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Title: A crystal plasticity-based study of the relationship between microstructure and ultra-high-cycle fatigue life in nickel titanium alloys

Journal Article · · International Journal of Fatigue
 [1];  [2];  [3];  [4];  [2];  [5]
  1. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Northwestern Univ., Evanston, IL (United States). Dept. of Mechanical Engineering
  2. Northwestern Univ., Evanston, IL (United States). Dept. of Materials Science and Engineering
  3. QuesTek Inovations LLC,Evanston, IL (United States)
  4. Harvard Univ., Cambridge, MA (United States). School of Engineering and Applied Sciences (SEAS)
  5. Northwestern Univ., Evanston, IL (United States). Dept. of Mechanical Engineering

Nickel Titanium (NiTi) alloys are often used in biomedical devices where failure due to mechanical fatigue is common. For other alloy systems, computational models have proven an effective means of determining the relationship between microstructural features and fatigue life. This work will extend the subset of those models which were based on crystal plasticity to examine the relationship between microstructure and fatigue life in NiTi alloys. It will explore the interaction between a spherical inclusion and the material’s free surface along with several NiTi microstructures reconstructed from 3D imaging. This work will determine the distance at which the free surface interacts with an inclusion and the effect of applied strain of surface-inclusion interaction. The effects of inclusion-inclusion interaction, matrix voiding, and matrix strengthening are explored and ranked with regards to their influence on fatigue life.

Research Organization:
Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
Sponsoring Organization:
USDOE
Grant/Contract Number:
AC52-07NA27344; 70NANB13Hl94; 70NANB14H012; LLNL-JRNL-675697
OSTI ID:
1305843
Alternate ID(s):
OSTI ID: 1324026
Report Number(s):
LLNL-JRNL-675697
Journal Information:
International Journal of Fatigue, Vol. 91, Issue P1; ISSN 0142-1123
Publisher:
ElsevierCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 17 works
Citation information provided by
Web of Science

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Cited By (2)

Data-driven multi-scale multi-physics models to derive process–structure–property relationships for additive manufacturing journal January 2018
Data science for finite strain mechanical science of ductile materials journal November 2018

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