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An extended Greenwood-Williamson modelbased normal interaction law for discrete element modelling of spherical particles with surface roughness
International Journal for Numerical and Analytical Methods in Geomechanics
Swansea University Author: Yuntian Feng
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DOI (Published version): 10.1002/nag.2805
Abstract
The current work aims to develop an improved random normal interaction law based on an extended Greenwood‐Williamson (GW) model for spherical particles with surface roughness in the discrete element modelling of particle systems. The extended GW model overcomes some theoretical defects of the classi...
Published in: | International Journal for Numerical and Analytical Methods in Geomechanics |
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ISSN: | 0363-9061 |
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2018
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URI: | https://cronfa.swan.ac.uk/Record/cronfa40270 |
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2018-07-13T14:20:54.0951653 v2 40270 2018-05-18 An extended Greenwood-Williamson modelbased normal interaction law for discrete element modelling of spherical particles with surface roughness d66794f9c1357969a5badf654f960275 0000-0002-6396-8698 Yuntian Feng Yuntian Feng true false 2018-05-18 ACEM The current work aims to develop an improved random normal interaction law based on an extended Greenwood‐Williamson (GW) model for spherical particles with surface roughness in the discrete element modelling of particle systems. The extended GW model overcomes some theoretical defects of the classic GW model when incorporated into the discrete element framework. Based on 2 nondimensional forms in which only 2 surface roughness parameters are involved, an empirical formula of the improved interaction law is derived by the curve‐fitting technique. The resulting interaction law is incorporated into discrete element modelling to investigate the mechanical response of particle systems with different surface roughness. Numerical simulations are performed to model 1‐dimensional and 3‐dimensional compression tests to explore the macro and micro characteristics of granular particles with surface roughness. The results show that surface roughness makes the initial packing of a particle assembly looser and has a greater influence on looser packed samples as expected, but an assembly with moderate roughness may exhibit a higher strength. The limitations of the current development are also highlighted. Journal Article International Journal for Numerical and Analytical Methods in Geomechanics 0363-9061 31 12 2018 2018-12-31 10.1002/nag.2805 COLLEGE NANME Aerospace, Civil, Electrical, and Mechanical Engineering COLLEGE CODE ACEM Swansea University 2018-07-13T14:20:54.0951653 2018-05-18T13:12:27.3391245 Faculty of Science and Engineering School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Civil Engineering Tingting Zhao 1 Y.T. Feng 2 Min Wang 3 Yuntian Feng 0000-0002-6396-8698 4 0040270-18052018131420.pdf zhao2018.pdf 2018-05-18T13:14:20.2530000 Output 8301320 application/pdf Accepted Manuscript true 2019-06-08T00:00:00.0000000 false eng |
title |
An extended Greenwood-Williamson modelbased normal interaction law for discrete element modelling of spherical particles with surface roughness |
spellingShingle |
An extended Greenwood-Williamson modelbased normal interaction law for discrete element modelling of spherical particles with surface roughness Yuntian Feng |
title_short |
An extended Greenwood-Williamson modelbased normal interaction law for discrete element modelling of spherical particles with surface roughness |
title_full |
An extended Greenwood-Williamson modelbased normal interaction law for discrete element modelling of spherical particles with surface roughness |
title_fullStr |
An extended Greenwood-Williamson modelbased normal interaction law for discrete element modelling of spherical particles with surface roughness |
title_full_unstemmed |
An extended Greenwood-Williamson modelbased normal interaction law for discrete element modelling of spherical particles with surface roughness |
title_sort |
An extended Greenwood-Williamson modelbased normal interaction law for discrete element modelling of spherical particles with surface roughness |
author_id_str_mv |
d66794f9c1357969a5badf654f960275 |
author_id_fullname_str_mv |
d66794f9c1357969a5badf654f960275_***_Yuntian Feng |
author |
Yuntian Feng |
author2 |
Tingting Zhao Y.T. Feng Min Wang Yuntian Feng |
format |
Journal article |
container_title |
International Journal for Numerical and Analytical Methods in Geomechanics |
publishDate |
2018 |
institution |
Swansea University |
issn |
0363-9061 |
doi_str_mv |
10.1002/nag.2805 |
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Faculty of Science and Engineering |
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facultyofscienceandengineering |
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Faculty of Science and Engineering |
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facultyofscienceandengineering |
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Faculty of Science and Engineering |
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School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Civil Engineering{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Civil Engineering |
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description |
The current work aims to develop an improved random normal interaction law based on an extended Greenwood‐Williamson (GW) model for spherical particles with surface roughness in the discrete element modelling of particle systems. The extended GW model overcomes some theoretical defects of the classic GW model when incorporated into the discrete element framework. Based on 2 nondimensional forms in which only 2 surface roughness parameters are involved, an empirical formula of the improved interaction law is derived by the curve‐fitting technique. The resulting interaction law is incorporated into discrete element modelling to investigate the mechanical response of particle systems with different surface roughness. Numerical simulations are performed to model 1‐dimensional and 3‐dimensional compression tests to explore the macro and micro characteristics of granular particles with surface roughness. The results show that surface roughness makes the initial packing of a particle assembly looser and has a greater influence on looser packed samples as expected, but an assembly with moderate roughness may exhibit a higher strength. The limitations of the current development are also highlighted. |
published_date |
2018-12-31T07:23:01Z |
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1821298688059768832 |
score |
11.047306 |