No Cover Image

Journal article 1182 views 177 downloads

An extended Greenwood-Williamson modelbased normal interaction law for discrete element modelling of spherical particles with surface roughness

Tingting Zhao, Y.T. Feng, Min Wang, Yuntian Feng Orcid Logo

International Journal for Numerical and Analytical Methods in Geomechanics

Swansea University Author: Yuntian Feng Orcid Logo

Check full text

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...

Full description

Published in: International Journal for Numerical and Analytical Methods in Geomechanics
ISSN: 0363-9061
Published: 2018
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa40270
Tags: Add Tag
No Tags, Be the first to tag this record!
first_indexed 2018-05-18T18:59:47Z
last_indexed 2018-07-13T19:34:11Z
id cronfa40270
recordtype SURis
fullrecord <?xml version="1.0"?><rfc1807><datestamp>2018-07-13T14:20:54.0951653</datestamp><bib-version>v2</bib-version><id>40270</id><entry>2018-05-18</entry><title>An extended Greenwood-Williamson modelbased normal interaction law for discrete element modelling of spherical particles with surface roughness</title><swanseaauthors><author><sid>d66794f9c1357969a5badf654f960275</sid><ORCID>0000-0002-6396-8698</ORCID><firstname>Yuntian</firstname><surname>Feng</surname><name>Yuntian Feng</name><active>true</active><ethesisStudent>false</ethesisStudent></author></swanseaauthors><date>2018-05-18</date><deptcode>CIVL</deptcode><abstract>The current work aims to develop an improved random normal interaction law based on an extended Greenwood&#x2010;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&#x2010;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&#x2010;dimensional and 3&#x2010;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.</abstract><type>Journal Article</type><journal>International Journal for Numerical and Analytical Methods in Geomechanics</journal><publisher/><issnPrint>0363-9061</issnPrint><keywords/><publishedDay>31</publishedDay><publishedMonth>12</publishedMonth><publishedYear>2018</publishedYear><publishedDate>2018-12-31</publishedDate><doi>10.1002/nag.2805</doi><url/><notes/><college>COLLEGE NANME</college><department>Civil Engineering</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>CIVL</DepartmentCode><institution>Swansea University</institution><apcterm/><lastEdited>2018-07-13T14:20:54.0951653</lastEdited><Created>2018-05-18T13:12:27.3391245</Created><path><level id="1">Faculty of Science and Engineering</level><level id="2">School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Civil Engineering</level></path><authors><author><firstname>Tingting</firstname><surname>Zhao</surname><order>1</order></author><author><firstname>Y.T.</firstname><surname>Feng</surname><order>2</order></author><author><firstname>Min</firstname><surname>Wang</surname><order>3</order></author><author><firstname>Yuntian</firstname><surname>Feng</surname><orcid>0000-0002-6396-8698</orcid><order>4</order></author></authors><documents><document><filename>0040270-18052018131420.pdf</filename><originalFilename>zhao2018.pdf</originalFilename><uploaded>2018-05-18T13:14:20.2530000</uploaded><type>Output</type><contentLength>8301320</contentLength><contentType>application/pdf</contentType><version>Accepted Manuscript</version><cronfaStatus>true</cronfaStatus><embargoDate>2019-06-08T00:00:00.0000000</embargoDate><copyrightCorrect>false</copyrightCorrect><language>eng</language></document></documents><OutputDurs/></rfc1807>
spelling 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 CIVL 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 Civil Engineering COLLEGE CODE CIVL 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
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str 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
document_store_str 1
active_str 0
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 2018-12-31T03:51:16Z
_version_ 1763752518081314816
score 11.013148

Similar Items