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Bayesian analysis of in-situ high-resolution X-ray diffraction synchrotron experiments of Ti-6Al-4V specimens undergoing tensile loading
conference contribution
posted on 2019-01-01, 00:00 authored by N Armstrong, Peter LynchPeter Lynch, Sitarama KadaSitarama Kada, Pavel CizekPavel Cizek, J A Kimpton, R A AntoniouLinking the accumulation of microstructural damage prior to crack initiation to the lifing of aero-engines components would help to better predict the time that a component spends in this crack initiation stage We present the results and analysis of in-situ high-resolution X-ray diffraction (XRD) experiments of a Ti-6Al-4V specimen that experienced tensile loading using medium energy synchrotron X-rays (≤21 keV) carried out at the Australian Synchrotron. The XRD analysis characterised XRD line-broadening due to the build-up of dislocations and the formation of crystallites in α- and β-Ti-6Al-4V specimens. Using Bayesian XRD analysis methods, the density, spatial arrangement of dislocations, and crystallite size information for α- and β-phases of the Ti-6Al-4V was extracted from the XRD line-profiles, as a function of applied load. The XRD analysis was then compared and validated with transmission electron microscopy (TEM) analysis of the specimen before and after the loading. Comparison of the TEM and XRD analysis reveals broad agreement in terms of the microstructural damage of Ti-6Al-4V specimens.
History
Event
American Society of Mechanical Engineers. Conference (2019 : Phoenix, Arizona)Volume
7A-2019Series
American Society of Mechanical Engineers ConferencePagination
1 - 10Publisher
American Society of Mechanical EngineersLocation
Phoenix, Ariz.Place of publication
New York, N.Y.Publisher DOI
Start date
2019-06-17End date
2019-06-21ISBN-13
9780791858684Language
engPublication classification
E1 Full written paper - refereedEditor/Contributor(s)
[Unknown]Title of proceedings
ASME Turbo Expo 2019 : Power for land, sea, and air : Proceedings of the ASME Turbomachinery and Technical Conference and ExpositionUsage metrics
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