Roundness and Sphericity of Soil Particles in Assemblies by Computational Geometry

Zheng, Junxing; Hryciw, Roman D.

doi:10.1061/(asce)cp.1943-5487.0000578

Cited by 85 publications

(28 citation statements)

References 52 publications

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“…Zheng and Hryciw developed a computational geometry algorithm, which can automatically compute R and S values of 3D particle geometries. The computational geometry code analyzed 3D particles in Figure .…”

Section: Soil Specimen and Materials Propertiesmentioning

confidence: 99%

Simulations of realistic granular soils in oedometer tests using physics engine

Zheng

2020

Num Anal Meth Geomechanics

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Summary Discrete element method (DEM) has become a preeminent numerical tool for investigating the mechanical behavior of granular soils. However, traditional DEM uses sphere clusters to approximate realistic particles, which is computationally demanding when simulating many particles. This paper demonstrates the potential of using a physics engine technique to simulate realistic particles. The physics engines are originally developed for video games for simulating physical and mechanical processes that occur in the real world to produce realistic game experiences. The simulation accuracy and efficiency of physics engines have been significantly improved in the last two decades allowing them to be used as a scientific tool in many disciplines. This paper introduces modeling methodologies of physics engine including realistic particle representation and the contact model. Then, oedometer tests are simulated using realistic particles scanned by X‐ray computed tomography (X‐ray CT). The simulation results agree well with experimental results. This paper demonstrates that physics engines can output contact parameters for geotechnical analysis and force chains for visualization.

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Section: Soil Specimen and Materials Propertiesmentioning

confidence: 99%

Simulations of realistic granular soils in oedometer tests using physics engine

Zheng

2020

Num Anal Meth Geomechanics

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“…The comparison experimental results of different proppants with different methods include manual measurement method, Pei's method [16], the method [24] proposed by the author in 2019 named Lyu2019, Zheng's method [21], [22](based on fuzzy connectedness extraction result and S WL is selected as the sphericity) and the proposed method in this paper.…”

Section: B Sphericity and Roundness Determination Experimentsmentioning

confidence: 99%

“…Fang et al [20] has used Fourier transform to calculate the roundness and sphericity in terms of describing the particle shape of sandy soil. Zheng and Hryciw [21], [22] and Hryciw [23] have used computational geometry methods to determine the roundness and sphericity for soil through threshold segmentation. They have used Adobe Photoshop lasso tools to delineate particles with full projections from images of three-dimensional particle assemblies.…”

Section: Introductionmentioning

confidence: 99%

Fracturing Proppant Quality Estimation Based on Fuzzy Connectedness and Shape Similarity

Lyu

Liu

et al. 2020

IEEE Access

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To improve the accuracy and efficiency of measuring fracturing proppant sphericity and roundness, a measurement scheme is designed by combining fuzzy connectedness and shape similarity. Firstly, in the proppant images collected by the microscope, according to the color characteristics of the test placement plane's hole and proppant, the region of each proppant and that of the hole without proppant are marked separately. Secondly, based on the feature of holes without proppant, the statistical method of labeling connected components is used to only reserve all the proppant regions. Thirdly, select a part of the region of each proppant as the seed region to calculate the fuzzy connectedness map between seed regions and other regions. Fourthly, select the appropriate connectedness threshold for each proppant based on histogram of fuzzy connectedness map of each proppant region to obtain the accurate region of each proppant. Finally, the shape similarity measurement method based on Hu moment is used to determine the sphericity and roundness of each proppant by measuring the similarity between the region of each proppant and that of 20 particles in the standard template. The experimental results show that the proposed scheme is consistent with manual measurement flow, and can avoid the human labor, meanwhile, the accuracy of measurement is basically consistent with the results of manual measurement.

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“…Consequently, we have used the So value directly generated by the analysis tool without knowing if this value takes into consideration any parameters (such as roughness) other than roundness [21,22], since cut off amplitudes for noise and roughness were not selected [47,57]. In the case of Rw, although the Roussillon Toolbox provides the analysis conditions, the technique does not allow for the correction of the influence of roughness, as recommended by [36,37].…”

Section: Representativity Of the Shape Parameters Studiedmentioning

confidence: 99%

“…">Shape Parameter QuantificationThe implementation of digital images in almost all electron and optical microscopes makes quantification more accessible currently. Furthermore, computer vision-based image processing provides shape measurements of particles or granular materials [17,30,[34][35][36][37]. The quantification and analysis of particles' sizes and shapes, and their distribution, have been successfully addressed through the use of: (i) advanced programming using specialized languages (e.g., C++ and Visual basic) or software (i.e., Matlab) with a specific image processing tool box (i.e., [38,39]), (ii) commercial image processing software (e.g., Image-Pro Plus ® , Aphelion) with morphological functions and a programming module (e.g., Visual basic) to automate the procedure [40], and (iii) free and open source image processing programs (e.g., ImageJ: [35,41]).…”

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confidence: 99%

Representativity of 2D Shape Parameters for Mineral Particles in Quantitative Petrography

et al. 2019

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This paper introduces an assessment of the representation of shape parameter measurements on theoretical particles. The aim of the study was to establish a numerical method for estimating sphericity, roundness, and roughness on artificially designed particles and to evaluate their interdependence. The parameters studied included a fractal dimension (FD), solidity (So), Wadell's roundness (Rw), a perimeter-area normalized ratio (¥), and sphericity (S). The methods of the work included: (a) the design of theoretical particles with different shapes, (b) the definition of optimal analysis conditions for automated measurements, (c) the quantification of particle parameters by computer vision-based image processing, and (d) the evaluation of interdependence between the parameters. The study established the minimum sizes required for analysis of the particle shape. These varied depending on the method used (150 pixels or 50 pixels). Evaluating the relationships between the parameters showed that FD and So are independent of S. Nevertheless, Rw and ¥ are clearly dependent on S and, thus, must be numerically corrected to Rwc and ¥c. FD, So, Rwc, and ¥c were used to establish, mathematically, a new regularity parameter (RBC) that reflects the degree of roundness of a particle. The process was applied to a case study and the evaluation of all parameters corroborated previous petrographic characterizations. Minerals 2019, 9, 768 2 of 21 corners of the particle. Six categories of roundness for sediment grains have been established and, for each category, one grain of low and one of high sphericity was introduced [3,6-9]. The six categories are: Very angular, angular, subangular, sub-rounded, rounded, and well-rounded. Two-dimensional particle shape measurements are particularly applicable when individual particles cannot be extracted from the rock matrix (e.g., thin sections under an optical microscope). Microscopic images are two-dimensional. Therefore, they only show part of the shape of the three-dimensional particle. The assessed image is usually of particles lying on their most stable plane on a flat support, i.e., showing the largest projection area.Traditionally, roundness indices compare the outline of a 2D projection of the particle to a circle. The first comparison defines the roundness as the ratio ri/R, which was shown in [10] (where ri is the radius of the sharpest corner, and R is the radius of the smallest circumscribing sphere). On the other hand, [11] defined the roundness parameter based on the radius of the curvature of particle corners and the radius of the largest inscribed sphere.[6] and [7] used comparison charts with a class limit table for roundness. Some authors considered angularity to be the opposite of roundness, while others considered the degree of angularity [12] to be a combination of the angular relationship between the planes bounding a corner and the distance of the corner from the center of the particle. The overall particle form heavily influences the method. In addition, [12] presente...

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Roundness and Sphericity of Soil Particles in Assemblies by Computational Geometry

Cited by 85 publications

References 52 publications

Simulations of realistic granular soils in oedometer tests using physics engine

Simulations of realistic granular soils in oedometer tests using physics engine

Fracturing Proppant Quality Estimation Based on Fuzzy Connectedness and Shape Similarity

Representativity of 2D Shape Parameters for Mineral Particles in Quantitative Petrography

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