PSI - Issue 22

S.C. Wu et al. / Procedia Structural Integrity 22 (2019) 211–218

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Author name / Structural Integrity Procedia 00 (2019) 000 – 000

Fig. 5. The P-S-N curve for different materials: (a) 2024-T4, (b) 2024-T3

5. Conclusion

 The STD of the stress level below the base-line level is positively associated with K , but negatively with α .  During fitting the P-S-N curve, the ISIA can reflect the gradient change of STD dependent on the stress level and lead to a bell shape with an opening down.  Combining with the load spectrum and the modified Miner theory, the ISIA can predicted the axle life with improved accuracy and reliability.  Obviously, the ISIA can be well applied for fitting the P-S-N curve of welded joints. Acknowledgements The authors give very sincere thanks to the National Natural Science Foundation of China (11572267), the Systematic Key Research and Development Program of China Railway Corporation (P2018J003), and the Open Research Project of State Key Laboratory of Traction Power (2018TPL_T03). References Wu S. C., Zhang S. Q., Xu Z. W., Kang G. Z., Cai L. X., 2016. Cyclic plastic strain based damage tolerance for railway axles in China. International Journal of Fatigue 93(1), 64-70. Hffern T. V., 2002. Probabilistic modeling and simulation of metal fatigue life prediction. California: Naval Postgraduate School. Xie L. Y., Liu J. Z., Wu N. X., Qian W. X., 2014. Backwards statistical inference method for P-S-N curve fitting with small-sample experiment data. International Journal of Fatigue 63, 62-67. Zheng X. L., Wei J. F., 2005. On the prediction of P-S-N curves of 45 steel notched elements and probability distribution of fatigue life under variable amplitude loading from tensile properties. International Journal of Fatigue 27(6), 601–609. Guida M., Penta F., 2010. ABayesian analysis of fatigue data. Structural Safety 32(1), 64-76. Liu X. W., Lu D. G., Hoogenboom P C J., 2017. Hierarchical Bayesian fatigue data analysis. International Journal of Fatigue 100, 418-428. Zhai J. M., Li X. Y., 2012. A methodology to determine a conditional probability density distribution surface from S-N data. International Journal of Fatigue 44, 107-115. Duquesnay D. L., Underhill P R., 2010. Fatigue life scatter in 7xxx series aluminum alloys. International Journal of Fatigue 32(2), 398-402. Wu S. C., Liu Y X, Li C. H., Kang G. Z., Liang S. L., 2018. On the fatigue performance and residual life of intercity railway axles with inside axle boxes. Engineering Fracture Mechanics 197, 176-191. Beretta S., Regazzi D., 2016. Probabilistic fatigue assessment for railway axles and derivation of a simple format for damage calculations. International Journal of Fatigue 86, 13-23. Zhao Y. X., Yang B., Feng M. F., Wang H., 2009. Probabilistic fatigue curves including the super-long life regime of a railway axle steel. International Journal of Fatigue 31(10), 1550-1558. Di S. S., Yang X. Q., Luan G. H., Jian B., 2006. Comparative study on fatigue properties between AA2024-T4 friction stir welds and base materials. Materials Science & Engineering A 435, 389-395. Zhou C. Z., Yang X. Q., Luan G. H., 2006. Effect of root flaws on the fatigue property of friction stir welds in 2024-T3 aluminum alloys. Materials Science & Engineering A 418(1), 155-160. Hobbacher A. F., 2016. Recommendations for fatigue design of welded joints and components. IIW document XIII-2151r4-07/XV-1254r4-07. In: Mayer, C. (Ed.). Springer International Publishing AG, Switzerland, pp. 39-49.