Three-dimensional sphericity, roundness and fractal dimension of sand particles

Zhou, Bo; Wang, J.; Wang, H.

doi:10.1680/jgeot.16.p.207

Cited by 164 publications

(62 citation statements)

References 41 publications

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“…And for ν ≤ d/2, we deal with a discontinuous intensity field m(x x x), which produces a disjoint particles microstructure (see Figure 2a). The regularity parameter ν is also related to the pore sphericity, one of the important parameters describing a microstructure [12,42,74]. We use the sphericity definition, proposed in [69], and define the relative pore size r:…”

Section: Matérn Covariancementioning

confidence: 99%

A Statistical Framework for Generating Microstructures of Two-Phase Random Materials: Application to Fatigue Analysis

Khristenko¹,

Constantinescu²,

Tallec³

et al. 2020

Multiscale Model. Simul.

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Random microstructures of heterogeneous materials play a crucial role in the material macroscopic behavior and in predictions of its effective properties. A common approach to modeling random multiphase materials is to develop so-called surrogate models approximating statistical features of the material. However, the surrogate models used in fatigue analysis usually employ simple microstructure, consisting of ideal geometries such as ellipsoidal inclusions, which generally does not capture complex geometries. In this paper, we introduce a simple but flexible surrogate microstructure model for two-phase materials through a level-cut of a Gaussian random field with covariance of Matérn class. Such parametrization of the covariance function allows for the representation of a few key design parameters while representing the geometry of inclusions in a more general setting for a large class of random heterogeneous two-phase media. In addition to the traditional morphology descriptors such as porosity, size and aspect ratio, it provides control of the regularity of the inclusions interface and sphericity. These parameters are estimated from a small number of real material images using Bayesian inversion. An efficient process of evaluating the samples, based on the Fast Fourier Transform, makes possible the use of Monte-Carlo methods to estimate statistical properties for the quantities of interest in a given material class. We demonstrate the overall framework of the use of the surrogate material model in application to the uncertainty quantification in fatigue analysis, its feasibility and efficiency, and its role in the microstructure design.

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Section: Matérn Covariancementioning

confidence: 99%

A Statistical Framework for Generating Microstructures of Two-Phase Random Materials: Application to Fatigue Analysis

Khristenko¹,

Constantinescu²,

Tallec³

et al. 2020

Multiscale Model. Simul.

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show abstract

“…So far, a 3D analysis of surfaces has been made possible with the development of suitable testing apparatus, such as optical interferometry (e.g. [2,4,[20][21][22][23]) and X-ray micro Computed-Tomography (CT) [24]. However, all of these are limited to sand-sized particles.…”

Section: Three-dimensional (3d) Surface Measurements Have Been Prefermentioning

confidence: 99%

3D Analysis of gravel surface texture

et al. 2019

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Surface texture plays an important role in understanding the mechanical and hydraulic behavior of a soil but has drawn little attention, especially for three dimensional parameters. Currently, the few studies on measurements and quantification of surface texture are limited to sand sized particles. To date, the surface texture of sand has been successfully obtained by using a high-resolution optical microscope for a given measurement area that is small and comparable to the sand particle size. However, for larger particles, such as gravel, the larger surface area may create difficulties. For instance, as the particle size increases, the surface texture could be influenced by other factors such as the mineral composition, scale-dependent fabric and others, suggests that the surface texture examined at a large scale by using the 3D laser scanner could be representative of the gravel, though cautions should be taken in individual cases for any quantitative studies of the effect of the surface texture.

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“…Many of the other form factors correlate with elongation or flatness, see [3]. Roundness was firstly defined by Wadell, [57][58][59], but also other definitions exist, see [4] for 2D data or [5,32,33,62,64] for 3D data. For roundness computation only convex areas of the particle are considered, ignoring edges and corners in concave parts.…”

Section: Introductionmentioning

confidence: 99%

Simple particle shapes for DEM simulations of railway ballast: influence of shape descriptors on packing behaviour

Suhr

Six

2020

Granular Matter

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In any DEM simulation, the chosen particle shape will greatly influence the simulated material behaviour. For a specific material, e.g. railway ballast, it remains an open question how to model the particle shape, such that DEM simulations are computationally efficient and simulation results are in good accordance with measurements. While DEM shape modelling for railway ballast is well addressed in the literature, approaches mainly aim at approximating the stones' actual shape, resulting in rather complex and thus inefficient particle shapes. In contrast, very simple DEM shapes will be constructed, clumps of three spheres, which aim to approximate shape descriptors of the considered ballast material. In DEM simulations of the packing behaviour, a set of clump shapes is identified, which can pack at porosities observed at track sites, as well as in lab tests. The relation between particle shape (descriptors) and obtained packing (characteristic) is investigated in a correlation analysis. The simulated packing's porosity is strongly correlated to four shape descriptors, which are also strongly correlated among each other. Thus, to derive simple shape models of a given particle shape, matching one of these shape descriptors, might be a good first step to bring simulated porosities closer to measured ones. The conducted correlation analysis also shows that packing's coordination number and isotropic fabric are correlated to more shape descriptors, making it more difficult to estimate the effect of particle shape on these quantities.

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Three-dimensional sphericity, roundness and fractal dimension of sand particles

Cited by 164 publications

References 41 publications

A Statistical Framework for Generating Microstructures of Two-Phase Random Materials: Application to Fatigue Analysis

A Statistical Framework for Generating Microstructures of Two-Phase Random Materials: Application to Fatigue Analysis

3D Analysis of gravel surface texture

Simple particle shapes for DEM simulations of railway ballast: influence of shape descriptors on packing behaviour

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