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微/纳米尺度下随机粗糙表面无润滑接触的静摩擦模型

A Static Friction Model for Unlubricated Contact of Random Rough Surfaces at Micro/Nano Scale.

作者信息

Zhu Shengguang, Ni Liyong

机构信息

Zhongshan Institute, University of Electronic Science and Technology of China, Zhongshan 528402, China.

College of Mechanical Engineering, South China University of Technology, Guangzhou 510641, China.

出版信息

Micromachines (Basel). 2021 Mar 29;12(4):368. doi: 10.3390/mi12040368.

Abstract

A novel static friction model for the unlubricated contact of random rough surfaces at micro/nano scale is presented. This model is based on the energy dissipation mechanism that states that changes in the potential of the surfaces in contact lead to friction. Furthermore, it employs the statistical theory of two nominally flat rough surfaces in contact, which assumes that the contact between the equivalent rough peaks and the rigid flat plane satisfies the condition of interfacial friction. Additionally, it proposes a statistical coefficient of positional correlation that represents the contact situation between the equivalent rough surface and the rigid plane. Finally, this model is compared with the static friction model established by Kogut and Etsion (KE model). The results of the proposed model agree well with those of the KE model in the fully elastic contact zone. For the calculation of dry static friction of rough surfaces in contact, previous models have mainly been based on classical contact mechanics; however, this model introduces the potential barrier theory and statistics to address this and provides a new way to calculate unlubricated friction for rough surfaces in contact.

摘要

提出了一种用于微/纳米尺度下随机粗糙表面非润滑接触的新型静摩擦模型。该模型基于能量耗散机制,即接触表面势能的变化会导致摩擦。此外,它采用了两个名义上平坦的粗糙表面接触的统计理论,该理论假设等效粗糙峰与刚性平面之间的接触满足界面摩擦条件。此外,它还提出了一个表示等效粗糙表面与刚性平面之间接触情况的位置相关统计系数。最后,将该模型与Kogut和Etsion建立的静摩擦模型(KE模型)进行了比较。在完全弹性接触区,所提出模型的结果与KE模型的结果吻合良好。对于接触粗糙表面的干静摩擦计算,以前的模型主要基于经典接触力学;然而,该模型引入了势垒理论和统计学来解决这一问题,并为计算接触粗糙表面的非润滑摩擦提供了一种新方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec64/8066081/e85f395f4955/micromachines-12-00368-g001.jpg

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