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Data-Driven Mechanistic Modeling of Influence of Microstructure on High-Cycle Fatigue Life of Nickel Titanium

JOM volume 70, pages 1154–1158 (2018)Cite this article

Abstract

A data-driven mechanistic modeling technique is applied to a system representative of a broken-up inclusion (“stringer”) within drawn nickel-titanium wire or tube, e.g., as used for arterial stents. The approach uses a decomposition of the problem into a training stage and a prediction stage. It is applied to compute the fatigue crack incubation life of a microstructure of interest under high-cycle fatigue. A parametric study of a matrix–inclusion–void microstructure is conducted. The results indicate that, within the range studied, a larger void between halves of the inclusion increases fatigue life, while larger inclusion diameter reduces fatigue life.

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References

  1. A. Pelton, V. Schroeder, M. Mitchell, X.Y. Gong, M. Barney, and S. Robertson, J. Mech. Behav. Biomed. Mater. 1, 153 (2008)

    Article  Google Scholar 

  2. S. Adlakha, M. Sheikh, J. Wu, M.W. Burket, U. Pandya, W. Colyer, E. Eltahawy, and C.J. Cooper, J. Interv. Cardiol. 23, 411 (2010)

    Article  Google Scholar 

  3. M. Rahim, J. Frenzel, M. Frotscher, J. Pfetzing-Micklich, R. Steegmüller, M. Wohlschlögel, H. Mughrabi, and G. Eggeler, Acta Mater. 61, 3667 (2013)

    Article  Google Scholar 

  4. F. Sczerzenie, G. Vergani, and C. Belden, J. Mater. Eng. Perform. 21, 2578 (2012)

    Article  Google Scholar 

  5. N. Salajegheh, R. Prasannavenkatesan, D.L. McDowell, G.B. Olson, and H.J. Jou, J. Eng. Mater. Technol. 136, 031003 (2014)

    Article  Google Scholar 

  6. R. Prasannavenkatesan, J. Zhang, D.L. McDowell, G.B. Olson, and H.J. Jou, Int. J. Fatigue 31, 1176 (2009)

    Article  Google Scholar 

  7. J.A. Moore, D. Frankel, R. Prasannavenkatesan, A.G. Domel, G.B. Olson, and W.K. Liu, Int. J Fatigue 91, 183 (2016)

    Article  Google Scholar 

  8. A. Fatemi and D.F. Socie, Fatigue Fract. Eng. Mater. Struct. 11, 149 (1988)

    Article  Google Scholar 

  9. G.M. Owolabi and H.A. Whitworth, J. Mater. Sci. Technol. 30, 203 (2014)

    Article  Google Scholar 

  10. Z. Liu, O.L. Kafka, C. Yu, and W.K. Liu, Data-driven self-consistent clustering analysis of heterogeneous materials with crystal plasticity, in Advances in Computational Plasticity: A Book in Honour of D. Roger J. Owen, ed. E. Oñate, D. Peric, E. de Souza Neto, M. Chiumenti (Springer International, 2018), pp. 221–242

  11. Z. Liu, M. Bessa, and W. Liu, Comput. Methods Appl. Mech. Eng. 306, 319 (2016)

    Article  Google Scholar 

  12. H. Moulinec and P. Suquet, Comput. Methods Appl. Mech. Eng. 157, 69 (1998)

    Article  Google Scholar 

  13. J. MacQueen, Proceedings of the Fifth Berkeley Symposium on Mathematics Statistics and Probability p. 281 (1967)

  14. M. Kabel, T. Böhlke, and M. Schneider, Comput. Mech. 54, 1497 (2014)

    MathSciNet  Article  Google Scholar 

  15. R.D. McGinty, Multiscale Representation of Polycrystalline Inelasticity, Ph.D. thesis, Geogia Tech (2001)

  16. C.H. Goh, R.W. Neu, and D.L. McDowell, Int. J. Plast. 19, 1627 (2003)

    Article  Google Scholar 

  17. M. Shenoy, J. Zhang, and D. McDowell, Fatigue Fract. Eng. Mater. Struct. 30, 889 (2007)

    Article  Google Scholar 

  18. G.M. Owolabi, R. Prasannavenkatesan, and D.L. McDowell, Int. J. Fatigue 32, 1378 (2010)

    Article  Google Scholar 

  19. H. Sehitoglu, J. Jun, X. Zhang, I. Karaman, Y. Chumlyakov, H. Maier, and K. Gall, Acta Mater. 49, 3609 (2001)

    Article  Google Scholar 

  20. S.W. Robertson, M. Launey, O. Shelley, I. Ong, L. Vien, K. Senthilnathan, P. Saffari, S. Schlegel, and A.R. Pelton, J. Mech. Behav. Biomed. Mater. 51, 119 (2015)

    Article  Google Scholar 

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Acknowledgements

C.Y., M.S., and W.K.L. thank the National Institute of Standards and Technology and Center for Hierarchical Materials Design (CHiMaD) under Grant Nos. 70NANB13Hl94 and 70NANB14H012; W.K.L. also acknowledges the support of the AFOSR. O.L.K. thanks the National Science Foundation (NSF) for their support through the NSF Graduate Research Fellowship Program (GRFP) under financial Award Number DGE-1324585.

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Authors and Affiliations

  1. Mechanical Engineering, Northwestern University, Evanston, USA

    Orion L. Kafka, Cheng Yu, Modesar Shakoor, Zeliang Liu, Gregory J. Wagner & Wing Kam Liu

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  1. Orion L. Kafka
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  2. Cheng Yu
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Correspondence to Wing Kam Liu.

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Kafka, O.L., Yu, C., Shakoor, M. et al. Data-Driven Mechanistic Modeling of Influence of Microstructure on High-Cycle Fatigue Life of Nickel Titanium. JOM 70, 1154–1158 (2018). https://doi.org/10.1007/s11837-018-2868-2

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  • DOI: https://doi.org/10.1007/s11837-018-2868-2