994) 635-649. https://doi.org/10.1111/j.1460-2695.1994.tb00262.x
- M.S. Kumar, S. Vijayarangan, 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 (2007) 141-146.
- L.M. Leemis, Reliability: Probabilistic Models and Statistical Methods, Prentice-Hall, Inc., 1995.
- U. Genschel, W.Q. Meeker, A comparison of maximum likelihood and median-rank regression for Weibull estimation, Quality Engineering 22 (2010) 236-255. https://doi.org/10.1080/08982112.2010.503447
- D. Bertsimas, J. Tsitsiklis, Simulated annealing, Statistical Science 8 (1993) 10-15. https://doi.org/10.1214/ss/1177011077
- S.S. Rao, Engineering Optimization: Theory and Practice, John Wiley & Sons, 2019.
- Y. Liu, A.I. Abeyratne, Practical Applications of Bayesian Reliability, John Wiley & Sons, 2019.
- J.F. Lawless, Statistical Models and Methods for Lifetime Data, John Wiley & Sons, 2011.
- D.F. Falaakh, C.B. Bahn, Bayesian approach for prediction of primary water stress corrosion cracking in Alloy 690 steam generator tubing, Nuclear Engineering and Technology (2022).