Heterogenous void growth revealed by in situ 3-D X-ray microtomography using automatic cavity tracking

Heterogenous void growth revealed by in situ 3-D X-ray microtomography using automatic cavity tracking

Ductile fracture by nucleation, growth and coalescence of internal voids is the dominant fracture mechanism in metals at ambient temperature. Micromechanics-based models for each elementary mechanism have been developed and enhanced over the past 40years, allowing microstructure-informed failure pre...

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Bibliographic Details
Published in:Acta materialia Vol. 63; pp. 130 - 139
Main Authors: Lecarme, L., Maire, E., Kumar K.C., A., De Vleeschouwer, C., Jacques, L., Simar, A., Pardoen, T.
Format: Journal Article
Language:English
Published: Kidlington Elsevier Ltd 15-01-2014
Elsevier
Subjects:
Applied sciences
Damage initiation
Data association
Engineering Sciences
Exact sciences and technology
Growth kinetics
Materials
Metals. Metallurgy
Titanium alloys
X-ray tomography
Damage initiation
X-ray tomography
Titanium alloys
Growth kinetics
Data association
In situ
Kinetics
Void
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Summary:Ductile fracture by nucleation, growth and coalescence of internal voids is the dominant fracture mechanism in metals at ambient temperature. Micromechanics-based models for each elementary mechanism have been developed and enhanced over the past 40years, allowing microstructure-informed failure predictions essentially assuming homogeneous damage evolution. In situ 3-D microtomography has been instrumental to assess these models from experimental evolution of average void density and size. Nevertheless, statistical effects on the damage evolution associated with microstructure distribution heterogeneities have not yet been addressed quantitatively due to the difficulty in tracking individual cavities. Here, we show, from 3-D in situ microtomography characterization of a Ti–6Al–4V alloy, factor ∼4 variations among the growth rate of individual cavities undergoing the same stress triaxiality and same plastic deformation. This statistical analysis has been made possible owing to an advanced tracking algorithm relying on a graph-based data association approach initially developed for the field of computer vision to track target motions. The measured variations originate from void shape and crystal orientation effects, as well as from local constraints changes due to the presence of two phases with different strengths.
ISSN:1359-6454
1873-2453
DOI:10.1016/j.actamat.2013.10.014