Study of microstructure evolution of magnesium alloy cylindrical part with longitudinal inner ribs during hot flow forming by coupling ANN-modified CA and FEA

微观结构 材料科学 镁合金 联轴节(管道) 变形(气象学) 复合材料 合金 压痕硬度 有限元法 应变率 冶金 结构工程 工程类
作者
Jinchuan Long,Gangfeng Xiao,Qinxiang Xia,Xinyun Wang
出处
期刊:Journal of Magnesium and Alloys [Elsevier BV]
卷期号:12 (8): 3229-3244 被引量:9
标识
DOI:10.1016/j.jma.2022.11.009
摘要

Hot flow forming (HFF) is a promising forming technology to manufacture thin-walled cylindrical part with longitudinal inner ribs (CPLIRs) made of magnesium (Mg) alloys, which has wide applications in the aerospace field. However, due to the thermo-mechanical coupling effect and the existence of stiffened structure, complex microstructure evolution and uneven microstructure occur easily at the cylindrical wall (CW) and inner rib (IR) of Mg alloy thin-walled CPLIRs during the HFF. In this paper, a modified cellular automaton (CA) model of Mg alloy considering the effects of deformation conditions on material parameters was developed using the artificial neural network (ANN) method. It is found that the ANN-modified CA model exhibits better predictability for the microstructure of hot deformation than the conventional CA model. Furthermore, the microstructure evolution of ZK61 alloy CPLIRs during the HFF was analyzed by coupling the modified CA model and finite element analysis (FEA). The results show that compared with the microstructure at the same layer of the IR, more refined grains and less sufficient DRX resulted from larger strain and strain rate occur at that of the CW; various differences of strain and strain rate in the wall-thickness exist between the CW and IR, which leads to the inhomogeneity of microstructure rising firstly and declining from the inside layer to outside layer; the obtained Hall-Petch relationship between the measured microhardness and predicted grain sizes at the CW and the IR indicates the reliability of the coupled FEA-CA simulation results.
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
2秒前
Zak完成签到 ,获得积分10
2秒前
genguzhuandi发布了新的文献求助10
2秒前
2秒前
2秒前
2秒前
友好旭尧完成签到,获得积分10
3秒前
宋万里发布了新的文献求助10
3秒前
杨123发布了新的文献求助10
3秒前
3秒前
SciGPT应助欧阳万仇采纳,获得10
4秒前
飞行中的鱼完成签到,获得积分10
5秒前
马尔斯完成签到,获得积分10
5秒前
6秒前
Linn完成签到 ,获得积分10
6秒前
7秒前
allenise完成签到,获得积分10
7秒前
Shandongdaxiu发布了新的文献求助10
7秒前
mirrovo发布了新的文献求助10
7秒前
cfpilot发布了新的文献求助10
7秒前
molihuakai应助lanshuitai采纳,获得20
8秒前
8秒前
刘源发布了新的文献求助10
8秒前
彭鱼晏发布了新的文献求助10
8秒前
花城发布了新的文献求助10
9秒前
情怀应助qiu采纳,获得10
9秒前
wangwang发布了新的文献求助10
10秒前
摆烂女硕发布了新的文献求助10
10秒前
科目三应助幸福台灯采纳,获得10
11秒前
殷勤的紫槐应助kaka12161采纳,获得200
11秒前
11秒前
13秒前
lu关注了科研通微信公众号
13秒前
yangbohhan完成签到,获得积分10
14秒前
bkagyin应助兴奋的万声采纳,获得10
14秒前
15秒前
16秒前
丘比特应助lihuahui采纳,获得10
17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
Cronologia da história de Macau 5000
Merrill's Atlas of Radiographic Positioning and Procedures - 3-Volume Set, 16th Edition 2000
Petrology and Plate Tectonics 800
Matrix Methods in Data Mining and Pattern Recognition 540
Interactions of Vowel Quality and Prosody in East Slavic 500
Vander's Renal Physiology第10版 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 7051648
求助须知:如何正确求助?哪些是违规求助? 8716147
关于积分的说明 18454692
捐赠科研通 6569459
什么是DOI,文献DOI怎么找? 3120272
关于科研通互助平台的介绍 2208749
邀请新用户注册赠送积分活动 2095924