Journal article 856 views 220 downloads
Calibration of linear contact stiffnesses in discrete element models using a hybrid analytical-computational framework
Powder Technology
Swansea University Author: Yuntian Feng
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© 2019. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
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DOI (Published version): 10.1016/j.powtec.2019.09.016
Abstract
Efficient selections of particle-scale contact parameters in discrete element modelling remain an open question. The aim of this study is to provide a hybrid calibration framework to estimate linear contact stiffnesses (normal and tangential) for both two-dimensional and three-dimensional simulation...
Published in: | Powder Technology |
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ISSN: | 0032-5910 |
Published: |
2019
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Online Access: |
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URI: | https://cronfa.swan.ac.uk/Record/cronfa51730 |
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Abstract: |
Efficient selections of particle-scale contact parameters in discrete element modelling remain an open question. The aim of this study is to provide a hybrid calibration framework to estimate linear contact stiffnesses (normal and tangential) for both two-dimensional and three-dimensional simulations. Analytical formulas linking macroscopic parameters (Young's modulus, Poisson's ratio) to mesoscopic particle parameters for granular systems are derived based on statistically isotropic packings under small-strain isotropic stress conditions. By taking the derived analytical solutions as initial approximations, the gradient descent algorithm automatically obtains a reliable numerical estimation. The proposed framework is validated with several numerical cases including randomly distributed monodisperse and polydisperse packings. The results show that this hybrid method practically reduces the time for artificial trials and errors to obtain reasonable stiffness parameters. The proposed framework can be extended to other parameter calibration problems in DEM. |
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Keywords: |
Discrete element method, Homogenisation methods, Constitutive law, Contact force chains, Calibration method, Gradient descent |
College: |
Faculty of Science and Engineering |