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PUBLICATIONS

Three-Dimensional Particle Shape Analysis Using X-ray Computed Tomography: Experimental Procedure and Analysis Algorithms for Metal Powder

Published

Author(s)

Edward Garboczi, Nik Hrabe

Abstract

Measuring the size distribution of the particles in a powder is a common activity in science and industry. Measuring the shape distribution of the particles is much less common. However, the shape and size of powder particles are not independent quantities. All known size/shape measurement techniques either assume a spherical shape or measure the shape in two dimensions only. The X-ray computed tomography (XCT) based method presented here measures both size and shape in 3D without making any assumptions. Starting from a 3D image of particles, the method can mathematically classify particles according to shape, for example particles composed of several smaller particles welded together as opposed to single particles that are not necessarily spherical. Of course, defining a single number as the "size" or "shape" of a random non-spherical particle is not possible in principle, leading to many ways to estimate particle size and shape via various interlinked parameters, which can all be generated from this complete 3D characterization in the form of averages and distributions. The necessary experimental procedures, mathematical analysis, and computer analysis are described and an example is given for a metal powder. The technique is limited to particles that can be imaged by XCT with about 1000 voxels per particle volume.
Citation
Additive Manufacturing
Volume
31
Pub Type
Journals

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DOI Link

Keywords

Powder, particles, metal, ceramic, cement, sand, shape, size, X-ray computed tomography, spherical harmonics, three dimensions
Metals, Concrete / cement, Composites, Ceramics and Additive manufacturing

Citation

Garboczi, E. and Hrabe, N. (2019), Three-Dimensional Particle Shape Analysis Using X-ray Computed Tomography: Experimental Procedure and Analysis Algorithms for Metal Powder, Additive Manufacturing, [online], https://doi.org/10.1016/j.addma.2019.100965 (Accessed April 24, 2024)

Created November 23, 2019, Updated February 7, 2023