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
woshi123应助谢同学采纳,获得10
刚刚
汉堡包应助ooooo采纳,获得10
1秒前
彭于晏应助阿涼又困了采纳,获得10
1秒前
NexusExplorer应助haitun采纳,获得10
2秒前
3秒前
天外发布了新的文献求助10
3秒前
枫叶发布了新的文献求助30
4秒前
Orange应助MYY采纳,获得10
5秒前
恢复出厂设置完成签到,获得积分10
6秒前
6秒前
日常卖命完成签到 ,获得积分10
7秒前
8秒前
怡然觅云发布了新的文献求助30
10秒前
谦让水池完成签到,获得积分10
12秒前
我是老大应助liva采纳,获得10
12秒前
13秒前
乐乐应助cong采纳,获得30
13秒前
Literature应助江子川采纳,获得30
14秒前
瓜牛不瓜发布了新的文献求助30
14秒前
15秒前
CipherSage应助cody采纳,获得10
17秒前
学霸业发布了新的文献求助30
17秒前
18秒前
丘比特应助Anker采纳,获得10
20秒前
20秒前
Zroo完成签到,获得积分10
20秒前
chenpoem完成签到,获得积分10
22秒前
外向烨磊发布了新的文献求助10
24秒前
25秒前
26秒前
精明的水杯完成签到,获得积分10
26秒前
26秒前
27秒前
27秒前
吉他平方完成签到,获得积分10
27秒前
flow完成签到,获得积分10
28秒前
1234发布了新的文献求助10
28秒前
亦依然完成签到 ,获得积分10
29秒前
huangdinghuang完成签到,获得积分10
29秒前
CipherSage应助端庄的靖巧采纳,获得10
30秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Römisch-Germanische Forschungen 1000
The Oxford Handbook of Digital Classical Studies 550
China Pluperfect I: Epistemology of Past and Outside in Chinese Art 520
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
The fast track to determining transfer functions of linear circuits: The student guide 500
The Analytical and Numerical Solution of Electric and Magnetic Fields 500
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 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7617949
求助须知:如何正确求助?哪些是违规求助? 9193175
关于积分的说明 19703263
捐赠科研通 7190429
什么是DOI,文献DOI怎么找? 3272065
关于科研通互助平台的介绍 2434843
邀请新用户注册赠送积分活动 2267229