共 81 条
Research Progress on the Design of Surface Texture in Tribological Applications: A Mini-Review
被引:0
作者:
Chen, Keyang
[1
,2
,3
,4
]
Tang, Yunqing
[1
,2
,3
,4
,5
]
机构:
[1] Shandong Univ, Sch Mech Engn, Jinan 250061, Peoples R China
[2] Shandong Univ, State key Lab Adv Equipment & Technol Met Forming, Jinan 250061, Peoples R China
[3] Minist Educ, Key Lab High Efficiency & Clean Mech Manufacture, Jinan 250061, Peoples R China
[4] Key Natl Demonstrat Ctr Expt Mech Engn Educ, Jinan 250061, Peoples R China
[5] Guilin Univ Elect Technol, Guangxi Key Lab Mfg Syst & Adv Mfg Technol, Guilin 541004, Peoples R China
来源:
SYMMETRY-BASEL
|
2024年
/
16卷
/
11期
基金:
中国国家自然科学基金;
关键词:
surface texture;
wear resistance;
friction;
symmetry and asymmetry;
LUBRICATION;
PERFORMANCE;
OPTIMIZATION;
PARAMETERS;
FRICTION;
STEEL;
REGIMES;
DIMPLE;
SHAPE;
FULL;
D O I:
10.3390/sym16111523
中图分类号:
O [数理科学和化学];
P [天文学、地球科学];
Q [生物科学];
N [自然科学总论];
学科分类号:
07 ;
0710 ;
09 ;
摘要:
Surface texturing technology, as an advanced method to improve surface tribological properties of friction pairs, has been widely used in many fields. In this work, the influence of surface texture parameters on tribological properties of friction pair surfaces are reviewed. For the currently most developed surface textures with symmetry and simple geometries and distributions, it is found that they could help reduce friction mainly by enhancing their dynamic pressure lubrication capability, storing abrasive debris and lubricants for dynamic lubrication or promoting the formation of friction films on surfaces of friction pairs. The dominant design parameters of surface textures influencing their tribological performance are found to be shape, geometry and density, while working condition, including contact mode and lubrication situation, also has a significant influence on the performance of surface textures with specific features. Asymmetric textures and multi-scale composite textures also show great tribological performance, while the coupling mechanism across different factors is still unclear, which makes it a challenge to maximize the advantage of asymmetric or multi-scale composite textures. The development of machine learning provides promising approaches for the multi-parameter optimization of surface textures, which is expected to promote and accelerate the design of advanced surface textures.
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页数:21
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