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Prediction of 3D size and shape descriptors of irregular granular particles from projected 2D images
Macroscopic mechanical properties of granular materials are closely related to particle morphology. For practical reasons, the morphological features are commonly examined from projected two-dimensional (2D) images of the three-dimensional (3D) particles. This brings forward the need for quantifying the correlations between the 2D and 3D particle descriptors. This paper addresses these correlations for irregular granular particles. Three-dimensional images of sand particles were acquired through microfocus X-ray computed tomography, based on which 3D surfaces of the particles were reconstructed using spherical harmonic analyses. The 3D particle size and shape descriptors were subsequently evaluated. All-around projection and random projection of the particles onto 2D planes were undertaken numerically to obtain the projected 2D images and thus the corresponding 2D size and shape descriptors. The results indicate that there are close correlations between 3D and 2D size descriptors averaged from the all-around projections. 2D and 3D shape descriptors can be approximately fitted with a linear relationship. The mean value of 2D descriptors of the tested sands obtained from a series of independent random-projection tests is essentially identical to that from the all-around projections; except that the data from the random-projection tests show a larger scatter. In light of the relationships among the descriptors, a novel and promising approach to predict the cumulative distribution of 3D descriptors from that of 2D descriptors evaluated from a random-projection test is proposed.
Prediction of 3D size and shape descriptors of irregular granular particles from projected 2D images
Macroscopic mechanical properties of granular materials are closely related to particle morphology. For practical reasons, the morphological features are commonly examined from projected two-dimensional (2D) images of the three-dimensional (3D) particles. This brings forward the need for quantifying the correlations between the 2D and 3D particle descriptors. This paper addresses these correlations for irregular granular particles. Three-dimensional images of sand particles were acquired through microfocus X-ray computed tomography, based on which 3D surfaces of the particles were reconstructed using spherical harmonic analyses. The 3D particle size and shape descriptors were subsequently evaluated. All-around projection and random projection of the particles onto 2D planes were undertaken numerically to obtain the projected 2D images and thus the corresponding 2D size and shape descriptors. The results indicate that there are close correlations between 3D and 2D size descriptors averaged from the all-around projections. 2D and 3D shape descriptors can be approximately fitted with a linear relationship. The mean value of 2D descriptors of the tested sands obtained from a series of independent random-projection tests is essentially identical to that from the all-around projections; except that the data from the random-projection tests show a larger scatter. In light of the relationships among the descriptors, a novel and promising approach to predict the cumulative distribution of 3D descriptors from that of 2D descriptors evaluated from a random-projection test is proposed.
Prediction of 3D size and shape descriptors of irregular granular particles from projected 2D images
Acta Geotech.
Su, D. (author) / Yan, W. M. (author)
Acta Geotechnica ; 15 ; 1533-1555
2020-06-01
23 pages
Article (Journal)
Electronic Resource
English
Correlation , Cumulative distribution , Particle morphology , Shape descriptor , Size descriptor Engineering , Geoengineering, Foundations, Hydraulics , Solid Mechanics , Geotechnical Engineering & Applied Earth Sciences , Soil Science & Conservation , Soft and Granular Matter, Complex Fluids and Microfluidics
Prediction of 3D size and shape descriptors of irregular granular particles from projected 2D images
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