摘要
采用Gleeble-3500型热模拟试验机对Ti-2.7Cu合金进行等温恒应变速率压缩实验,研究其在变形温度740～890℃,应变速率0.001～10s^(-1)范围内的热变形行为;并在Arrhenius型双曲正弦函数方程基础上引入应变量构建了基于应变补偿的本构模型,同时构建了基于PSO-BP神经网络的本构关系模型。结果表明:合金的流变应力对变形温度和应变速率较为敏感,变形温度升高和应变速率减小都会使流变应力降低;在高温和低应变速率条件下,流变曲线大多呈现稳态流动特征。经过误差计算得出,基于应变补偿的本构模型,预测值偏差在15%以内的数据点占85.28%;采用PSO-BP神经网络建立的本构模型,预测值偏差在15%以内的数据点占96.67%,PSO-BP神经网络模型具有更高的精度,能准确预测Ti-2.7Cu合金的高温流变应力。
The isothermal compression tests of Ti-2.7Cu alloy were tested to study the hot deformation behavior in temperature range of 740-890℃and strain rate range of 0.001-10s-1 on a Gleeble-3500 thermomechanical simulator.Constitutive model based on strain compensation was established by the Arrhenius hyperbolic sine function equation,and set up a constitutive equation for PSO-BP neural network.The results show that the flow stress is more sensitive to deformation temperature and strain rate,the flow stress is decreased with the increase of deformation temperature and decrease of strain rate;the flow stress curves present stable states in high temperature and low strain rate.For a constitutive equation based on strain compensation,the data points with the predicted error less than 15%account for 85.28%of all test data by error calculation;and for the constitutive equation based on PSO-BP neural network,the data points with the predicted error less than 15%account for 96.67%of all test data.PSO-BP neural network model has higher accuracy,it can better predict the flow stress of Ti-2.7Cu at elevated temperature.
作者
万鹏
王克鲁
鲁世强
陈虚怀
周峰
WAN Peng;WANG Ke-lu;LU Shi-qiang;CHEN Xu-huai;ZHOU Feng(School of Aeronautical Manufacturing Engineering,Nanchang Hangkong University,Nanchang 330063,China)
出处
《材料工程》
EI
CAS
CSCD
北大核心
2019年第4期113-119,共7页
Journal of Materials Engineering
基金
国家自然科学基金资助项目(51464035)
