Particle morphology is an essential characteristic in determining the mechanical properties of natural sands. Based on micro x-ray computed tomography data, this paper introduces a mathematical approach using spherical harmonics (SHs) to characterise and reconstruct particle morphology in three dimensions. The basic geometric properties of natural sand particles (volume and surface area) and two empirical engineering indices (sphericity and convexity) are the main focus of the investigation on validating the efficiency of SH analysis. This approach is shown to be a robust technique for reproducing particle morphology in terms of shape irregularity and surface texture when the maximum harmonic degree is greater than ten. By using principal component analysis for the obtained SH descriptors of the scanned particles, a virtual sand assembly, consisting of statistically reconstructed particles with random shapes but major morphological features, is successfully generated. This approach can be used in efficient discrete element modelling to further study the micromechanics of natural sands.
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25 March 2015
Research Article|
January 07 2015
Random generation of natural sand assembly using micro x-ray tomography and spherical harmonics
B. Zhou;
B. Zhou
*
Department of Civil Engineering and Mechanics, Huazhong University of Science and Technology, Wuhan
, China
†
Department of Architecture and Civil Engineering, City University of Hong Kong, Kowloon
, Hong Kong
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J. Wang
J. Wang
†
Department of Architecture and Civil Engineering, City University of Hong Kong, Kowloon
, Hong Kong
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Publisher: Emerald Publishing
Received:
September 29 2014
Accepted:
December 09 2014
Online ISSN: 2045-2543
ICE Publishing: all rights reserved
2015
Geotechnique Letters (2015) 5 (1): 6–11.
Article history
Received:
September 29 2014
Accepted:
December 09 2014
Citation
Zhou B, Wang J (2015), "Random generation of natural sand assembly using micro x-ray tomography and spherical harmonics". Geotechnique Letters, Vol. 5 No. 1 pp. 6–11, doi: https://doi.org/10.1680/geolett.14.00082
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