Correlation between surface textural parameter and tribological behaviour of four metal materials with laser surface texturing (LST)

材料科学 摩擦学 润滑 纹理(宇宙学) 田口方法 复合材料 正交数组 钛镍合金 酒窝 表面光洁度 形状记忆合金 图像(数学) 人工智能 计算机科学
作者
Shuo Yuan,Naiming Lin,Weihua Wang,Hongxia Zhang,Zhiqi Liu,Yuan Yu,Qunfeng Zeng,Yucheng Wu
出处
期刊:Applied Surface Science [Elsevier BV]
卷期号:583: 152410-152410 被引量:54
标识
DOI:10.1016/j.apsusc.2021.152410
摘要

Laser processing technology was used to fabricate dimple-shaped surface textures on four metal materials (316 SS, NiTi, TA2, and Ti6Al4V). A Taguchi L16 (22 × 42) orthogonal array design was used to determine the correlation between the textural parameters and dry sliding tribological behaviour of the four metal materials. Furthermore, the validity of the optimized textural parameters was determined under oil lubrication conditions. The influencing parameters were texture density, material type, type of counterpart and applied load. The output result of the mass loss was converted into a signal-to-noise ratio (S/N) for the analysis of the optimal parameter combination. Analysis of variance (ANOVA) was applied to determine the significance of the four factors. The results of the S/N analysis and the ANOVA indicated that the influence degrees of the factors on mass loss were in the following order: material type > type of counterpart > texture density > applied load. For the 316 SS, NiTi, TA2 and Ti6Al4V, the optimal texture densities were 5%, 7%, 5%, and 11%, respectively. According to the observation of the wear morphology, it was found that the surface texturing played a positive role in improving the wear resistance of the selected material, especially under oil lubrication conditions.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
慕小之完成签到,获得积分10
刚刚
诗奕发布了新的文献求助10
1秒前
2秒前
4秒前
灯火阑珊曦完成签到,获得积分10
5秒前
Rzzzz完成签到,获得积分20
5秒前
111完成签到,获得积分10
5秒前
6秒前
大个应助欢呼的巧蕊采纳,获得30
6秒前
科研通AI6.4应助lei采纳,获得10
7秒前
7秒前
wang1030完成签到,获得积分10
8秒前
NathanChen完成签到,获得积分10
9秒前
即兴发布了新的文献求助10
9秒前
科研通AI6.2应助sui采纳,获得10
10秒前
Juli完成签到,获得积分10
10秒前
Guo99完成签到,获得积分10
10秒前
老武完成签到,获得积分10
11秒前
11秒前
彭于晏应助乐观尔芙采纳,获得10
12秒前
12秒前
12秒前
panzerVI完成签到,获得积分10
13秒前
大意的迎曼完成签到,获得积分20
13秒前
江苏大猩猩完成签到,获得积分10
13秒前
sky完成签到,获得积分10
14秒前
克林沙星完成签到,获得积分10
14秒前
向阳而生发布了新的文献求助10
15秒前
南风吹梦发布了新的文献求助10
15秒前
17秒前
阿辰发布了新的文献求助10
17秒前
SciGPT应助蛋黄的阿爸采纳,获得10
18秒前
19秒前
19秒前
青柠完成签到 ,获得积分20
19秒前
悲凉的大娘完成签到 ,获得积分10
19秒前
dadas发布了新的文献求助10
20秒前
crystalese完成签到,获得积分10
20秒前
20秒前
彭于晏应助Fortitude采纳,获得10
20秒前
高分求助中
Introduction to Helicopter and Tiltrotor Flight Simulation, Second Edition 2000
Overcoming Stigma and Bias in Obesity Management 1200
Malcolm Fraser : a biography 700
Signals, Systems, and Signal Processing 610
Bounds for Statistical Estimation in Semiparametric Models 500
Forced degradation and stability indicating LC method for Letrozole: A stress testing guide 500
Ideology and Meaning-Making under the Putin Regime 450
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6488935
求助须知:如何正确求助?哪些是违规求助? 8287408
关于积分的说明 17679883
捐赠科研通 5578848
什么是DOI,文献DOI怎么找? 2914156
邀请新用户注册赠送积分活动 1891280
关于科研通互助平台的介绍 1748846