Quantitative X-ray tomography

By Eric Maire, P. J. Withers. 2014

1,193 citations recorded by the source corpus.

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.

Subfields: Biomedical Engineering, Mechanical Engineering, Radiation

View Paper: https://www.semanticscholar.org/paper/e8633ad7b2d08d56aa282b1e1170481873f6fb87

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Citations in the corpus

Successes and challenges in non-destructive testing of aircraft composite structures (2020, background): “(1) Detector pixel size restricts resolution which depending on component geometry is often 2–3 times the pixel size.(193) (2) The effective area that is covered by the detector is typically 2000–4000 pixels wide(194) and this thus restricts the size of the test object.”
XCT analysis of the influence of melt strategies on defect population in Ti?6Al?4V components manufactured by Selective Electron Beam Melting (2015, methodology): “To assess pore size distributions and volume fractions a lower pore size cut-off of 2 x 2 x 2 (8) voxels was therefore used and for morphological analysis only objects with a minimum volume of 5 x 5 x 5 (125) voxels have been analysed, which is in line with resolution limits presented in the literat”
Dynamic compressive behaviour of cellular materials: A review of phenomenon, mechanism and modelling (2018, neutral): “The finite element modelling based on computed tomography, so-called image-based modelling [189] (see Section 4.”
Recent advances in hot tearing during casting of aluminium alloys (2020, background): “[91,92], which can guide its improvement and application in hot tearing research.”
The effect of powder oxidation on defect formation in laser additive manufacturing (2019, background): “6 μm per pixel, this implies we are 404 unable to quantify any pores with a diameter less than approximately 20 μm [73], additionally, the 405 radiographic analysis does not consider the pore depth along the X-ray beam path.”
X-Ray Microcomputed Tomography in Additive Manufacturing: A Review of the Current Technology and Applications (2018, neutral): “In materials sciences, its increasingly widespread use was reviewed in Maire and Withers, 4 which makes it clear that the method has evolved from a qualitative imaging technique in the past to a mature and quantitative analytical technique in recent years.”