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The developments of multi-level computational methodologies for discrete element modelling of granular materials / Tingting Zhao

DOI (Published version): 10.23889/Suthesis.52441

Abstract

Granular materials are prevalent in this world while their non-trivial behaviour, which may resemble solid, liquid and/or gas under di˙erent circumstances, is still poorly understood. The challenging mechanics and dynamics of granular materials combined with their ubiquity have made this topic espec...

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Published: 2019
URI: https://cronfa.swan.ac.uk/Record/cronfa52441
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Considering the unique properties of granular materials and the inadequate features of the DEM, this thesis improves the current DEM from three di&#x2D9;erent aspects and scales.On the micro scale at the particle level, a novel contact model is developed by introducing the statistical Greenwood Williamson (GW) model which can consider the stochastic surface roughness of particles. Two non-dimensional forms of the original formulations are derived which can reduce the computational costs significantly. A Newton-Raphson based numerical solution is proposed which can solve the inter-dependence problem involved. A theoretical inconsistency of the classic GW model is deduced which leads to the development of the extended elastic GW (E-GW) model. An empirical normal contact law is obtained by the curve-fitting method and can be incorporated into the DEM code to conduct the one and three dimension compression tests. An extended elastic-plastic GW (EP-GW) model is developed to allow the plastic deformation at the asperities. Furthermore, the tangential contact model and thermal conductivity model are proposed.On the meso scale at the sample level, a new packing characterisation method is proposed based on the digitalised image matrix of a packing and the subsequent application of the principal component analysis (PCA) with which the configuration of the particle assemblies can be evaluated quantitatively. The procedures of the packing digitalisation and formation of packing image are established for both 2D and 3D cases. The obtained PCA results of the packing image matrix can be revealed by the proposed principal variance function (PVF) and dissimilarity coe&#xFF;cient (DC). The values of PVF and DC can indicate the magnitude of e&#x2D9;ects on a packing caused by the configuration randomness, the particle distribution, the packing density and the particle size distribution. The uniformity and isotropy of a packing can also be investigated by this PCA based approach.On the macro scale at the level of real industrial applications, the existing coarse graining methods are carefully analysed by the exact scaling law and the e&#x2D9;ective thermal properties of particulate phase change materials are derived by the homogenisation method. An enthalpy based discrete thermal modelling framework for particulate systems with phase change materials is developed which can consider both the heat conduction process and the phase change transition. This proposed methodology is assessed by solving a particle version of the classic one-phase Stefan melting problem. 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spelling 2019-10-15T16:33:41.4949234 v2 52441 2019-10-15 The developments of multi-level computational methodologies for discrete element modelling of granular materials 2019-10-15 Granular materials are prevalent in this world while their non-trivial behaviour, which may resemble solid, liquid and/or gas under di˙erent circumstances, is still poorly understood. The challenging mechanics and dynamics of granular materials combined with their ubiquity have made this topic especially interesting to study. The discrete element method (DEM) is a reliable and e˙ective numerical technique to model many scientific and engineering problems involving granular materials but it is still not a fully mature method. Considering the unique properties of granular materials and the inadequate features of the DEM, this thesis improves the current DEM from three di˙erent aspects and scales.On the micro scale at the particle level, a novel contact model is developed by introducing the statistical Greenwood Williamson (GW) model which can consider the stochastic surface roughness of particles. Two non-dimensional forms of the original formulations are derived which can reduce the computational costs significantly. A Newton-Raphson based numerical solution is proposed which can solve the inter-dependence problem involved. A theoretical inconsistency of the classic GW model is deduced which leads to the development of the extended elastic GW (E-GW) model. An empirical normal contact law is obtained by the curve-fitting method and can be incorporated into the DEM code to conduct the one and three dimension compression tests. An extended elastic-plastic GW (EP-GW) model is developed to allow the plastic deformation at the asperities. Furthermore, the tangential contact model and thermal conductivity model are proposed.On the meso scale at the sample level, a new packing characterisation method is proposed based on the digitalised image matrix of a packing and the subsequent application of the principal component analysis (PCA) with which the configuration of the particle assemblies can be evaluated quantitatively. The procedures of the packing digitalisation and formation of packing image are established for both 2D and 3D cases. The obtained PCA results of the packing image matrix can be revealed by the proposed principal variance function (PVF) and dissimilarity coeÿcient (DC). The values of PVF and DC can indicate the magnitude of e˙ects on a packing caused by the configuration randomness, the particle distribution, the packing density and the particle size distribution. The uniformity and isotropy of a packing can also be investigated by this PCA based approach.On the macro scale at the level of real industrial applications, the existing coarse graining methods are carefully analysed by the exact scaling law and the e˙ective thermal properties of particulate phase change materials are derived by the homogenisation method. An enthalpy based discrete thermal modelling framework for particulate systems with phase change materials is developed which can consider both the heat conduction process and the phase change transition. This proposed methodology is assessed by solving a particle version of the classic one-phase Stefan melting problem. Additional numerical simulations are also conducted to illustrate the e˙ectiveness of this modelling framework. EThesis 1 1 2019 2019-01-01 10.23889/Suthesis.52441 A selection of third party content is redacted or is partially redacted from this thesis. COLLEGE NANME COLLEGE CODE Swansea University 2019-10-15T16:33:41.4949234 2019-10-15T10:05:45.5550681 College of Engineering College of Engineering Tingting Zhao 1 0052441-15102019114007.pdf Zhao_Tingting_PhD_Thesis_Final_Redacted.pdf 2019-10-15T11:40:07.9270000 Output 41875748 application/pdf Redacted version - open access true 2019-10-14T00:00:00.0000000 true
title The developments of multi-level computational methodologies for discrete element modelling of granular materials
spellingShingle The developments of multi-level computational methodologies for discrete element modelling of granular materials
,
title_short The developments of multi-level computational methodologies for discrete element modelling of granular materials
title_full The developments of multi-level computational methodologies for discrete element modelling of granular materials
title_fullStr The developments of multi-level computational methodologies for discrete element modelling of granular materials
title_full_unstemmed The developments of multi-level computational methodologies for discrete element modelling of granular materials
title_sort The developments of multi-level computational methodologies for discrete element modelling of granular materials
author ,
author2 Tingting Zhao
format EThesis
publishDate 2019
institution Swansea University
doi_str_mv 10.23889/Suthesis.52441
college_str College of Engineering
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hierarchy_top_title College of Engineering
hierarchy_parent_id collegeofengineering
hierarchy_parent_title College of Engineering
department_str College of Engineering{{{_:::_}}}College of Engineering{{{_:::_}}}College of Engineering
document_store_str 1
active_str 0
description Granular materials are prevalent in this world while their non-trivial behaviour, which may resemble solid, liquid and/or gas under di˙erent circumstances, is still poorly understood. The challenging mechanics and dynamics of granular materials combined with their ubiquity have made this topic especially interesting to study. The discrete element method (DEM) is a reliable and e˙ective numerical technique to model many scientific and engineering problems involving granular materials but it is still not a fully mature method. Considering the unique properties of granular materials and the inadequate features of the DEM, this thesis improves the current DEM from three di˙erent aspects and scales.On the micro scale at the particle level, a novel contact model is developed by introducing the statistical Greenwood Williamson (GW) model which can consider the stochastic surface roughness of particles. Two non-dimensional forms of the original formulations are derived which can reduce the computational costs significantly. A Newton-Raphson based numerical solution is proposed which can solve the inter-dependence problem involved. A theoretical inconsistency of the classic GW model is deduced which leads to the development of the extended elastic GW (E-GW) model. An empirical normal contact law is obtained by the curve-fitting method and can be incorporated into the DEM code to conduct the one and three dimension compression tests. An extended elastic-plastic GW (EP-GW) model is developed to allow the plastic deformation at the asperities. Furthermore, the tangential contact model and thermal conductivity model are proposed.On the meso scale at the sample level, a new packing characterisation method is proposed based on the digitalised image matrix of a packing and the subsequent application of the principal component analysis (PCA) with which the configuration of the particle assemblies can be evaluated quantitatively. The procedures of the packing digitalisation and formation of packing image are established for both 2D and 3D cases. The obtained PCA results of the packing image matrix can be revealed by the proposed principal variance function (PVF) and dissimilarity coeÿcient (DC). The values of PVF and DC can indicate the magnitude of e˙ects on a packing caused by the configuration randomness, the particle distribution, the packing density and the particle size distribution. The uniformity and isotropy of a packing can also be investigated by this PCA based approach.On the macro scale at the level of real industrial applications, the existing coarse graining methods are carefully analysed by the exact scaling law and the e˙ective thermal properties of particulate phase change materials are derived by the homogenisation method. An enthalpy based discrete thermal modelling framework for particulate systems with phase change materials is developed which can consider both the heat conduction process and the phase change transition. This proposed methodology is assessed by solving a particle version of the classic one-phase Stefan melting problem. Additional numerical simulations are also conducted to illustrate the e˙ectiveness of this modelling framework.
published_date 2019-01-01T13:16:24Z
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