An improved shear modified GTN model for ductile fracture of aluminium alloys under different stress states and its parameters identification

材料科学 极限抗拉强度 剪切(地质) 微尺度化学 复合材料 结构工程 工程类 数学 数学教育
作者
Zao He,Hao Zhu,Yumei Hu
出处
期刊:International Journal of Mechanical Sciences [Elsevier BV]
卷期号:192: 106081-106081 被引量:55
标识
DOI:10.1016/j.ijmecsci.2020.106081
摘要

To solve the problem that the original GTN model cannot accurately simulate ductile fracture of material under low stress triaxiality, many scholars have made shear improvement to it, but these shear modified GTN models have their own advantages and disadvantages and the parameters are difficult to be determined. An improved shear modified GTN (ISMGTN) model containing two independent damage mechanisms is proposed for ductile fracture prediction of materials under different stress states. The shear damage parameters, tensile damage parameters and the hardening parameters are identified using a FE inverse identification method incorporating the Latin hypercube design, Kriging approximate model and NLPQL optimization method performed in the optimization software ISIGHT. Influence of each damage parameter on damage evolution under different stress states is analyzed by a unit cell model. Accuracy of the ISMGTN model and feasibility of the damage parameters identification method are verified by performing them on a material aluminum alloy 6061 with 0°, 30° and 60° shear tests, plate tensile tests, and notched tensile tests. Additionally, fracture morphology analyses of the fractured specimen and contour plots of the effective tensile damage and effective shear damage from the FE analysis using the identified parameters are performed to study possible mechanism of deformation and failure in microscale and macroscale perspectives, respectively, and a good consistence is obtained.

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
1234发布了新的文献求助10
1秒前
星辰大海应助怡然的怀莲采纳,获得10
1秒前
1秒前
再上层楼发布了新的文献求助10
2秒前
znn发布了新的文献求助10
2秒前
2秒前
Daisy完成签到,获得积分10
3秒前
瑾瑜完成签到,获得积分10
3秒前
3秒前
风181013完成签到,获得积分10
3秒前
小马甲应助大葱采纳,获得10
4秒前
123321发布了新的文献求助10
4秒前
LBJ23发布了新的文献求助10
5秒前
xingxing完成签到,获得积分10
6秒前
7秒前
Victor完成签到 ,获得积分10
7秒前
酷酷炫饭发布了新的文献求助10
7秒前
8秒前
Criminology34应助忧郁的鱿鱼采纳,获得10
8秒前
汉堡包应助默默采纳,获得10
8秒前
慕青应助再上层楼采纳,获得10
8秒前
科研通AI2S应助1234采纳,获得10
10秒前
crown1010完成签到,获得积分10
10秒前
Owen应助yuuu采纳,获得10
11秒前
12秒前
宿帅帅发布了新的文献求助10
12秒前
12秒前
13秒前
13秒前
13秒前
ayu关闭了ayu文献求助
14秒前
14秒前
14秒前
伙腿长完成签到,获得积分10
15秒前
15秒前
勤劳的政桦完成签到,获得积分10
15秒前
yingxinfu完成签到,获得积分10
15秒前
joe55667788发布了新的文献求助10
16秒前
16秒前
充电宝应助海绵宝宝采纳,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
PowerCascade: A Synthetic Dataset for Cascading Failure Analysis in Power Systems 2000
The Composition and Relative Chronology of Dynasties 16 and 17 in Egypt 1500
Picture this! Including first nations fiction picture books in school library collections 1500
Signals, Systems, and Signal Processing 610
Unlocking Chemical Thinking: Reimagining Chemistry Teaching and Learning 555
Rheumatoid arthritis drugs market analysis North America, Europe, Asia, Rest of world (ROW)-US, UK, Germany, France, China-size and Forecast 2024-2028 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 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6365980
求助须知:如何正确求助?哪些是违规求助? 8179951
关于积分的说明 17243709
捐赠科研通 5420758
什么是DOI,文献DOI怎么找? 2868220
邀请新用户注册赠送积分活动 1845370
关于科研通互助平台的介绍 1692840