3D quantitative shape analysis on form, roundness, and compactness with μCT

Abstract Particle shape plays an important role in determining the engineering behaviour of granular materials. In this regard, characterisation and quantification of particle shape are essential for understanding the behaviour of granular materials. X-ray micro-computed tomography (μCT) enables observation of particle morphology at ever-greater resolutions. The challenge has thus become extracting quantified shape parameters from these rich three-dimensional (3D) images. In this paper, we implement X-ray μCT to obtain 3D particle morphology and utilize image processing and analysis techniques to quantify it at different scales. A novel framework is proposed to measure 3D shape parameters of form, roundness, and compactness. New 3D roundness indexes were formulated from the local curvature on reconstructed triangular surface mesh. Subsequently, this method is utilized to study the change of particle shape by single particle crushing tests on Leighton Buzzard sand (LBS) particles. It is found that compactness value (i.e., sphericity) could be influenced by both form and roundness. Then, the distributions of shape parameters are characterised by Weibull statistics. It shows that single particle crushing tests generate more irregular fragments which have smaller shape parameters with larger variance for the measured shape parameters.

[1]  Theodor Zingg,et al.  Beitrag zur Schotteranalyse , 1935 .

[2]  Seah Hock Soon,et al.  Deformable volumetric model and isosurface: exploring a new approach for surface boundary construction , 1996, Comput. Graph..

[3]  Nickolay V. Lavrik,et al.  Quantifying Morphology of Sands Using 3D Imaging , 2015 .

[4]  Mario Botsch,et al.  Feature sensitive surface extraction from volume data , 2001, SIGGRAPH.

[5]  H. Wadell Volume, Shape, and Roundness of Rock Particles , 1932, The Journal of Geology.

[6]  J. Santamarina,et al.  Closure of "Particle Shape Effects on Packing Density, Stiffness, and Strength: Natural and Crushed Sands" , 2006 .

[7]  D. Asahina,et al.  Geometry of irregular particles: Direct surface measurements by 3-D laser scanner , 2011 .

[8]  M. Coop,et al.  Changes to particle characteristics associated with the compression of sands , 2011 .

[9]  Andre Phillion,et al.  Quantitative Assessment of Deformation-Induced Damage in a Semisolid Aluminum Alloy via X-ray Microtomography , 2008 .

[10]  H. Hege,et al.  A Generalized Marching Cubes Algorithm Based On Non-Binary Classifications , 1997 .

[11]  B. Sukumaran,et al.  Quantitative characterisation of the geometry of discrete particles , 2001 .

[12]  Edward J. Garboczi,et al.  Three dimensional shape analysis of JSC-1A simulated lunar regolith particles , 2011 .

[13]  Francis Schmitt,et al.  Intrinsic Surface Properties from Surface Triangulation , 1992, ECCV.

[14]  J. Bullard,et al.  Defining shape measures for 3D star-shaped particles: Sphericity, roundness, and dimensions , 2013 .

[15]  K. Soga,et al.  Particle shape characterisation using Fourier descriptor analysis , 2001 .

[16]  N. Otsu A threshold selection method from gray level histograms , 1979 .

[17]  Hans-Christian Hege,et al.  Interactive Segmentation of 3D Medical Images with Subvoxel Accuracy , 1998 .

[18]  E. List,et al.  A new system for single particle strength testing of grinding powders , 2006 .

[19]  Jan D. Miller,et al.  3D characterization and analysis of particle shape using X-ray microtomography (XMT) , 2005 .

[20]  Runqiu Huang,et al.  DEM investigation of particle anti-rotation effects on the micromechanical response of granular materials , 2013 .

[21]  Catherine O'Sullivan,et al.  Analysis of an Image-Based Method to Quantify the Size and Shape of Sand Particles , 2013 .

[22]  K. Pye,et al.  Particle shape: a review and new methods of characterization and classification , 2007 .

[23]  Glenn R. McDowell,et al.  An insight into the yielding and normal compression of sand with irregularly-shaped particles using DEM , 2015 .

[24]  Peter Lindstrom,et al.  Fast and memory efficient polygonal simplification , 1998, Proceedings Visualization '98 (Cat. No.98CB36276).

[25]  Hai-Sui Yu,et al.  Discrete Element Modeling of Cone Penetration Tests Incorporating Particle Shape and Crushing , 2015 .

[26]  William E. Lorensen,et al.  Marching cubes: A high resolution 3D surface construction algorithm , 1987, SIGGRAPH.

[27]  R. J. Fannin,et al.  Influence of roundness on the void ratio and strength of uniform sand , 2008 .

[28]  R. D. Hryciw,et al.  Traditional soil particle sphericity, roundness and surface roughness by computational geometry , 2015 .

[29]  Edward J. Garboczi,et al.  Spherical harmonic-based random fields based on real particle 3D data: Improved numerical algorithm and quantitative comparison to real particles , 2011 .

[30]  Gioacchino Viggiani,et al.  An investigation of single sand particle fracture using X-ray micro-tomography , 2015 .

[31]  Budi Zhao,et al.  Micromorphology characterization and reconstruction of sand particles using micro X-ray tomography and spherical harmonics , 2015 .

[32]  Wilhelm Burger,et al.  Digital Image Processing - An Algorithmic Introduction using Java , 2008, Texts in Computer Science.

[33]  David W. Fowler,et al.  Some properties of irregular 3-D particles , 2006 .

[34]  Catherine O'Sullivan,et al.  Non-invasive characterization of particle morphology of natural sands , 2012 .

[35]  James K. Mitchell,et al.  Fundamentals of soil behavior , 1976 .

[36]  C.R.I. Clayton,et al.  A method of estimating the form of fine particulates , 2009 .

[37]  T. Banchoff,et al.  Differential Geometry of Curves and Surfaces , 2010 .

[38]  Chenshi Dong,et al.  Curvatures estimation on triangular mesh , 2005 .

[39]  Yifei Sun,et al.  Three-dimensional characterisation of particle size and shape for ballast , 2014 .

[40]  M. Coop,et al.  Tangential load-deflection behaviour at the contacts of soil particles , 2013 .

[41]  Barry Lehane,et al.  The influence of particle shape on the (centrifuge) cone penetration test (CPT) end resistance in uniformly graded granular soils , 2012 .

[42]  Eric Vincens,et al.  Influence of particle shape and angularity on the behaviour of granular materials: a numerical analysis , 2003 .

[43]  Wolfgang Heiden,et al.  Fast generation of molecular surfaces from 3D data fields with an enhanced “marching cube” algorithm , 1993, J. Comput. Chem..

[44]  Greg Turk,et al.  Fast and memory efficient polygonal simplification , 1998 .

[45]  Stephan Kröner,et al.  Determination of minimum pixel resolution for shape analysis: Proposal of a new data validation method for computerized images , 2013 .

[46]  Guilhem Mollon,et al.  Fourier–Voronoi-based generation of realistic samples for discrete modelling of granular materials , 2012, Granular Matter.

[47]  N. C. Janke The shape of rock particles, a critical review , 1981 .

[48]  E. Garboczi Three-dimensional mathematical analysis of particle shape using X-ray tomography and spherical harmonics: Application to aggregates used in concrete , 2002 .

[49]  Rafael C. González,et al.  Local Determination of a Moving Contrast Edge , 1985, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[50]  H. J. Herrmann,et al.  Influence of particle shape on sheared dense granular media , 2006 .

[51]  D. A. Field Laplacian smoothing and Delaunay triangulations , 1988 .

[52]  Joakim Lindblad,et al.  Surface area estimation of digitized 3D objects using weighted local configurations , 2005, Image Vis. Comput..

[53]  Peter L. Choyke,et al.  Isosurfaces as deformable models for magnetic resonance angiography , 2003, IEEE Transactions on Medical Imaging.

[54]  M. Coop,et al.  The influence of particle characteristics on the behaviour of coarse grained soils , 2010 .

[55]  S. Stock Recent advances in X-ray microtomography applied to materials , 2008 .