Fatigue Damage Assessment Leveraging Nondestructive Evaluation Data

Abstract

Fatigue in materials depends on several microstructural parameters. The length and time scales involved in such processes have been investigated by characterization methods that target microstructural effects or that rely on specimen-level observations. Combinations of in situ and ex situ techniques are also used to correlate microstructural changes to bulk properties. We present herein an effort to directly link local changes with specimen-level fatigue damage assessment. To achieve this goal, grain-scale observations in an aluminum alloy are linked with deformation measurements made by digital image correlation and with acoustic emission monitoring obtained from inside the scanning electron microscope. Damage assessment is attempted using a data-processing framework that involves noise removal, data reduction, and classification. The results demonstrate that nondestructive evaluation combined with small-scale testing can provide a means for fatigue damage assessment applicable to a broad range of materials and testing conditions.

This is a preview of subscription content, log in to check access.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

References

  1. 1.

    D.G. Aggelis, E.Z. Kordatos, and T.E. Matikas, Mech. Res. Commun. 38, 106 (2011).

    Article  Google Scholar 

  2. 2.

    Y. Akiniwa, K. Tanaka, and E. Matsui, Mater. Sci. Eng. A Struct. 104, 105 (1988).

    Article  Google Scholar 

  3. 3.

    L.P. Borrego, J.M. Costa, S. Silva, and J.M. Ferreira, Int. J. Fatigue 26, 1321 (2004).

    Article  Google Scholar 

  4. 4.

    P.A. Vanniamparambil, U. Guclu, and A. Kontsos, Exp. Mech. 55, 837 (2015).

    Article  Google Scholar 

  5. 5.

    T.M. Roberts and M. Talebzadeh, J. Constr. Steel Res. 59, 695 (2003).

    Article  Google Scholar 

  6. 6.

    Z. Zhong, X. Ai, Z. Liu, J. Liu, and Q. Xu, Int. J. Adv. Manuf. Technol. Int. 78, 281 (2014).

    Article  Google Scholar 

  7. 7.

    Y. Zhang, H.-J. Shi, J. Gu, C. Li, K. Kadau, and O. Luesebrink, Theor. Appl. Fract. Mech. 69, 80 (2014).

    Article  Google Scholar 

  8. 8.

    J. Payne, G. Welsh, R.J. Christ, J. Nardiello, and J.M. Papazian, Int. J. Fatigue 32, 247 (2010).

    Article  Google Scholar 

  9. 9.

    F. Pierron, M. Sutton, and V. Tiwari, Exp. Mech. 51, 537 (2011).

    Article  Google Scholar 

  10. 10.

    J. Abanto-Bueno and J. Lambros, Eng. Fract. Mech. 69, 1695 (2002).

    Article  Google Scholar 

  11. 11.

    A.H. Cannon, J.D. Hochhalter, A.W. Mello, G.F. Bomarito, and M.D. Sangid, Microsc. Microanal. 21, 451 (2015).

    Article  Google Scholar 

  12. 12.

    R. Carmi, P.A. Vanniamparambil, J. Cuadra, K. Hazeli, S. Rajaram, U. Guclu, A. Bussiba, I. Bartoli, and A. Kontsos, Advances in Acoustic Emission Technology, ed. G. Shen, Z. Wu, and J. Zhang (New York: Springer, 2015), pp. 605–622.

    Google Scholar 

  13. 13.

    J.D. Carroll, W. Abuzaid, J. Lambros, and H. Sehitoglu, Int. J. Fatigue 57, 140 (2013).

    Article  Google Scholar 

  14. 14.

    A. Kammers and S. Daly, Meas. Sci. Technol. 22, 125501 (2011).

    Article  Google Scholar 

  15. 15.

    F. Khan, I. Bartoli, S. Rajaram, P. Vanniamparambil, A. Kontsos, M. Bolhassani, and A. Hamid, SPIE 9063, 90630B (2014).

    Google Scholar 

  16. 16.

    P.A. Vanniamparambil, J. Cuadra, U. Guclu, I. Bartoli, and A. Kontsos, SPIE 9064, 906411 (2014).

    Google Scholar 

  17. 17.

    M.N. Bassim, S.S. Lawrence, and C.D. Liu, Eng. Fract. Mech. 47, 207 (1994).

    Article  Google Scholar 

  18. 18.

    C. Scala and S.M. Cousland, J. Mater. Sci. Eng. 61, 211 (1983).

    Article  Google Scholar 

  19. 19.

    P. Vanniamparambil, U. Guclu, and A. Kontsos, Exp. Mech. 55, 837 (2015).

    Article  Google Scholar 

  20. 20.

    B.R. Tittmann and O. Buck, J. Nondestr. Eval. Diagn. Progn. Eng. Syst. 1, 123 (1980).

    Article  Google Scholar 

  21. 21.

    T.M. Roberts and M. Talebzadeh, J. Constr. Steel Res. 59, 679 (2003).

    Article  Google Scholar 

  22. 22.

    F. Bridier, D.L. McDowell, P. Villechaise, and J. Mendez, Int. J. Plast 25, 1066 (2009).

    Article  Google Scholar 

  23. 23.

    A. Merati, Int. J. Fatigue 27, 33 (2005).

    Article  Google Scholar 

  24. 24.

    J.D. Hochhalter, D.J. Littlewood, R.J. Christ Jr, M.G. Veilleux, J.E. Bozek, A.R. Ingraffea and A.M. Maniatty, Modell. Simul. Mater. Sci. Eng., 18, 045004 (2010)

    Article  Google Scholar 

  25. 25.

    J.D. Hochhalter, D.J. Littlewood, R.J. Christ Jr, M.G. Veilleux, J.E. Bozek, A.R. Ingraffea and A.M. Maniatty, Modell. Simul. Mater. Sci. Eng., 19, 035008 (2011)

    Article  Google Scholar 

  26. 26.

    G. Bian, Y. Chen, J. Hu, and M. Yang, in The Proceedings of 2011 9th International Conference on Reliability, Maintainability and Safety, ed. G. Shen, Z. Wu, and J. Zhang (New Jersey: IEEE, 2011), pp. 416–419.

  27. 27.

    C.J. Boehlert, C.J. Cowen, S. Tamirisakandala, D.J. McEldowney, and D.B. Miracle, Scr. Mater. 55, 465 (2006).

    Article  Google Scholar 

  28. 28.

    B. Moser, J. Kuebler, H. Meinhard, W. Muster, and J. Michler, Adv. Eng. Mater. 7, 388 (2005).

    Article  Google Scholar 

  29. 29.

    B. Wisner and A. Kontsos, Fatigue Fract. Eng. Mater. Struct. 41, 581 (2017).

    Article  Google Scholar 

  30. 30.

    V. Patel and R. Mehta, in Proceedings of the International Conference on Soft Computing for Problem Solving (SocProS 2011) (New York, NY: Springer, 2011), pp. 691–700.

  31. 31.

    H. Bi, Z. Li, D. Hu, I. Toku-Gyamerah, and Y. Cheng, Materialwiss. Werkstofftech. 46, 736 (2015).

    Article  Google Scholar 

  32. 32.

    R. Gutkin, C.J. Green, S. Vangrattanachai, S.T. Pinho, P. Robinson, and P.T. Curtis, Mech. Syst. Signal Process. 25, 1393 (2011).

    Article  Google Scholar 

  33. 33.

    M. Wevers, NDT&E Int. 30, 99 (1997).

    Article  Google Scholar 

  34. 34.

    P.A. Vanniamparambil, I. Bartoli, K. Hazeli, J. Cuadra, E. Schwartz, R. Saralaya, and A. Kontsos, in Proceedings of SPIEThe International Society for Optical Engineering (2012), p. 83482J .

  35. 35.

    B. Wisner and A. Kontsos, Fracture, Fatigue, Failure and Damage Evolution, Vol. 1 (New York: Springer, 2017), pp. 1–8.

    Google Scholar 

  36. 36.

    B. Wisner, M. Cabal, P. Vanniamparambil, J. Hochhalter, W. Leser, and A. Kontsos, Exp. Mech. 55, 1705 (2015).

    Article  Google Scholar 

  37. 37.

    B. Wisner and A. Kontsos, in Fracture, Fatigue, Failure and Damage Evolution, Vol. 1, ed. 37. A.T. Zehnder, J. Carroll, K. Hazeli, R.B. Berke, G. Pataky, M. Cavalli, A.M. Beese, and S. Xia (New York: Springer, 2017), pp. 1–8.

    Google Scholar 

  38. 38.

    L. Al Shalabi and Z. Shaaban, in International Conference on Dependability of Computer Systems (Wroclaw, Poland: DepCos-RELCOMEX’06, 2006), pp. 207–214.

  39. 39.

    S. Azrour, S. Piérard, P. Geurts, and M. Van Droogenbroeck, in European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (Bruges, Belgium: ESANN, 2014), pp. 649–654.

  40. 40.

    C. Colantuoni, G. Henry, S. Zeger, and J. Pevsner, Bioinformatics 18, 1540–1541 (2002).

    Article  Google Scholar 

  41. 41.

    C. Boutsidis, M.W. Mahoney, and P. Drineas, in Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (Las Vegas, Nevada: SIGKDD, 2008), pp. 61–69

  42. 42.

    J.E. Jackson, A User’s Guide to Principal Components, Vol. 1 (Hoboken, NY: Wiley, 2004).

    Google Scholar 

  43. 43.

    C. Aggarwal, Data Mining (New York, NY: Springer, 2015), pp. 237–263.

    Google Scholar 

  44. 44.

    K. Worden, G. Manson, and N.R. Fieller, J. Sound Vib. 229, 647 (2000).

    Article  Google Scholar 

Download references

Acknowledgements

A. Kontsos would like to acknowledge financial support received by the Office of Naval Research Under Award #N00014-14-1-0571.

Author information

Affiliations

Authors

Corresponding author

Correspondence to A. Kontsos.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (PDF 321 kb)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Mazur, K., Wisner, B. & Kontsos, A. Fatigue Damage Assessment Leveraging Nondestructive Evaluation Data. JOM 70, 1182–1189 (2018). https://doi.org/10.1007/s11837-018-2882-4

Download citation