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

  • Data-driven Material Investigations: Understanding Fatigue Behavior
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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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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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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

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