Texture Control for Improving Deep Drawability in Rolled and Annealed Aluminum Alloy Sheets

材料科学 再结晶(地质) 合金 退火(玻璃) 冶金 拉深 限制 纹理(宇宙学) 表层 复合材料 图层(电子) 人工智能 机械工程 古生物学 工程类 生物 计算机科学 图像(数学)
作者
Hirofumi Inoue,Takayuki Takasugi
出处
期刊:Materials transactions [The Japan Institute of Metals]
卷期号:48 (8): 2014-2022 被引量:88
标识
DOI:10.2320/matertrans.l-mra2007871
摘要

In order to find a possibility of texture control for improving deep drawability in rolled and annealed aluminum alloys, the relation among recrystallization texture, r-value and limiting drawing ratio was examined for sheet materials with various textures. By using specimens with {111} texture prepared artificially, limiting drawing ratio could be measured in a wide range of average r-value from 0.4 to 1.6. Experimental results demonstrated that there was a positive correlation between average r-value and limiting drawing ratio even in aluminum alloys. This means that an increase in average r-value leads to improvement of deep drawability. Warm rolling that forms shear texture including {111} components, therefore, was conducted to enhance average r-value for Al-Mg and Al-Mg-Si alloys. Recrystallization texture of an annealed Al-Mg alloy consisted of retained shear texture components in the surface layer and cube plus R orientations in the center layer. The average r-value was considerably improved compared with that of a cold rolled sheet. On the other hand, a T4-treated Al-Mg-Si alloy had a relatively weak cube texture on the whole, though the surface layer showed a different texture from the center. In this case, warm rolling was ineffective in improving average r-value, in spite of the existence of surface texture with higher r-value. However, the relation between recrystallization texture and experimental r-value was successfully explained for the Al-Mg-Si alloy as well as for the Al-Mg alloy, based on r-value calculations from overall texture through sheet thickness.

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
紫色奶萨完成签到 ,获得积分10
1秒前
大葱发布了新的文献求助10
2秒前
li发布了新的文献求助10
3秒前
希妍完成签到,获得积分10
3秒前
悦耳羊完成签到,获得积分10
4秒前
Adam罗发布了新的文献求助10
9秒前
顾矜应助发大财采纳,获得10
9秒前
小牧鱼完成签到,获得积分10
11秒前
11秒前
ZHH发布了新的文献求助10
12秒前
夨坕发布了新的文献求助10
12秒前
15秒前
aaa关闭了aaa文献求助
15秒前
动听的灯泡完成签到,获得积分10
16秒前
量子星尘发布了新的文献求助10
16秒前
小蘑菇应助xuan采纳,获得10
19秒前
NexusExplorer应助大葱采纳,获得10
19秒前
20秒前
20秒前
Popeye发布了新的文献求助10
21秒前
22秒前
震震发布了新的文献求助10
22秒前
共享精神应助spume采纳,获得10
22秒前
慕青应助Adam罗采纳,获得10
23秒前
魔幻青枫发布了新的文献求助10
24秒前
伊力扎提发布了新的文献求助10
25秒前
所所应助满庭芳采纳,获得10
25秒前
26秒前
26秒前
26秒前
忍冬发布了新的文献求助10
27秒前
小王完成签到 ,获得积分10
27秒前
完美世界应助高高的玫瑰采纳,获得10
27秒前
27秒前
28秒前
落后世界完成签到,获得积分10
28秒前
儒雅寄灵完成签到,获得积分10
28秒前
大模型应助研友_5ZlN6L采纳,获得10
28秒前
29秒前
高分求助中
Theoretical Modelling of Unbonded Flexible Pipe Cross-Sections 10000
(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
《药学类医疗服务价格项目立项指南(征求意见稿)》 880
花の香りの秘密―遺伝子情報から機能性まで 800
3rd Edition Group Dynamics in Exercise and Sport Psychology New Perspectives Edited By Mark R. Beauchamp, Mark Eys Copyright 2025 600
1st Edition Sports Rehabilitation and Training Multidisciplinary Perspectives By Richard Moss, Adam Gledhill 600
Digital and Social Media Marketing 500
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5620905
求助须知:如何正确求助?哪些是违规求助? 4705599
关于积分的说明 14932648
捐赠科研通 4763944
什么是DOI,文献DOI怎么找? 2551370
邀请新用户注册赠送积分活动 1513876
关于科研通互助平台的介绍 1474715