Abstract

We use concepts and techniques of network optimization theory to gain a better understanding of force transmission in dense granular materials. Specifically, we represent a deforming granular material over the different stages of a quasi-static biaxial compression test as a series of representative flow networks, and analyze force transmission through these networks. The forces in such a material are transmitted through the contacts between the constituent grains. As the sample deforms during the various stages of the biaxial test, these grains rearrange: while many contacts are preserved in this rearrangement process, some new contacts form and some old contacts break. We consider the maximum flow problem and the minimum cost maximum flow (MCMF) problem for the flow networks constructed from this evolving network of grain contacts. We identify the flow network bottleneck and establish the sufficient and necessary conditions for a minimum cut of the maximum flow problem to be unique. We also develop an algorithm to determine the MCMF pathway, i.e. a set of edges that always transmit non-zero flow in every solution of the MCMF problem. The bottlenecks of the flow networks develop in the locality of the persistent shear band, an intensively-studied phenomenon that has long been regarded as the signature failure microstructure for dense granular materials. The cooperative evolution of the most important structural building blocks for force transmission, i.e. the force chains and 3-cycles, is examined with respect to the MCMF pathways. We find that the majority of the particles in the major load-bearing columnar force chains and 3-cycles consistently participate in the MCMF pathways.

Highlights

  • Flow networks are ubiquitous in everyday life

  • A recurring question of great practical interest is: how can we ensure optimal efficiency of flow in these networks subject to certain constraints? In this study, we focus on force transmission through the contact network, i.e. the network of

  • In order to demonstrate the efficacy of the network optimization analysis for characterizing force transmission in a dense granular material, we use the data from a discrete element simulation (DEM) developed and described in detail elsewhere [21] and further analyzed with respect to other simulation and experimental tests in [23, 26]

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Summary

Introduction

Flow networks are ubiquitous in everyday life. These are characterized by some quantity being passed from one node to another in the network: current through electrical networks, product components through assembly lines, energy flow through food webs in an ecosystem, fluid or gas through pipelines, information through communication networks, vehicles through roadways, etc. A recurring question of great practical interest is: how can we ensure optimal efficiency of flow in these networks subject to certain constraints? We focus on force transmission through the contact network, i.e. the network of. Maximum flow, minimum cut, minimum cost, granular materials, force chains. The reviewing process of the paper was handled by Ryan Loxton as Guest Editor

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