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。
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 Ti 2AlNb based alloy plastic forming process.
作者
周峰
王克鲁
鲁世强
万鹏
陈虚怀
ZHOU Feng;WANG Ke-lu;LU Shi-qiang;WAN Peng;CHEN Xu-huai(School of Aeronautical Manufacturing Engineering,NanchangHangkong University,Nanchang 330063,China)
出处
《材料工程》
EI
CAS
CSCD
北大核心
2019年第8期141-146,共6页
Journal of Materials Engineering
基金
国家自然科学基金资助项目(51464035)
