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.

Details

Title
Multiscale study of the dynamic friction coefficient due to asperity plowing
Author
Hu Jianqiao 1 ; Song Hengxu 2 ; Sandfeld Stefan 2 ; Liu, Xiaoming 1 ; Yueguang, Wei 3 

 Chinese Academy of Sciences, State Key Laboratory of Nonlinear Mechanics, Institute of Mechanics, Beijing, China (GRID:grid.9227.e) (ISNI:0000000119573309); University of Chinese Academy of Sciences, School of Engineering Science, Beijing, China (GRID:grid.410726.6) (ISNI:0000 0004 1797 8419) 
 IAS-9: Materials Data Science and Informatics Forschungszentrum Juelich GmbH, Institute for Advanced Simulation, Juelich, Germany (GRID:grid.8385.6) (ISNI:0000 0001 2297 375X) 
 Peking University, Department of Mechanics and Engineering Science, College of Engineering, Beijing, China (GRID:grid.11135.37) (ISNI:0000 0001 2256 9319) 
Pages
822-839
Publication year
2021
Publication date
Aug 2021
Publisher
Springer Nature B.V.
ISSN
22237690
e-ISSN
22237704
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2503529821
Copyright
© The author(s) 2020. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.