Review on field assisted metal additive manufacturing

领域(数学) 灵活性(工程) 工程类 机械工程 微观结构 工作(物理) 材料科学 纳米技术 冶金 数学 统计 纯数学
作者
Chaolin Tan,Runsheng Li,Jinlong Su,Dafan Du,Yang Du,Bonnie Attard,Youxiang Chew,Haiou Zhang,Enrique J. Lavernia,Yves Fautrelle,Jie Teng,Anping Dong
出处
期刊:International Journal of Machine Tools & Manufacture [Elsevier BV]
卷期号:189: 104032-104032 被引量:150
标识
DOI:10.1016/j.ijmachtools.2023.104032
摘要

Additive manufacturing (AM) offers unprecedented design freedom and manufacturing flexibility for processing complex components. Despite the numerous advantages of AM over conventional manufacturing methods, there are still some issues and bottlenecks that hinder the wide-scale industrial adaptation of AM techniques. The emerging field-assisted additive manufacturing (FAAM) is a designation that combines different auxiliary energy fields (e.g., ultrasound, magnetism, etc.) to overcome limitations in AM by benefiting from the intrinsic advantages of auxiliary fields. This work provides an up-to-date and dedicated review of FAAM in metallic materials, assisted by mainstream auxiliary magnetic, acoustic, mechanical, and thermal fields, as well as some emerging fields. The work principle and interaction mechanism between the field and the deposited metallic materials are elucidated. FAAM processes simulation and modelling are also reviewed. The auxiliary fields can affect the melt pool convection and dynamics, alter the temperature profile and thermal history during material solidification and induce stress or plastic deformation to the deposited materials. Hence, the effects of the auxiliary fields on the melt pool dynamics, solidification kinetics, densification behaviour, microstructure and texture, mechanical properties and fatigue performance are reviewed and discussed in detail. The perspectives on the research gap and further development trends of FAAM are also discussed.
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
卓天宇完成签到,获得积分10
刚刚
柚子完成签到 ,获得积分10
刚刚
550发布了新的文献求助10
刚刚
D1fficulty完成签到,获得积分10
刚刚
1秒前
1秒前
OmmeHabiba发布了新的文献求助10
2秒前
彪壮的如松完成签到,获得积分10
2秒前
4秒前
mango3005发布了新的文献求助10
5秒前
科研通AI5应助鳗鱼落雁采纳,获得10
7秒前
surfing完成签到,获得积分10
7秒前
ZYK完成签到,获得积分10
7秒前
冰渣凉发布了新的文献求助10
8秒前
OmmeHabiba完成签到,获得积分10
8秒前
8秒前
科研通AI5应助挑片岛屿采纳,获得10
9秒前
在水一方应助包容沛蓝采纳,获得10
10秒前
surfing发布了新的文献求助30
10秒前
火星上冥茗完成签到,获得积分10
10秒前
可靠的南露完成签到,获得积分10
12秒前
Song完成签到 ,获得积分10
12秒前
13秒前
13秒前
zzzzzzz发布了新的文献求助10
14秒前
14秒前
morry5007完成签到,获得积分10
16秒前
Akim应助冰渣凉采纳,获得10
16秒前
17秒前
18秒前
希望天下0贩的0应助ANG采纳,获得10
19秒前
Julie发布了新的文献求助10
19秒前
酷波er应助李悟尔采纳,获得50
20秒前
大秀子发布了新的文献求助10
21秒前
鳗鱼落雁发布了新的文献求助10
23秒前
碧蓝亦玉完成签到,获得积分10
24秒前
NexusExplorer应助煜钧采纳,获得10
24秒前
Owen应助斯文的傲珊采纳,获得10
24秒前
25秒前
zzzzzzz完成签到,获得积分10
25秒前
高分求助中
Thinking Small and Large 500
Algorithmic Mathematics in Machine Learning 500
Getting Published in SSCI Journals: 200+ Questions and Answers for Absolute Beginners 300
Deciphering Earth's History: the Practice of Stratigraphy 200
New Syntheses with Carbon Monoxide 200
Quanterion Automated Databook NPRD-2023 200
Interpretability and Explainability in AI Using Python 200
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 物理 生物化学 纳米技术 计算机科学 化学工程 内科学 复合材料 物理化学 电极 遗传学 量子力学 基因 冶金 催化作用
热门帖子
关注 科研通微信公众号,转发送积分 3835028
求助须知:如何正确求助?哪些是违规求助? 3377507
关于积分的说明 10498840
捐赠科研通 3096984
什么是DOI,文献DOI怎么找? 1705397
邀请新用户注册赠送积分活动 820539
科研通“疑难数据库(出版商)”最低求助积分说明 772123