Constrained optimisation in granular network flows: Games with a loaded dice

Flows in real world networks are rarely the outcome of unconditional random allocations as, say, the roll of a dice. Think, for example, of force transmission through a contact network in a quasistatically deforming granular material. Forces ‘flow’ through this network in a highly conditional manner...

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Bibliographic Details
Main Authors: Lin, Qun, Tordesillas, A.
Other Authors: Aibing Yu
Format: Conference Paper
Published: AIP 2013
Online Access:http://hdl.handle.net/20.500.11937/46884
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author Lin, Qun
Tordesillas, A.
author2 Aibing Yu
author_facet Aibing Yu
Lin, Qun
Tordesillas, A.
author_sort Lin, Qun
building Curtin Institutional Repository
collection Online Access
description Flows in real world networks are rarely the outcome of unconditional random allocations as, say, the roll of a dice. Think, for example, of force transmission through a contact network in a quasistatically deforming granular material. Forces ‘flow’ through this network in a highly conditional manner. How much force is transmitted between two contacting particles is always conditional not only on all the other forces acting between the particles in question but also on those acting on the other particles in the system. Broadly, we are interested in the nature and extent to which flows through a contact network favour certain pathways over others, and how the mechanisms that govern such biased flows for a given imposed loading history determine the future evolution of the contact network. Our first step is to solve a selection of fundamental combinatorial optimisation problems on the contact network from the perspective of force transmission. Here we report on solutions to the Maximum Flow Minimum Cost Problem for a weighted contact network where the weights assigned to the links of the contact network are varied according to their contact types. We found that those pathways through which the maximum flow of force is transmitted, in the direction of the maximum principal stress, at minimum cost – pass through the great majority of the force chains. Although the majority of the contacts in these pathways are elastic, the plastic contacts bear an undue influence on the minimum cost.
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spelling curtin-20.500.11937-468842023-02-13T08:01:35Z Constrained optimisation in granular network flows: Games with a loaded dice Lin, Qun Tordesillas, A. Aibing Yu Kejun Dong Runyu Yang Stefan Luding Flows in real world networks are rarely the outcome of unconditional random allocations as, say, the roll of a dice. Think, for example, of force transmission through a contact network in a quasistatically deforming granular material. Forces ‘flow’ through this network in a highly conditional manner. How much force is transmitted between two contacting particles is always conditional not only on all the other forces acting between the particles in question but also on those acting on the other particles in the system. Broadly, we are interested in the nature and extent to which flows through a contact network favour certain pathways over others, and how the mechanisms that govern such biased flows for a given imposed loading history determine the future evolution of the contact network. Our first step is to solve a selection of fundamental combinatorial optimisation problems on the contact network from the perspective of force transmission. Here we report on solutions to the Maximum Flow Minimum Cost Problem for a weighted contact network where the weights assigned to the links of the contact network are varied according to their contact types. We found that those pathways through which the maximum flow of force is transmitted, in the direction of the maximum principal stress, at minimum cost – pass through the great majority of the force chains. Although the majority of the contacts in these pathways are elastic, the plastic contacts bear an undue influence on the minimum cost. 2013 Conference Paper http://hdl.handle.net/20.500.11937/46884 10.1063/1.4811989 AIP fulltext
spellingShingle Lin, Qun
Tordesillas, A.
Constrained optimisation in granular network flows: Games with a loaded dice
title Constrained optimisation in granular network flows: Games with a loaded dice
title_full Constrained optimisation in granular network flows: Games with a loaded dice
title_fullStr Constrained optimisation in granular network flows: Games with a loaded dice
title_full_unstemmed Constrained optimisation in granular network flows: Games with a loaded dice
title_short Constrained optimisation in granular network flows: Games with a loaded dice
title_sort constrained optimisation in granular network flows: games with a loaded dice
url http://hdl.handle.net/20.500.11937/46884