Skip to main content

Advertisement

SpringerLink
  • Friction
  • Journal Aims and Scope
  • Submit to this journal
Multiscale study of the dynamic friction coefficient due to asperity plowing
Download PDF
Your article has downloaded

Similar articles being viewed by others

Slider with three articles shown per slide. Use the Previous and Next buttons to navigate the slides or the slide controller buttons at the end to navigate through each slide.

Theoretical and Finite Element Analysis of Static Friction Between Multi-Scale Rough Surfaces

25 October 2018

Xianzhang Wang, Yang Xu & Robert L. Jackson

Elastic Contact Mechanics of Randomly Rough Surfaces: An Assessment of Advanced Asperity Models and Persson’s Theory

14 May 2018

L. Afferrante, F. Bottiglione, … G. Carbone

Asperity-based modification on theory of contact mechanics and rubber friction for self-affine fractal surfaces

15 May 2021

Anahita Emami, Seyedmeysam Khaleghian & Saied Taheri

Friction in rough contacts of linear viscoelastic surfaces with anisotropic statistical properties

27 June 2019

Luciano Afferrante, Carmine Putignano, … Giuseppe Carbone

Friction and Plasticity in Contacts Between Amorphous Solids

09 April 2021

Binquan Luan & Mark O. Robbins

Experimental insights into adhesion and friction between nominally dry rough surfaces

01 December 2022

Bart Weber, Julien Scheibert, … Ali Dhinojwala

A Simple Mechanistic Model for Friction of Rough Partially Lubricated Surfaces

17 June 2021

Gianluca Costagliola, Tobias Brink, … Jean-François Molinari

Experimental investigation and finite element simulation of the effect of surface roughness on nanoscratch testing

08 May 2019

Mohsen Nazemian & Mohammad Chamani

Multiscale Friction Simulation of Dry Polymer Contacts: Reaching Experimental Length Scales by Coupling Molecular Dynamics and Contact Mechanics

06 May 2021

Daniele Savio, Jannik Hamann, … Michael Moseler

Download PDF
  • Research Article
  • Open Access
  • Published: 01 December 2020

Multiscale study of the dynamic friction coefficient due to asperity plowing

  • Jianqiao Hu1,2,
  • Hengxu Song3,
  • Stefan Sandfeld3,
  • Xiaoming Liu1,2 &
  • …
  • Yueguang Wei4 

Friction volume 9, pages 822–839 (2021)Cite this article

  • 697 Accesses

  • 16 Citations

  • Metrics details

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.

Download to read the full article text

Working on a manuscript?

Avoid the common mistakes

References

  1. Bowden F P, Tabor D. The Friction and Lubrication of Solids. Oxford (UK): Oxford University Press, 1950.

    MATH  Google Scholar 

  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)

    MathSciNet  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)

    MathSciNet  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)

    MATH  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)

    MATH  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 

Download references

Acknowledgements

This work was supported by the National Natural Science Foundation of China (Nos. 11802310 and 11772334), the Youth Innovation Promotion Association CAS (No. 2018022), and by the Strategic Priority Research Program of the Chinese Academy of Sciences (No. XDB22040501). HS and SS acknowledge financial support from the European Research Council through the ERC Grant Agreement No. 759419 MuDiLingo (“A Multiscale Dislocation Language for Data-Driven Materials Science”).

Author information

Authors and Affiliations

  1. State Key Laboratory of Nonlinear Mechanics, Institute of Mechanics, Chinese Academy of Sciences, Beijing, 100190, China

    Jianqiao Hu & Xiaoming Liu

  2. School of Engineering Science, University of Chinese Academy of Sciences, Beijing, 100049, China

    Jianqiao Hu & Xiaoming Liu

  3. Institute for Advanced Simulation, IAS-9: Materials Data Science and Informatics Forschungszentrum Juelich GmbH, Juelich, 52425, Germany

    Hengxu Song & Stefan Sandfeld

  4. Department of Mechanics and Engineering Science, College of Engineering, Peking University, Beijing, 100871, China

    Yueguang Wei

Authors
  1. Jianqiao Hu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hengxu Song
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Stefan Sandfeld
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Xiaoming Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Yueguang Wei
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Hengxu Song or Xiaoming Liu.

Additional information

Jianqiao HU. He received his bachelor and Ph.D. degrees in engineering mechanics from Tsinghua University, China, in 2012 and 2017, respectively. He currently works as an assistant research fellow in the State Key Laboratory of Nonlinear Mechanics, Institute of Mechanics, Chinese Academy of Sciences. His research interests include the multiscale study of contact, friction, and wear.

Hengxu SONG. He received his bachelor degree in engineering mechanics in 2010 from Tongji University, and master degree in solid mechanics in 2012 from Tsinghua University, and Ph.D. degree in applied physics from University of Groningen, the Netherlands. He currently works as a postdoc research fellow in Institute for Advanced Simulation, IAS-9: Materials Data Science and Informatics Forschungszentrum Juelich GmbH, Germany. His research interests include multiscale modelling, micromechanics of materials, contact mechanics, friction, and dislocation plasticity.

Xiaoming LIU. He received his bachelor degree in engineering mechanics from Xi’an Jiaotong University in 2003. Then, he obtained Ph.D. degree in engineering mechanics from Tsinghua University in 2008. He is currently a full professor in the State Key Laboratory of Nonlinear Mechanics, Institute of Mechanics, Chinese Academy of Sciences. His current research focuses on how the microscale plasticity and size effect change the sliding of two blocks.

Rights and permissions

Open Access: 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/.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Hu, J., Song, H., Sandfeld, S. et al. Multiscale study of the dynamic friction coefficient due to asperity plowing. Friction 9, 822–839 (2021). https://doi.org/10.1007/s40544-020-0438-4

Download citation

  • Received: 25 May 2020

  • Revised: 16 July 2020

  • Accepted: 31 July 2020

  • Published: 01 December 2020

  • Issue Date: August 2021

  • DOI: https://doi.org/10.1007/s40544-020-0438-4

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Keywords

  • multiscale friction
  • asperity plowing
  • dislocation plasticity
  • size/velocity effect
  • crystal orientation
  • statistical model
Download PDF

Working on a manuscript?

Avoid the common mistakes

Advertisement

Over 10 million scientific documents at your fingertips

Switch Edition
  • Academic Edition
  • Corporate Edition
  • Home
  • Impressum
  • Legal information
  • Privacy statement
  • California Privacy Statement
  • How we use cookies
  • Manage cookies/Do not sell my data
  • Accessibility
  • FAQ
  • Contact us
  • Affiliate program

Not affiliated

Springer Nature

© 2023 Springer Nature Switzerland AG. Part of Springer Nature.