Dynamic simulation of random packing of spherical particles

Cheng, Yongjian; Guo, Shuang; Lai, Hongpeng

doi:10.1016/s0032-5910(99)00178-3

Cited by 79 publications

(27 citation statements)

References 24 publications

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“…4d-f ). In some models, each inclusion is subject to small random movements, regardless of position of the neighbor inclusions, until the best possible position for denser packing of inclusions is found (Berryman 1983;Cheng et al 2000). The Hard-Core model, also called random sequential adsorption model, was discussed by (Lotwick 1982;Hinrichsen et al 1986).…”

Section: Generation Of Random Microstructuresmentioning

confidence: 99%

Statistical methods for mechanical characterization of randomly reinforced media

Tashkinov

2017

Mech Adv Mater Mod Process

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Advanced materials with heterogeneous microstructure attract extensive interest of researchers and engineers due to combination of unique properties and ability to create materials that are most suitable for each specific application. One of the challenging tasks is development of models of mechanical behavior for such materials since precision of the obtained numerical results highly depends on level of consideration of features of their heterogeneous microstructure. In most cases, numerical modeling of composite structures is based on multiscale approaches that require special techniques for establishing connection between parameters at different scales. This work offers a review of instruments of the statistics and the probability theory that are used for mechanical characterization of heterogeneous media with random positions of reinforcements. Such statistical descriptors are involved in assessment of correlations between the microstructural components and are parts of mechanical theories which require formalization of the information about microstructural morphology. Particularly, the paper addresses application of the instruments of statistics for geometry description and media reconstruction as well as their utilization in homogenization methods and local stochastic stress and strain field analysis.

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Section: Generation Of Random Microstructuresmentioning

confidence: 99%

Statistical methods for mechanical characterization of randomly reinforced media

Tashkinov

2017

Mech Adv Mater Mod Process

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“…In fact, depending on the electrical nature of the involved particles the van der Waals forces are due to instantaneous dipole-dipole interactions (London forces), permanent dipole-dipole interactions (Keesom forces) and/or permanent dipole-induced dipole interactions (Debye forces). Previous works [13][14][15][16] have shown that van der Waals forces can form local particle clusters which hamper the particle rearrangement. Moreover, they can change the packing structural characteristics depending on the particle properties.…”

Section: Introductionmentioning

confidence: 99%

“…Significant contributions in the study of these processes were given by Yen and Chaki [13], Cheng et al [15] and Yang et al [14] using DEM. Collective rearrangement models [20][21][22][23][24] have also been used to simulate particle random packing.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Simulation of Random Packing of Polydispersive Fine Particles

Ferraz

Marques

2017

Braz J Phys

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In this paper, we perform molecular dynamics (MD) simulations to study the two-dimensional packing process of both monosized and random size particles with radii ranging from 1.0 µm to 7.0 µm. The initial positions as well as the radii of five thousand fine particles were defined inside a retangular box by using a random number generator. Both the translational and the rotational movement of each particle were considered in the simulations. In order to deal with interacting fine particles, we take into account both the contact forces and the long-range dispersive forces. We account for normal and static/sliding tangential friction forces between particles and between particle and wall by means of a linear model approach, while the long-range dispersive forces are computed by using a Lennard-Jones like potential. The packing processes were studied assuming different long-range interaction strengths. We carry out statistical calculations of the different quantities studied such as packing density, mean coordination number, kinetic energy and radial distribution function as the system evolves over time. We find that the long-range dispersive forces can strongly influence the packing process dynamics as they might form large particle clusters, depending on the intensity of the long-range interaction strength.

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“…Binary packing porosity has been extensively investigated in numerous works (Yu and Standish, 1988) and it has been observed that most of the granular packings found in nature have a random structure (Cheng et al, 2000). An analytical-parametric theory of the random packing of particles developed by Yu and Standish (1988) shows the existence of two packing mechanisms: the filling mechanism and the occupation mechanism.…”

Section: Introductionmentioning

confidence: 99%

Permeability analysis in bisized porous media: Wall effect between particles of different size

Dias

Fernandes

Teixeira

et al. 2008

Journal of Hydrology

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SummaryThe permeability of binary packings of glass beads with different size ratio -13.3, 20, and 26.7, was investigated. In the Kozeny-Carman equation, the dependence of the tortuosity s on the mixture porosity e(x D ) was described according to s = 1/e n for different volume fraction of large particles in the mixture, x D . Obtained data on packing permeability shows that the parameter n is a function of the volume fraction and particle size ratio, with values between 0.5 and 0.4. This can be explained by the wall effect resulting from the arrangement of the small particles occurring near the large particle surface. A model taking in account this effect was suggested that can be useful in the characterization of transport phenomena in granular beds as well as in engineering applications. ª

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Dynamic simulation of random packing of spherical particles

Cited by 79 publications

References 24 publications

Statistical methods for mechanical characterization of randomly reinforced media

Statistical methods for mechanical characterization of randomly reinforced media

Dynamic Simulation of Random Packing of Polydispersive Fine Particles

Permeability analysis in bisized porous media: Wall effect between particles of different size

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