Experimental Characterization and Crystal Plasticity Modeling of Heterogeneous Deformation in Polycrystalline α-Ti

Wang, Leyun; Barabash, Rozaliya; Yang, Yunfan; Bieler, T. R.; Crimp, M. A.; Eisenlohr, Philip; Liu, W.; Ice, Gene E.

doi:10.1007/s11661-010-0249-8

Cited by 126 publications

(41 citation statements)

References 38 publications

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“…154,438 Others have focussed primarily on capturing the local reorientations arising from polycrystalline deformation, for example Wang et al 439 have compared 30 Examples of mesh geometries created from tomographic images; a tetrahedral mesh: contour map of Mises stress through the mid-section of a (repaired) velociraptor claw loaded at the tendon location and constrained at the tip; image based crystal plasticity predictions with in situ measurements of local reorientation made by 3D X-ray microscopy. The grain orientations can also affect the elastic development of thermal contraction stresses for materials having non-cubic crystals systems.…”

Section: Polycrystal Propertiesmentioning

confidence: 99%

Quantitative X-ray tomography

Maire¹,

Withers²

2013

International Materials Reviews

1,060

601

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X-ray computer tomography (CT) is fast becoming an accepted tool within the materials science community for the acquisition of 3D images. Here the authors review the current state of the art as CT transforms from a qualitative diagnostic tool to a quantitative one. Our review considers first the image acquisition process, including the use of iterative reconstruction strategies suited to specific segmentation tasks and emerging methods that provide more insight (e.g. fast and high resolution imaging, crystallite (grain) imaging) than conventional attenuation based tomography. Methods and shortcomings of CT are examined for the quantification of 3D volumetric data to extract key topological parameters such as phase fractions, phase contiguity, and damage levels as well as density variations. As a non-destructive technique, CT is an ideal means of following structural development over time via time lapse sequences of 3D images (sometimes called 3D movies or 4D imaging). This includes information needed to optimise manufacturing processes, for example sintering or solidification, or to highlight the proclivity of specific degradation processes under service conditions, such as intergranular corrosion or fatigue crack growth. Besides the repeated application of static 3D image quantification to track such changes, digital volume correlation (DVC) and particle tracking (PT) methods are enabling the mapping of deformation in 3D over time. Finally the use of CT images is considered as the starting point for numerical modelling based on realistic microstructures, for example to predict flow through porous materials, the crystalline deformation of polycrystalline aggregates or the mechanical properties of composite materials.

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Section: Polycrystal Propertiesmentioning

confidence: 99%

Quantitative X-ray tomography

Maire¹,

Withers²

2013

International Materials Reviews

1,060

601

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“…[42][43][44][45] With the microbeam scanning on the sample surface, subsurface orientation maps can be built based on the reconstructed Laue patterns. [49] In the annealed (undeformed) condition, the Laue patterns were characterized by sharp diffraction spots. After deformation, Laue diffraction spots were often streaked, giving evidence of lattice rotations within the diffracting volume, which has been attributed to the presence of GNDs.…”

Section: A Sample and Deformationmentioning

confidence: 99%

“…This method has been successfully used to identify the GND content in a few materials. [47,49,[53][54][55] In the current study, we will use the same method to analyze those diffraction patterns that display straight streaked peaks. However, only edge GNDs can be considered in the analysis.…”

Section: A Sample and Deformationmentioning

confidence: 99%

Study of $$ \{ 11\bar{2} 1\} $$ Twinning in α-Ti by EBSD and Laue Microdiffraction

Wang

Barabash

Bieler

et al. 2013

Metall Mater Trans A

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Activity of the f11 " 21gh " 1 " 126i extension twinning (T2) mode was analyzed in a commercial purity Ti sample after 2 pct tensile strain imposed by four-point bending. The sample had a moderate c-axis fiber texture parallel to the tensile axis. Compared with the many f10 " 12gh " 1011i extension (T1) twins that formed in 6 pct of the grains, T2 twins were identified in 0.25 pct of the grains by scanning electron microscopy (SEM) and electron backscattered diffraction (EBSD) maps. Most of the T2 twins exhibited irregular twin boundaries (TBs) on one side of the twin. Highresolution EBSD revealed both intermediate orientations at some matrix/twin interfaces and substantial lattice rotation within some T2 twins. Interactions between matrix hc + ai dislocations 1 3 h1 " 213i and a f11 " 21g T2 twin were investigated by combining SEM/EBSD slip trace characterization and Laue microdiffraction peak streak analysis. hc + ai dislocations that originally glided on a pyramidal plane in the matrix were found on other planes in both the matrix and the twin, which was attributed to extensive cross-slip of the screw component, whose Burgers vector was parallel to the twinning plane. On the other hand, thickening of the twin could engulf some pile-up edge components in front of the TB. During this process, these hc + ai dislocations transmuted from a pyramidal plane ð0 " 111Þ in the matrix to a prismatic plane ð " 1010Þ T in the twin lattice. Finally, possible mechanisms for the nucleation and growth of T2 twins will be discussed.

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“…All of these considerations also imply that improved interpretations of experimental work could be effectively informed by correlating simulations of microstructure using crystal plasticity models in connection with finite element or spectral solvers. 10,17 However, developing the representations of the actual microstructure requires its nondestructive three-dimensional (3-D) characterization prior to and after deformation (which is not trivial). Nevertheless, the current analysis provides an indication of mechanistic phenomena that take place at the mesoscale despite the lack of credible stress tensor information.…”

Section: Discussionmentioning

confidence: 99%