Modelling of surface morphology and roughness in fluid jet polishing

抛光 磨料 喷射(流体) 表面粗糙度 材料科学 表面光洁度 机械工程 机械加工 微尺度化学 机械 计算机科学 工程制图 复合材料 冶金 物理 工程类 数学 数学教育
作者
Zili Zhang,Chi Fai Cheung,Chunjin Wang,Jiang Guo
出处
期刊:International Journal of Mechanical Sciences [Elsevier BV]
卷期号:242: 107976-107976 被引量:30
标识
DOI:10.1016/j.ijmecsci.2022.107976
摘要

Fluid jet polishing (FJP) has been extensively used in various kinds of fields such as precision molding, optical components, etc. However, previous works mainly focused on the material removal process on the macro-scale (e.g., tool influence function, surface generation) to improve the form accuracy, the understanding of surface morphology evolution of FJP on the micro-scale is still far from complete, which makes it difficult to predict the surface quality under certain polishing conditions. Time-consuming and high-cost trial and error are usually needed to obtain suitable polishing conditions for specific surface quality requirements. In this paper, a physical model was developed to predict the surface morphology and roughness after FJP, by combining the computational fluid dynamics (CFD) simulation and kinetic analysis of the abrasives. The single abrasive erosion process including indentation action, ploughing action, and cutting action was analyzed by kinetic analysis. Besides, the overlap of single abrasive erosion pits was modeled to simulate the surface morphology evolution in FJP and determine the surface roughness after polishing. Different parameters were considered in the model including jet pressure, jet angle, and abrasive size. A series of polishing experiments were conducted to validate this model and the effect of different polishing parameters on surface quality was elucidated by the impact velocity distribution and erosion morphologies. It is found that the simulation results agree well with the experimental results. This paper not only provides a deeper understanding of the microscale material removal in FJP, but also provides an effective method for the prediction of surface roughness in FJP.
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
1秒前
1秒前
1秒前
yu发布了新的文献求助10
2秒前
科研通AI6.4应助学分采纳,获得10
2秒前
2秒前
2秒前
3秒前
shi发布了新的文献求助10
3秒前
3秒前
4秒前
4秒前
sertraline发布了新的文献求助10
4秒前
小宇宙完成签到,获得积分10
5秒前
5秒前
土豆发布了新的文献求助10
5秒前
5秒前
6秒前
6秒前
默默发布了新的文献求助10
6秒前
6秒前
JamesPei应助Harrison采纳,获得10
6秒前
完美世界应助柚子采纳,获得10
6秒前
六也发布了新的文献求助10
7秒前
DW应助turnsole采纳,获得10
7秒前
7秒前
笨笨藏鸟完成签到,获得积分10
8秒前
咕涵发布了新的文献求助10
8秒前
8秒前
8秒前
Zhou_zp完成签到,获得积分10
9秒前
9秒前
Easton发布了新的文献求助10
9秒前
10秒前
AtoPos发布了新的文献求助10
11秒前
乐观发布了新的文献求助10
11秒前
涂玉含发布了新的文献求助10
11秒前
慢慢发布了新的文献求助10
11秒前
科研通AI6.4应助凌波丽采纳,获得10
11秒前
Baylin发布了新的文献求助10
11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
Essentials of Carbohydrate Chemistry and Biochemistry, 4th Edition 800
Organizational Behavior 510
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
CLSI VET01S-2024 Performance Standards for Antimicrobial Disk and Dilution Susceptibility Tests for Bacteria Isolated From Animals (7th Ed) 500
A Case Study on Hotels as Noncongregate Emergency Living Accommodations for Returning Citizens 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 计算机科学 化学工程 工程类 有机化学 物理 复合材料 生物化学 内科学 细胞生物学 基因 遗传学 免疫学 冶金 光电子学 癌症研究
热门帖子
关注 科研通微信公众号,转发送积分 7764887
求助须知:如何正确求助?哪些是违规求助? 9309156
关于积分的说明 20309602
捐赠科研通 7349682
什么是DOI,文献DOI怎么找? 3314656
关于科研通互助平台的介绍 2464003
邀请新用户注册赠送积分活动 2328973