A particle shape extraction and evaluation method using a deep convolutional neural network and digital image processing

This report investigates the effects of Fourier-based particle shape on the macroscopic and microscopic shear responses of rockfill material via a series of numerical biaxial compression tests. The multi-disk method is employed to model two-dimensional irregular rockfill particles. The macroscopic characteristics, including the shear strength and the dilatancy response, and the microscopic characteristics, including the contact force, the coordination number and the sliding contact, are examined. Then, detailed analyses of the fabric anisotropy of the entire contact network empower us to understand the microscopic mechanisms that lead to the dependency of the shear strength on particle shape. Subsequently, analyses concerning the fabric anisotropy of the strong and weak contact networks are carried out. It is found that the macroscopic stress ratio exhibits a linear pattern with the anisotropic coefficient of contacts in the strong contact network, and that the slope depends on particle shape.

Investigating the effects of Fourier-based particle shape on the shear behaviors of rockfill material via DEM

3D shape quantification and random packing simulation of rock aggregates using photogrammetry-based reconstruction and discrete element method

Stochastic numerical model of stone-based materials with realistic stone-inclusion features

Abstract Rock joint surface roughness is usually characterized by heterogeneity, but the determination of a required number of samples for achieving a reasonable heterogeneity assessment remains a challenge. In this paper, a novel method, the global search method, was proposed to investigate the heterogeneity of rock joint roughness. In this method, the roughness heterogeneity was characterized based on a statistical analysis of the roughness of all samples extracted from different locations of a given rock joint. Analyses of the effective sample number were conducted, which showed that sampling bias was caused by an inadequate number of samples. To overcome this drawback, a large natural slate joint sample (1000 mm × 1000 mm in size) was digitized in a laboratory using a high-accuracy laser scanner. The roughness heterogeneities of both two-dimensional (2D) profiles and three-dimensional (3D) surface topographies were systematically investigated. The results show that the expected value obtained from conventional methods failed to accurately represent the overall roughness. The relative errors between the population parameter and the expected value varied not only from sample to sample but also with the scale. The roughness heterogeneity characteristics of joint samples of various sizes can be obtained using the global search method. This new method could facilitate the determination of the most representative samples and their positions. 

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Characterization of Joint Roughness Heterogeneity and Its Application in Representative Sample Investigations

Quantitative characterization of joint roughness based on semivariogram parameters

This paper presents a particle shape characterization and reconstruction method to describe the geometrical information of granular railway ballast. The outline of a real granular particle is segmented and transformed as discrete time domain signals based on Fourier transform method. Then, the discrete Fourier transform algorithm is developed and applied to convert discrete time domain signals into a discrete Fourier spectrum. Meanwhile, the normalized amplitudes are defined as Fourier descriptors, which is found to be applicable to characterize and reconstruct particle contour. Further, the proposed method is validated by comparing the contours of the real particle with that of reconstructed particle. Moreover, the shape indexes of particles Fourier descriptors and reconstruction of ballasted gravel are illustrated and the the results show that the geometrical parameters can be classified as three levels which can represent the geometrical characteristics in terms of macroscopical and microscopic structure. The inverse discrete Fourier transform can quantitatively control the shape of reconstructed particles by controlling the value and distribution of Fourier descriptors, which matchs the three levels of shape indexes. Furthermore, it can be found that a large number of virtual particles with similar geometrical features can be reconstructed using the proposed Fourier descriptors in a rapid and convenient manner, which is beneficial for providing a virtual test sample for the numerical modeling of realistic granular materials.

Zhang Shuaihao

Papers

Quantitative characterization of joint roughness based on semivariogram parameters

Reconstruction of granular railway ballast based on inverse discrete Fourier transform method

A new method for constructing finite difference model of soil-rock mixture slope and its stability analysis