Influence of Angle on Plate Penetration into Dense Granular Materials (Large-scale DEM Simulation Using Real Particle Size)

Large scale, three dimensional computer simulations of a dense aggregative bed were performed to provide insight into the physics behind bubble formation in vertically vibrated granular materials in a shaker. As the shaker acceleration exceeds a critical value, turbulent fluctuations proportional to the particle size were produced to promote fractures at the interface between the gas and particles suspended in the gas near the bottom of the shaker. As the wave fronts pass, the solid fractures took the form of sharply defined regions of very low solids fraction (air cavities) that rose through the bed with a speed that depends on their size. The nucleation of bubbles is found to be of the heterogeneous type.

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Large-Scale DEM Simulation of Plate Drag in Dry Granular Materials

Journal of the Society of Powder Technology Japan ◽

10.4164/sptj.57.317 ◽

2020 ◽

Vol 57 (6) ◽

pp. 317-325

Author(s):

Murino Kobayakawa

Keyword(s):

Granular Materials ◽

Large Scale ◽

Dem Simulation

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Estimating Contact Force Chains Using Artificial Neural Network

Applied Sciences ◽

10.3390/app11146278 ◽

2021 ◽

Vol 11 (14) ◽

pp. 6278

Author(s):

Mengmeng Wu ◽

Jianfeng Wang

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Particle Size ◽

Granular Materials ◽

Coordination Number ◽

Contact Force ◽

Force Chains ◽

Granular System ◽

Biaxial Test ◽

Artificial Neural

The inhomogeneous distribution of contact force chains (CFC) in quasi-statically sheared granular materials dominates their bulk mechanical properties. Although previous micromechanical investigations have gained significant insights into the statistical and spatial distribution of CFC, they still lack the capacity to quantitatively estimate CFC evolution in a sheared granular system. In this paper, an artificial neural network (ANN) based on discrete element method (DEM) simulation data is developed and applied to predict the anisotropy of CFC in an assembly of spherical grains undergoing a biaxial test. Five particle-scale features including particle size, coordination number, x- and y-velocity (i.e., x and y-components of the particle velocity), and spin, which all contain predictive information about the CFC, are used to establish the ANN. The results of the model prediction show that the combined features of particle size and coordination number have a dominating influence on the CFC’s estimation. An excellent model performance manifested in a close match between the rose diagrams of the CFC from the ANN predictions and DEM simulations is obtained with a mean accuracy of about 0.85. This study has shown that machine learning is a promising tool for studying the complex mechanical behaviors of granular materials.

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Micro-Deformation Mechanism of Granular Materials under Different Boundary Conditions Based on DEM Simulation

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.170-173.3361 ◽

2012 ◽

Vol 170-173 ◽

pp. 3361-3366

Author(s):

Zhao Xia Tong ◽

Min Zhou ◽

Yang Ping Yao

Keyword(s):

Boundary Condition ◽

Granular Materials ◽

Biaxial Compression ◽

Special Focus ◽

Particle Rotation ◽

Axis Orientation ◽

Dem Simulation ◽

Steel Bars ◽

Strain Relationship ◽

Micro Deformation

Series of biaxial compression simulations are carried out to investigate the effects of boundary condition on the deformation of granular materials by using DEM. The parameters used in DEM are validated by the biaxial compression experiments on elliptical steel bars. The effects of boundary condition on the stress-strain relationship are analyzed. And special focus are put in the analysis of particle displacement, particle rotation, void distribution, particle long axis orientation and contact force with the development of deformation.

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A novel parameter inversion method for an improved DEM simulation of a river damming process by a large-scale landslide

Engineering Geology ◽

10.1016/j.enggeo.2021.106282 ◽

2021 ◽

pp. 106282

Author(s):

Wen-Jie Xu ◽

Qiang Xu ◽

Guang-Yu Liu ◽

Hui-Ya Xu

Keyword(s):

Large Scale ◽

Inversion Method ◽

Dem Simulation ◽

River Damming ◽

Parameter Inversion

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Effects of CO<sub>2</sub> on particle size distribution and phytoplankton abundance during a mesocosm bloom experiment (PeECE II)

Biogeosciences ◽

10.5194/bg-5-509-2008 ◽

2008 ◽

Vol 5 (2) ◽

pp. 509-521 ◽

Cited By ~ 85

Author(s):

A. Engel ◽

K. G. Schulz ◽

U. Riebesell ◽

R. Bellerby ◽

B. Delille ◽

...

Keyword(s):

Particle Size ◽

Particle Size Distribution ◽

Size Distribution ◽

Large Scale ◽

Phytoplankton Community ◽

Co2 Enrichment ◽

Suspended Particles ◽

Phytoplankton Abundance ◽

General Importance ◽

Co2 Treatment

Abstract. The influence of seawater carbon dioxide (CO2) concentration on the size distribution of suspended particles (2–60 μm) and on phytoplankton abundance was investigated during a mesocosm experiment at the large scale facility (LFS) in Bergen, Norway, in the frame of the Pelagic Ecosystem CO2 Enrichment study (PeECE II). In nine outdoor enclosures the partial pressure of CO2 in seawater was modified by an aeration system to simulate past (~190 μatm CO2), present (~370 μatm CO2) and future (~700 μatm CO2) CO2 conditions in triplicates. Due to the initial addition of inorganic nutrients, phytoplankton blooms developed in all mesocosms and were monitored over a period of 19 days. Seawater samples were collected daily for analysing the abundance of suspended particles and phytoplankton with the Coulter Counter and with Flow Cytometry, respectively. During the bloom period, the abundance of small particles (<4 μm) significantly increased at past, and decreased at future CO2 levels. At that time, a direct relationship between the total-surface-to-total-volume ratio of suspended particles and DIC concentration was determined for all mesocosms. Significant changes with respect to the CO2 treatment were also observed in the phytoplankton community structure. While some populations such as diatoms seemed to be insensitive to the CO2 treatment, others like Micromonas spp. increased with CO2, or showed maximum abundance at present day CO2 (i.e. Emiliania huxleyi). The strongest response to CO2 was observed in the abundance of small autotrophic nano-plankton that strongly increased during the bloom in the past CO2 mesocosms. Together, changes in particle size distribution and phytoplankton community indicate a complex interplay between the ability of the cells to physiologically respond to changes in CO2 and size selection. Size of cells is of general importance for a variety of processes in marine systems such as diffusion-limited uptake of substrates, resource allocation, predator-prey interaction, and gravitational settling. The observed changes in particle size distribution are therefore discussed with respect to biogeochemical cycling and ecosystem functioning.

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