Calibration for discrete element modelling of railway ballast: A review

Guo, Yunlong; Zhao, Chunfa; Markine, Valéri; Jing, Guoqing; Zhai, Wanming

doi:10.1016/j.trgeo.2020.100341

Cited by 82 publications

(22 citation statements)

References 126 publications

(266 reference statements)

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“…The sleepers are built by combining discs as a Clump (rigid block), and the rail is built by bonding discs together as a beam with linear 99 parallel bonds. The linear parallel bonds present a physical performance similar to the cement, which can glue together the two contacting discs (Guo et al 2020a).…”

Section: Model Descriptionmentioning

confidence: 99%

“…The DEM is an effective and reliable approach to present the granular material properties of ballast assembly, e.g. density, degradation, particle size and particle shape (Guo et al 2020a), and has been successfully applied in many ballast-related studies, such as, under sleeper pads (Li and McDowell 2018), ballast particle acceleration (Liu et al 2019) and friction sleeper (Guo et al 2020b). The hybrid discrete-continuum approach has been proved to be an effective solution for the ballasted track studies involving the subgrade (Shao et al 2017;Ngo et al 2017;Li et al 2019;Shi et al 2020a).…”

Section: Introductionmentioning

confidence: 99%

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Analysis of Railway Ballasted Track Stiffness and Behavior with a Hybrid Discrete–Continuum Approach

et al. 2021

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Railway ballasted track stiffness is an important indicator to identify supporting condition that ensures the facility is well designed and functioned. Although many studies have been performed on track stiffness based on experimental tests and finite element methods, the factors influencing the track stiffness have not been completely confirmed yet, especially the influences from ballast and subgrade layers at a mesoscopic level. To address this research gap, a coupled the discrete element method (DEM) and the finite difference method (FDM) model is utilised to study the factors influencing on the track stiffness from the particle level. Factors (related to ballast layer properties) are bulk density, thickness and stiffness, and other factor (related to subgrade properties) is elastic modulus. Additionally, the relationship between the track stiffness and the mechanical behaviour of ballast is analysed. This study quantified the influences of track components on the track stiffness and accordingly proposed how to improve it from the ballast and subgrade layers at the mesoscopic level, which can provide the guidance for railway ballasted track design and maintenance.

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Section: Model Descriptionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Analysis of Railway Ballasted Track Stiffness and Behavior with a Hybrid Discrete–Continuum Approach

et al. 2021

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“…Note that one model corresponds to only one type of particle shape. The clump particles are created with the identical template that was obtained by scanning the real ballast particle [40].…”

Section: Contact Model and Particle Shapementioning

confidence: 99%

Discrete element modelling of railway ballast performance considering particle shape and rolling resistance

et al. 2020

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To simulate ballast performance accurately and efficiently, the input in discrete element models should be carefully selected, including the contact model and applied particle shape. To study the effects of the contact model and applied particle shape on the ballast performance (shear strength and deformation), the direct shear test (DST) model and the large-scale process simulation test (LPST) model were developed on the basis of two types of contact models, namely the rolling resistance linear (RRL) model and the linear contact (LC) model. Particle shapes are differentiated by clumps. A clump is a sphere assembly for one ballast particle. The results show that compared with the typical LC model, the RRL method is more efficient and realistic to predict shear strength results of ballast assemblies in DSTs. In addition, the RRL contact model can also provide accurate vertical and lateral ballast deformation under the cyclic loading in LPSTs.

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“…Particle shape representation and reconstruction are becoming increasingly important for numerical investigations of particle morphology and its effects on micro-macro mechanical behavior [1,[30][31][32]. Clumps, clusters and polyhedrons have typically been used in discrete element modeling to represent a realistic shape, along with developed overlapping or skeletonization algorithms (e.g.…”

Section: Particle Shape Reconstructionmentioning

confidence: 99%

Internal rolling method for particle shape evaluation and reconstruction

2020

PLoS ONE

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A concise and robust method for 2D particle shape evaluation and reconstruction is proposed using the concept of the internal rolling of covering discs within the outline of a particle. By downscaling the covering disc size for capturing multiscale features, the calculation of the Euclidean distance can effectively yield three indices for sphericity, roundness and roughness. The geometric-based evaluations of particle morphology are dimensionless and precisely distinguishable between shapes after calibration and validation against constructed particles and natural sands. A sphericity-roundness diagram is provided to visualize the particle shape characterization, and a probabilistic density surface in the sphericity-roundness diagram is then proposed to statistically represent the distributions of the particle shapes. The concept of internal rolling is also utilized for particle shape reconstruction using a limited number of balls to replicate the indices of sphericity, roundness and roundness characteristic curve. The probabilistic density surface is duplicated for statistical particle shape reconstruction, which provides an effective approach for numerical investigations of the relationships between particle shapes and mechanical behavior. The effect of image quality on 2D shape evaluation is also examined by using a minimum area per particle, and the proposed method is intuitively extendable to 3D measurements using rolling covering spheres.

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Calibration for discrete element modelling of railway ballast: A review

Cited by 82 publications

References 126 publications

Analysis of Railway Ballasted Track Stiffness and Behavior with a Hybrid Discrete–Continuum Approach

Analysis of Railway Ballasted Track Stiffness and Behavior with a Hybrid Discrete–Continuum Approach

Discrete element modelling of railway ballast performance considering particle shape and rolling resistance

Internal rolling method for particle shape evaluation and reconstruction

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