A comparison between bridges and force-chains in photoelastic disk packing

Soft Matter ◽  
2014 ◽  
Vol 10 (1) ◽  
pp. 109-114 ◽  
Author(s):  
Ling Zhang ◽  
Shuxiao Cai ◽  
Zunpeng Hu ◽  
Jie Zhang
Keyword(s):  
Force Chains ◽  
Disk Packing

Tunnel excavation in granular media: the role of force chains

2021 ◽  
Vol 23 (4) ◽  
Author(s):  
Raj Kumar Pal ◽  
Robert Buraque de Macedo ◽  
José E Andrade
Keyword(s):  
Granular Media ◽  
Force Chains ◽  
Tunnel Excavation

scholarly journals Force chains in crystalline and frustrated packings of uniform spheres visualized by stress-birefringence

Soft Matter ◽  
2021 ◽  
Author(s):  
David Fischer ◽  
Ralf Stannarius ◽  
Karsten Tell ◽  
Peidong Yu ◽  
Matthias Sperl
Keyword(s):  
Granular Material ◽  
Force Chains ◽  
Force Networks ◽  
The Stability

Force networks play an important role in the stability of configurations when granular material is packed into a container. These networks can redirect part of the weight of grains inside...

scholarly journals Estimating Contact Force Chains Using Artificial Neural Network

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.

Influence of Force Chains Behaviors on Strength of Al/W/PTFE Granular Composite

2021 ◽  
Vol 324 ◽  
pp. 94-99
Author(s):  
Le Tang ◽  
Die Hu ◽  
Sheng Zhou ◽  
Chao Ge ◽  
Hai Fu Wang ◽  
...  
Keyword(s):  
Random Distribution ◽  
Force Chains ◽  
Metal Particles ◽  
Fracture Mechanisms ◽  
Mesoscale Simulation ◽  
Dynamic Simulations ◽  
Granular Composite ◽  
Compressive Response ◽  
Cracks Propagation ◽  
The Stability

Mesoscale simulation is conducted to investigate the effect of force chains between metal particles on the mechanical behavior of aluminum-tungsten-polytetrafluoroethylene (Al/W/PTFE) granular composite under a strain-controlled loading. A two-dimensional model followed the random distribution of particles is developed. Dynamic simulations are performed with variations in the size of Al particles to reveal the strength and fracture mechanisms of the composites. The results indicate that, force chains governed by the number and the size of metal particles significantly affects the global compressive response and macro-cracks propagation. The stability and reconstruction of mesoscale force chains explain the phenomenon that a higher strength is observed in the material with fine Al particles. Combined with the angle between particles, we examine the properties of force chains and the network as they evolve during the course of the deformation. Findings indicate that reactive composites tend to produce shorter chains, and straighter force chains with a smaller force angle result in a macroscopically stronger granular material.

scholarly journals Flow impact on granular force chains and induced instability

2018 ◽  
Vol 98 (4) ◽  
Author(s):  
Antoine Wautier ◽  
Stéphane Bonelli ◽  
François Nicot
Keyword(s):  
Force Chains

scholarly journals PROPERTIES OF THE INVARIANT DISK PACKING IN A MODEL BANDPASS SIGMA–DELTA MODULATOR

2003 ◽  
Vol 13 (03) ◽  
pp. 631-641 ◽  
Author(s):  
PETER ASHWIN ◽  
XIN-CHU FU ◽  
JONATHAN DEANE
Keyword(s):  
Phase Space ◽  
Analytic Functions ◽  
Parameter Family ◽  
Sigma Delta Modulator ◽  
Sigma Delta ◽  
Disk Packing ◽  
Piecewise Isometries ◽  
Map Operations ◽  
Countably Infinite ◽  
Parameter Values

In this paper we discuss the packing properties of invariant disks defined by periodic behavior of a model for a bandpass Σ–Δ modulator. The periodically coded regions form a packing of the forward invariant phase space by invariant disks. For this one-parameter family of PWIs, by introducing codings underlying the map operations we give explicit expressions for the centers of the disks by analytic functions of the parameters, and then show that tangencies between disks in the packings are very rare; more precisely they occur on parameter values that are at most countably infinite. We indicate how similar results can be obtained for other plane maps that are piecewise isometries.

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