Characterization of force networks in a dense high-shear system

Khalilitehrani, Mohammad; Sasic, Srdjan; Rasmuson, Anders

doi:10.1016/j.partic.2017.11.001

Cited by 13 publications

(3 citation statements)

References 32 publications

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“…Granular aggregates accommodate external loading through system-scale force networks that arise from repulsive contact forces between individual particles. Several studies have examined internal force networks within noncohesive granular aggregates under shear (e.g., Khalilitehrani et al, 2018) and compression (e.g., Kondic et al, 2012;Radjai et al, 1996Radjai et al, , 1999. However, to our knowledge, no studies have focused on the development of force networks within cohesive, cemented, granular aggregates of varying porosity in three dimensions under triaxial compression.…”

Section: Characterization Of Force Networkmentioning

confidence: 99%

How Porosity Controls Macroscopic Failure via Propagating Fractures and Percolating Force Chains in Porous Granular Rocks

2019

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This contribution aims to illuminate the micromechanisms that control the macroscopic failure of porous, granular, and cohesive rocks. With discrete element method simulations, we triaxially compress cohesive granular models composed of interlocking breakable grains, similar to sandstone and oolitic limestone. We track the morphology of the force network and the resulting spatiotemporal fracture distribution. To shed light on the varying applicability of the pore‐emanated and Hertzian fracture models, we focus on differences in the micromechanics that develop between and within grains. For 5–20% porosity rocks, the cement between grains develops 10–50% higher mean forces than material within grains. Force chains that support the highest system‐spanning forces are more localized prior to failure in 20% porosity rocks and are more diffusely spread in 5% porosity rocks. Confining stress reduces this localization, similar to the impact of confining stress on the macroscopic expression of brittle failure. The magnitude and rate of fracture development relative to the axial strain or axial stress increase toward failure, consistent with experimental observations. In contrast, the rate of fracture development relative to the amount of external work done on the system, Wext, is approximately constant. Higher porosity rocks require lower inputs of Wext to produce the same degree of fracturing. Decreasing the cement strength promotes fracture development within the cement, revealing the dominance of intergranular, pore‐emanated fractures. These simulations provide predictions about how porosity controls the persistence of the stress field, with implications on the sequential development of deformation bands, and other deformational processes that modify porosity.

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Section: Characterization Of Force Networkmentioning

confidence: 99%

How Porosity Controls Macroscopic Failure via Propagating Fractures and Percolating Force Chains in Porous Granular Rocks

2019

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“…Aggregate contact characteristics, including the contact number, contact distance distribution, contact length distribution, and contact orientation, etc., are descriptions of the adjacent aggregate particle interaction, which play an important role in the load transmission in asphalt mixtures. The studies of contact in asphalt mixtures fall into two categories: (1) parameterization of aggregate contact [ 20 , 30 , 54 , 55 , 56 , 57 ] and (2) contact chain characterization [ 58 , 59 , 60 , 61 ]. The parameters such as aggregate contact point, average contact length, total contact length, and contact orientation can be obtained from a section image of the asphalt mixture.…”

Section: Characterization Of Load Transfer Mechanismmentioning

confidence: 99%

Review on Load Transfer Mechanisms of Asphalt Mixture Meso-Structure

Wang

Miao

et al. 2023

Materials

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Asphalt mixture is a skeleton filling system consisting of aggregate and asphalt binder. Its performance is directly affected by the internal load transfer mechanism of the skeleton filling system. It is significant to understand the load transfer mechanisms for asphalt mixture design and performance evaluation. The objective of this paper is to review the research progress of the asphalt mixture load transfer mechanism. Firstly, this paper summarizes the test methods used to investigate the load transfer mechanism of asphalt mixtures. Then, an overview of the characterization of load transfer mechanism from three aspects was provided. Next, the indicators capturing contact characteristics, contact force characteristics, and force chain characteristics were compared. Finally, the load transfer mechanism of asphalt mixtures under different loading conditions was discussed. Some recommendations and conclusions in terms of load transfer mechanism characterization and evaluation were given. The related work can provide valuable references for the study of the load transfer mechanism of asphalt mixtures.

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“…Unlike homogeneous simple solids, the stress in such fragile matter propagates inhomogeneously via these force chains 16 , 17 , which therefore act as a crucial component in describing the mechanical and transport properties of such systems 18 – 25 . For instance, the knowledge of the force chain network is crucial to understand several key properties of granular materials, such as sound propagation 22 , non-local mechanisms of momentum transfer 26 , or the response to external confining stress 18 . Understanding when force chains will form, how the network that they make up carries the external load and responds to external or internal mechanical deformation 27 – 29 , and characterizing the statistical properties of force chains 30 – 34 constitute central challenges in ongoing research in granular matter systems.…”

Section: Introductionmentioning

confidence: 99%

Robust prediction of force chains in jammed solids using graph neural networks

2022

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Force chains are quasi-linear self-organised structures carrying large stresses and are ubiquitous in jammed amorphous materials like granular materials, foams or even cell assemblies. Predicting where they will form upon deformation is crucial to describe the properties of such materials, but remains an open question. Here we demonstrate that graph neural networks (GNN) can accurately predict the location of force chains in both frictionless and frictional materials from the undeformed structure, without any additional information. The GNN prediction accuracy also proves to be robust to changes in packing fraction, mixture composition, amount of deformation, friction coefficient, system size, and the form of the interaction potential. By analysing the structure of the force chains, we identify the key features that affect prediction accuracy. Our results and methodology will be of interest for granular matter and disordered systems, e.g. in cases where direct force chain visualisation or force measurements are impossible.

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Characterization of force networks in a dense high-shear system

Cited by 13 publications

References 32 publications

How Porosity Controls Macroscopic Failure via Propagating Fractures and Percolating Force Chains in Porous Granular Rocks

How Porosity Controls Macroscopic Failure via Propagating Fractures and Percolating Force Chains in Porous Granular Rocks

Review on Load Transfer Mechanisms of Asphalt Mixture Meso-Structure

Robust prediction of force chains in jammed solids using graph neural networks

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