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2222材料工程  2019, Vol. 47 Issue (8): 141-146    DOI: 10.11868/j.issn.1001-4381.2017.001548
  研究论文 本期目录 | 过刊浏览 | 高级检索 |
Ti-22Al-24Nb-0.5Y合金流变行为及BP神经网络高温本构模型
周峰, 王克鲁(), 鲁世强, 万鹏, 陈虚怀
南昌航空大学 航空制造工程学院, 南昌 330063
Flow behavior and BP neural network high temperature constitutive model of Ti-22Al-24Nb-0.5Y alloy
Feng ZHOU, Ke-lu WANG(), Shi-qiang LU, Peng WAN, Xu-huai CHEN
School of Aeronautical Manufacturing Engineering, Nanchang Hangkong University, Nanchang 330063, China
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摘要 

利用Gleeble-3500热模拟试验机进行等温恒应变热压缩实验,以实验获得的数据为基础,研究Ti-22Al-24Nb-0.5Y合金流变行为,通过正交实验对影响合金的流变应力因素进行分析,并建立基于BP神经网络的合金高温本构关系模型。结果表明:影响合金流变应力的主要因素依次为应变速率、变形温度和应变量;Ti-22Al-24Nb-0.5Y合金在热变形时的流变应力对应变速率和变形温度都较为敏感。当变形温度较低,应变速率较高时,合金变形呈流变软化特征,当变形温度较高,应变速率较低时,合金变形趋向于稳态流动;利用BP神经网络建立的合金高温本构关系模型,具有较高的精度,其相关性系数达到0.9949,平均相对误差在3.23%,预测值偏差在10%以内的数据点达98.79%,该预测模型可作为Ti2AlNb基合金塑性成形过程有限元模拟的本构关系。

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周峰
王克鲁
鲁世强
万鹏
陈虚怀
关键词 Ti-22Al-24Nb-0.5Y合金流变应力正交实验BP神经网络本构关系模型    
Abstract

Isothermal constant strain thermal compression test was carried out by Gleeble-3500 thermal simulation test machine. Based on the experimental data, the flow behavior of Ti-22Al-24Nb-0.5Y alloy was studied. The factors affecting the flow stress of the alloy were analyzed by orthogonal test, and a constitutive model based on BP neural network was established. The results show that the main factors affecting the flow stress of the alloy successively are the strain rate, deformation temperature and strain. The flow stress of Ti-22Al-24Nb-0.5Y alloy in hot deformation is more sensitive to the strain rate and the deformation temperature. The deformation of the alloy is characterized by flow softening at low deformation temperature and high strain rate, but the deformation tends to steady flow with high deformation temperature and low strain rate. The high temperature constitutive model of alloy established by BP neural network has high accuracy. The correlation coefficient reaches 0.9949, the average relative error is 3.23%, the predictive value with the deviation within 10% data points reaches up to 98.79%, and the prediction model can be used as a constitutive relation for the finite element simulation in Ti2AlNb based alloy plastic forming process.

Key wordsTi-22Al-24Nb-0.5Y alloy    flow stress    orthogonal test    BP neural network    constitutive relationship model
收稿日期: 2017-12-17      出版日期: 2019-08-22
中图分类号:  TG146.2  
基金资助:国家自然科学基金资助项目(51464035)
通讯作者: 王克鲁     E-mail: wangkelu@126.com
作者简介: 王克鲁(1968-), 男, 教授, 博士, 研究方向:航空难变形材料与新型金属材料, 联系地址:江西省南昌市丰和南大道696号南昌航空大学M栋教学楼(330063), E-mail:wangkelu@126.com
引用本文:   
周峰, 王克鲁, 鲁世强, 万鹏, 陈虚怀. Ti-22Al-24Nb-0.5Y合金流变行为及BP神经网络高温本构模型[J]. 材料工程, 2019, 47(8): 141-146.
Feng ZHOU, Ke-lu WANG, Shi-qiang LU, Peng WAN, Xu-huai CHEN. Flow behavior and BP neural network high temperature constitutive model of Ti-22Al-24Nb-0.5Y alloy. Journal of Materials Engineering, 2019, 47(8): 141-146.
链接本文:  
http://jme.biam.ac.cn/CN/10.11868/j.issn.1001-4381.2017.001548      或      http://jme.biam.ac.cn/CN/Y2019/V47/I8/141
Fig.1  Ti-22Al-24Nb-0.5Y合金铸态组织
Level Experiment factor
Strain rate(A)/ s-1 Deformation temperature(B)/℃ Strain(C)
1 0.001 930 0.05
2 1.0 990 0.55
3 0.1 1080 0.85
Table 1  正交实验因素水平
No A B C D Flow stress/MPa
1 1(0.001s-1) 1(930℃) 1(0.05) 1 187.75
2 1(0.001s-1) 2(990℃) 2(0.55) 2 72.20
3 1(0.001s-1) 3(1080℃) 3(0.85) 3 24.74
4 2(1.0s-1) 1(930℃) 2(0.55) 3 343.64
5 2(1.0s-1) 2(990℃) 3(0.85) 1 378.22
6 2(1.0s-1) 3(1080℃) 1(0.05) 2 157.83
7 3(0.1s-1) 1(930℃) 3(0.85) 2 350.71
8 3(0.1s-1) 2(990℃) 1(0.05) 3 203.96
9 3(0.1s-1) 3(1080℃) 2(0.55) 1 168.23
K1 94.90 294.70 251.22 244.73
K2 293.23 218.13 183.18 190.78
K3 240.97 116.93 194.69 193.58
R 198.33 177.77 68.04 53.95
Table 2  实验方案及结果分析
Fig.2  Ti-22Al-24Nb-0.5Y合金不同变形条件下的应力-应变曲线
(a)=0.001s-1; (b)=1.0s-1
Fig.3  Ti-22Al-24Nb-0.5Y合金不同应变速率下的温升曲线
(a) =0.001s-1; (b) =1.0s-1
Fig.4  BP神经网络结构
Fig.5  Ti-22Al-24Nb-0.5Y合金流变应力实验值与BP预测值的比较
Fig.6  不同变形条件下BP神经网络本构模型流变应力预测值与实验数据对比
(a) =0.001s-1; (b) =1.0s-1
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