AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
Powered by AMiner. Clicking this button will take you away from SciOpen.
Home Friction Article
PDF (11.4 MB)
Cite
EndNote(RIS) BibTeX
Collect
Submit Manuscript AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Research Article | Open Access

Multiscale study of the dynamic friction coefficient due to asperity plowing

Jianqiao HU1,2, Hengxu SONG3( ), Stefan SANDFELD3, Xiaoming LIU1,2( ), Yueguang WEI4
State Key Laboratory of Nonlinear Mechanics, Institute of Mechanics, Chinese Academy of Sciences, Beijing 100190, China
School of Engineering Science, University of Chinese Academy of Sciences, Beijing 100049, China
Institute for Advanced Simulation, IAS-9: Materials Data Science and Informatics Forschungszentrum Juelich GmbH, Juelich 52425, Germany
Department of Mechanics and Engineering Science, College of Engineering, Peking University, Beijing 100871, China
Show Author Information

Abstract

A macroscopically nominal flat surface is rough at the nanoscale level and consists of nanoasperities. Therefore, the frictional properties of the macroscale-level rough surface are determined by the mechanical behaviors of nanoasperity contact pairs under shear. In this work, we first used molecular dynamics simulations to study the non-adhesive shear between single contact pairs. Subsequently, to estimate the friction coefficient of rough surfaces, we implemented the frictional behavior of a single contact pair into a Greenwood-Williamson-type statistical model. By employing the present multiscale approach, we used the size, rate, and orientation effects, which originated from nanoscale dislocation plasticity, to determine the dependence of the macroscale friction coefficient on system parameters, such as the surface roughness,separation, loading velocity, and direction. Our model predicts an unconventional dependence of the friction coefficient on the normal contact load, which has been observed in nanoscale frictional tests. Therefore, this model represents one step toward understanding some of the relevant macroscopic phenomena of surface friction at the nanoscale level.

Keywords

multiscale frictionasperity plowingdislocation plasticitysize/velocity effectcrystal orientationstatistical model

References

[1]
Bowden F P, Tabor D. The Friction and Lubrication of Solids. Oxford (UK): Oxford University Press, 1950.
[2]
Greenwood J A, Williamson J B P. Contact of nominally flat surfaces. Proc Roy Soc A Math Phys Eng Sci 295(1442): 300-319 (1966)
Google Scholar
[3]
Greenwood J A. A simplified elliptic model of rough surface contact. Wear 261(2): 191-200 (2006)
Google Scholar
[4]
Ciavarella M, Greenwood J A, Paggi M. Inclusion of “interaction” in the Greenwood and Williamson contact theory. Wear 265(5-6): 729-734 (2008)
Google Scholar
[5]
Vakis A I. Asperity interaction and substrate deformation in statistical summation models of contact between rough surfaces. J Appl Mech 81(4): 041012 (2014)
Google Scholar
[6]
Xu Y, Jackson R L, Marghitu D B. Statistical model of nearly complete elastic rough surface contact. Int J Solids Struct 51(5): 1075-1088 (2014)
Google Scholar
[7]
Song H, Vakis A I, Liu X, Van Der Giessen E. Statistical model of rough surface contact accounting for size-dependent plasticity and asperity interaction. J Mech Phys Solids 106: 1-14 (2017)
Google Scholar
[8]
Persson B N J. Theory of rubber friction and contact mechanics. J Chem Phys 115(8): 3840-3861 (2001)
Google Scholar
[9]
Hyun S, Robbins M O. Elastic contact between rough surfaces: Effect of roughness at large and small wavelengths. Tribol Int 40(10-12): 1413-1422 (2007)
Google Scholar
[10]
Carbone G. A slightly corrected Greenwood and Williamson model predicts asymptotic linearity between contact area and load. J Mech Phys Solids 57(7): 1093-1102 (2009)
Google Scholar
[11]
Putignano C, Afferrante L, Carbone G, Demelio G. The influence of the statistical properties of self-affine surfaces in elastic contacts: A numerical investigation. J Mech Phys Solids 60(5): 973-982 (2012)
Google Scholar
[12]
Afferrante L, Carbone G, Demelio G. Interacting and coalescing Hertzian asperities: A new multiasperity contact model. Wear 278-279: 28-33 (2012)
Google Scholar
[13]
Weber B, Suhina T, Junge T, Pastewka L, Brouwer A M, Bonn D. Molecular probes reveal deviations from Amontons’ law in multi-asperity frictional contacts. Nat Commun 9: 888 (2018)
Google Scholar
[14]
Malekan A, Rouhani S. Model of contact friction based on extreme value statistics. Friction 7(4): 327-339 (2019)
Google Scholar
[15]
Bush A W, Gibson R D, Thomas T R. The elastic contact of a rough surface. Wear 35(1): 87-111 (1975)
Google Scholar
[16]
Song H, Deshpande V S, Van Der Giessen E. Discrete dislocation plasticity analysis of loading rate-dependent static friction. Proc Roy Soc A Math Phys Eng Sci 472(2192): 20150877 (2016)
Google Scholar
[17]
Shi X, Zou Y W, Fang H B. Numerical investigation of the three-dimensional elastic-plastic sloped contact between two hemispheric asperities. J Appl Mech 83(10): 101004 (2016)
Google Scholar
[18]
Jankowiak T, Rusinek A, List G, Sutter G, Abed F. Numerical analysis for optimizing the determination of dynamic friction coefficient. Tribol Int 95: 86-94 (2016)
Google Scholar
[19]
Song H, Dikken R J, Nicola L, Van Der Giessen E. Plastic ploughing of a sinusoidal asperity on a rough surface. J Appl Mech 82(7): 071006 (2015)
Google Scholar
[20]
Gagel J, Weygand D, Gumbsch P. Discrete dislocation dynamics simulations of dislocation transport during sliding. Acta Mater 156: 215-227 (2018)
Google Scholar
[21]
Vadgama B N, Jackson R L, Harris D K. Molecular scale analysis of dry sliding copper asperities. Appl Nanosci 5(4): 469-480 (2014)
Google Scholar
[22]
Zhong J, Shakiba R, Adams J B. Molecular dynamics simulation of severe adhesive wear on a rough aluminum substrate. J Phys D 46(5): 055307 (2013)
Google Scholar
[23]
Molinari J F, Aghababaei R, Brink T, Frérot L, Milanese E. Adhesive wear mechanisms uncovered by atomistic simulations. Friction 6(3): 245-259 (2018)
Google Scholar
[24]
Zhang Z N, Pan S H, Yin N, Shen B, Song J. Multiscale analysis of friction behavior at fretting interfaces. Friction 9(1): 119-131 (2021)
Google Scholar
[25]
Mulvihill D M, Kartal M E, Nowell D, Hills D A. An elastic-plastic asperity interaction model for sliding friction. Tribol Int 44(12): 1679-1694 (2011)
Google Scholar
[26]
Zhang L C, Tanaka H. Towards a deeper understanding of wear and friction on the atomic scale-a molecular dynamics analysis. Wear 211(1): 44-53 (1997)
Google Scholar
[27]
Gunkelmann N, Alhafez I A, Steinberger D, Urbassek H M, Sandfeld S. Nanoscratching of iron: A novel approach to characterize dislocation microstructures. Comput Mater Sci 135: 181-188 (2017)
Google Scholar
[28]
Sandfeld S, Monavari M, Zaiser M. From systems of discrete dislocations to a continuous field description: Stresses and averaging aspects. Model Simul Mat Sci Eng 21(8): 085006 (2013)
Google Scholar
[29]
Lia J, Fang Q H, Zhang L C, Liu Y W. Subsurface damage mechanism of high speed grinding process in single crystal silicon revealed by atomistic simulations. Appl Surf Sci 324: 464-474 (2015)
Google Scholar
[30]
Müser M H, Wenning L, Robbins M O. Simple microscopic theory of Amontons's laws for static friction. Phys Rev Lett 86(7): 1295-1298 (2001)
Google Scholar
[31]
Mo Y, Turner K, Szlufarska I. Friction laws at the nanoscale. Nature 457(7233): 1116-1119 (2009)
Google Scholar
[32]
Plimpton S. Fast parallel algorithms for short-range molecular dynamics. J Comput Phys 117(1): 1-19 (1995)
Google Scholar
[33]
Mishin Y, Mehl M J, Papaconstantopoulos D A, Voter A F, Kress J D. Structural stability and lattice defects in copper: Ab initio, tight-binding, and embedded-atom calculations. Phys Rev B 63(22): 224106 (2001)
Google Scholar
[34]
Li B, Wang L, E J C, Ma H H, Luo S N. Shock response of He bubbles in single crystal Cu. J Appl Phys 116(21): 213506 (2014)
Google Scholar
[35]
Wen P, Tao G, Pang C Q, Yuan S Q, Wang Q. A molecular dynamics study of the shock-induced defect microstructure in single crystal Cu. Comput Mater Sci 124: 304-310 (2016)
Google Scholar
[36]
Hu J Q, Liu Z L, Chen K G, Zhuang Z. Investigations of shock-induced deformation and dislocation mechanism by a multiscale discrete dislocation plasticity model. Comput Mater Sci 131: 78-85 (2017)
Google Scholar
[37]
Shi J Q, Fang L, Sun K, Peng W X, Ghen J, Zhang M. Surface removal of a copper thin film in an ultrathin water environment by a molecular dynamics study. Friction 8(2): 323-334 (2020)
Google Scholar
[38]
Stukowski A, Bulatov V V, Arsenlis A. Automated identification and indexing of dislocations in crystal interfaces. Model Simul Mat Sci Eng 20(8): 085007 (2012)
Google Scholar
[39]
Stukowski A. Visualization and analysis of atomistic simulation data with OVITO-the open visualization tool. Model Simul Mat Sci Eng 18(1): 015012 (2010)
Google Scholar
[40]
Song H X, Dimiduk D, Papanikolaou S. Universality class of nanocrystal plasticity: localization and self-organization in discrete dislocation dynamics. Phys Rev Lett 122(17): 178001 (2019)
Google Scholar
[41]
Chowdhury M A, Khalil M K, Nuruzzaman D M, Rahaman M L. The effect of sliding speed and normal load on friction and wear property of aluminum. IJMME 11(1): 53-57 (2011)
Google Scholar
[42]
Kumar A, Staedler T, Jiang X. Effect of normal load and roughness on the nanoscale friction coefficient in the elastic and plastic contact regime. Beilstein J Nanotechnol 4: 66-71 (2013)
Google Scholar
[43]
Nuruzzaman D M, Chowdhury M A. Effect of load and sliding velocity on friction coefficient of aluminum sliding against different pin materials. Am J Mater Sci 2(1): 26-31 (2012)
Google Scholar
[44]
Dieterich J H. Modeling of rock friction: 1. Experimental results and constitutive equations. J Geophys Res 84(B5): 2161-2168 (1979)
Google Scholar
[45]
Van Den Ende M P A, Chen J, Ampuero J P, Niemeijer A R. A comparison between rate-and-state friction and microphysical models, based on numerical simulations of fault slip. Tectonophysics 733: 273-295 (2018)
Google Scholar
[46]
Gatzen H H, Beck M. Investigations on the friction force anisotropy of the silicon lattice. Wear 254(11): 1122-1126 (2003)
Google Scholar
[47]
Mancinelli C M, Gellman A J. Friction anisotropy at Pd(100)/Pd(100) interfaces. Langmuir 20(5): 1680-1687 (2004)
Google Scholar
[48]
Yu B J, Qian L M. Effect of crystal plane orientation on the friction-induced nanofabrication on monocrystalline silicon. Nanoscale Res Lett 8(1): 137 (2013)
Google Scholar
Friction
Volume 9 Issue 4,
August 2021
Pages 822-839
DOI: 10.1007/s40544-020-0438-4
Cite this article:
HU J, SONG H, SANDFELD S, et al. Multiscale study of the dynamic friction coefficient due to asperity plowing. Friction, 2021, 9(4): 822-839. https://doi.org/10.1007/s40544-020-0438-4

727

Views

43

Downloads

23

Crossref

N/A

Web of Science

21

Scopus

4

CSCD

Altmetrics
Received: 25 May 2020
Revised: 16 July 2020
Accepted: 31 July 2020
Published: 01 December 2020
© The author(s) 2020

This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made.

The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

To view a copy of this licence, visit http:// creativecommons.org/licenses/by/4.0/.
Return