Article Article
Numerical Study of Rayleigh Wave Interaction with Rolling Contact Fatigue Type of Defects

Rolling Contact Fatigue or Damage (RCF/RCD) presents significant maintenance challenges to railroads across the globe. Quantifying RCF/RCD crack depths and density in rails is important for all railroads to manage their grinding programs effectively and efficiently and being able to conduct ultrasonic testing (UT) of rails for reliable detection of internal fatigue damage. This work focuses on the modeling of Rayleigh waves UT approach to detect and characterize RCF type of defects which can form as: vertical, oblique or branched shaped surface breaking defects in the rail head. Specifically, the transmission coefficient (Tc) of Rayleigh waves was studied using finite element analysis (FEA). The effect of crack tip geometry on Tc values is discussed. The results suggest that for oblique, and branch cracks, characterization based purely on the Tc can be challenging due to symmetric sinusoidal fluctuations in the Tc. A real crack using a micrograph image was also modeled to validate the Tc results for oblique and branched cracks. This points to the need for additional parameters to be identified for efficient and reliable characterization of RCF/RCD type of defects in rails.

DOI: https://doi.org/10.1080/09349847.2023.2180560

References

1. A. Poudel and M. Witte, AAR/MxV Rail Technology Digest. TD18-016, 2018. https://aar.com/TD-eLibrary/

2. A. Poudel et al., Mater Eval. 77 (7), 951–965 (2019).

3. H. M. Tournay, AAR/MxV Rail Technology Digest. TD-10-040, 2010.

4. M. A. Anis et al. In IOP Conference Series: Materials Science and Engineering, volume 377, page 012098. Varna, Bulgaria, IOP Publishing, 2018.

5. D. F. Cannon et al., Fatigue Fract. Engg. Mater. Struct. 26 (10), 865–886 (2003).

6. E. E. Magel et al., Rolling Contact Fatigue: A Comprehensive Review (Washington, DC, United States Department of Transportation. Federal Railroad Administration. Office of Railroad Policy . . ., 2011).

7. A. Kapoor, I. Salehi, and A. M. S. Asih, Rolling Contact Fatigue (RCF) (Springer US, Boston, MA, pp. 2904–2910, 2013).

8. J. Shen et al., Nondestr. Test. Eval. 35 (1), 1–18 (2020). DOI: 10.1080/10589759.2019.1611817.

9. W. Zhong et al., Wear. 271 (1–2), 388–392 (2011). DOI: 10.1016/j.wear.2010.10.071.

10. A. Poudel and M. Witte, AAR/MxV Rail Technology Digest. TD 20-007, 2020.

11. A. Poudel and M. Witte, AAR/MxV Rail Technol. Digest. TD 21-012, 2021.

12. Z. Popović et al., Metalurgija. 52 (4), 537–540 (2013).

13. W. Fletcher and K. Oldenburg, Transportation statistics annual report 2005. 2005.

14. S. L. Grassie, Wear. 258 (7–8), 1310–1318 (2005). DOI: 10.1016/j.wear.2004.03.065.

15. A. Poudel, B. Lindeman, and R. Wilson, Mater. Eval. 77 (7), 870–883 (2019).

16. D. E. Bray, NDT Int. 12 (5), 217–223 (1979). DOI: 10.1016/0308-9126(79)90002-6.

17. T. Heckel et al., NDTIP Proceedings, Prague, 2009.

18. S. Alahakoon et al., J. Dyn. Syst. Meas. Control. 140 (2), (2018). DOI: 10.1115/1.4037295.

19. R. Anandika and J. Lundberg, Proc. Instit. Mech. Eng. Part F: J. Rail Rapid Transit. 236 (5), 532–544 (2022). DOI: 10.1177/09544097211029534.

20. T. A. Alvarenga et al., Sensors. 21 (23), 7937 (2021).

21. J. Rajamäki et al., Proc. Instit. Mech. Eng., Part F: J. Rail Rapid Transit. 232 (1), 121–129 (2018). DOI: 10.1177/0954409716657848.

22. J. Zhu et al., IEEE Trans. Instrum. Meas. 68 (5), 1373–1381 (2019). DOI: 10.1109/TIM.2018.2890053.

23. E. E. Kriezis et al., Proc. IEEE. 80 (10), 1559–1589 (1992). DOI: 10.1109/5.168666.

24. S. Yanfeng and C. E. Cesnik, J. Nondestr. Eval., Diag. Prognost. Engg. Syst. 1 (1), 84–94 (2018).

25. S. K. Chakrapani, L. J. Bond, and R. Edwards, ASM Handbook, Nondestr. Evaluat. Mater. 17, 266–282 (2018).

26. S. K. Chakrapani, J. Acoust. Soc. Am. 141 (1), 137–146 (2017). DOI: 10.1121/1.4973688.

27. R. Clark and S. Singh, Insight-Non-Destr. Test. Cond. Monitor. 45 (6), 387–393 (2003).

28. S. Kenderian et al., Res. Nondestr. Eval. 16 (4), 195–207 (2005). DOI: 10.1080/09349840500306006.

29. R. S. Edwards et al. AIP Conference Proceedings, volume 1335, pages 257–264. San Diego, California, American Institute of Physics, 2011.

30. F. Hernandez-Valle et al. AIP Conference Proceedings, volume 1511, pages 324–329. Denver, Colorado, American Institute of Physics, 2013.

31. F. Hernandez-Valle et al. Proceedings of 18th World Conference on Non-Destructive Testing, Durban, South Africa, 2012.

32. A. Vu, Y. Madhuranthakam, and S. K. Chakrapani. 30th ASNT Research Symposium Conference Proceedings, volume 30, pages 84–87. St Louis, Missouri, American Society for Nondestructive Testing, 2022.

33. X. Jian et al., J. Appl. Phys. 101 (6), 064906 (2007). DOI: 10.1063/1.2435803.

34. V. K. Kinra and B. Q. Vu, J. Acoust. Soc. Am. 79 (6), 1688–1692 (1986). DOI: 10.1121/1. 393229.

35. W. Wang, Z. Zhong, and Y. D. Pan. AIP Conference Proceedings, volume 1650, pages 1307–1315. Boise, Idaho, American Institute of Physics, 2015.

36. C. Wang et al., Optics Laser Technol. 92, 15–18 (2017).

37. M. Ahmad et al. IOP Conference Series: Materials Science and Engineering, volume 1043, page 042038. IOP Publishing, 2021.

38. S. Yanfeng, J. Wang, and W. Xu, Smart Mater. Struct. 27 (10), 105044 (2018).

 

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