SMA texture and reorientation: Simulations & neutron diffraction studies

Xiujie Gao*, Donald W. Brown, L Catherine Brinson

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

5 Scopus citations

Abstract

With increased usage of shape memory alloys (SMA) for applications in various fields, it is important to understand how the material behavior is affected by factors such as texture, stress state and loading history, especially for complex multiaxial loading states. Using the in-situ neutron diffraction loading facility (SMARTS diffractometer) and ex situ inverse pole figure measurement facility (HIPPO diffractometer) at the Los Alamos Neutron Science Center (LANCE), the macroscopic mechanical behavior and texture evolution of Nickel-Titanium (Nitinol) SMAs under sequential compression in alternating directions were studied. The simplified multivariant model developed at Northwestern University was then used to simulate the macroscopic behavior and the microstructural change of Nitinol under this sequential loading. Pole figures were obtained via post-processing of the multivariant results for volume fraction evolution and compared quantitatively well to the experimental results. The experimental results can also be used to test or verify other SMA constitutive models.

Original languageEnglish (US)
Article number84
Pages (from-to)715-726
Number of pages12
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume5764
DOIs
StatePublished - Sep 29 2005
EventSmart Structures and Materials 2005 - Smart Structures and Integrated Systems - San Diego, CA, United States
Duration: Mar 7 2005Mar 10 2005

Keywords

  • Complex stress state
  • Correspondence variant
  • Habit plane variant
  • In-situ straining
  • Multivariant modeling
  • Neutron diffraction
  • Nitinol
  • Reorienation
  • Shape memory alloys
  • Texture evolution

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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