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材料工程  2019, Vol. 47 Issue (4): 113-119    DOI: 10.11868/j.issn.1001-4381.2018.000426
  研究论文 本期目录 | 过刊浏览 | 高级检索 |
基于应变补偿和PSO-BP神经网络的Ti-2.7Cu合金本构关系
万鹏, 王克鲁, 鲁世强, 陈虚怀, 周峰
南昌航空大学 航空制造工程学院, 南昌 330063
Constitutive modeling of Ti-2.7Cu alloy based on strain compensation and PSO-BP neural network
WAN Peng, WANG Ke-lu, LU Shi-qiang, CHEN Xu-huai, ZHOU Feng
School of Aeronautical Manufacturing Engineering, Nanchang Hangkong University, Nanchang 330063, China
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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。
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万鹏
王克鲁
鲁世强
陈虚怀
周峰
关键词 Ti-2.7Cu合金热变形行为本构模型应变补偿PSO-BP神经网络    
Abstract: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.
Key wordsTi-2.7Cu alloy    hot deformation behavior    activation energy    strain compensation    PSO-BP neural network
收稿日期: 2018-04-23      出版日期: 2019-04-19
中图分类号:  TG146.2  
通讯作者: 王克鲁(1968-),男,教授,博士,主要从事金属材料组织与性能控制研究,联系地址:江西省南昌市红谷滩新区南昌航空大学前湖校区丰和南大道696号(330063),E-mail:wangkelu@126.com     E-mail: wangkelu@126.com
引用本文:   
万鹏, 王克鲁, 鲁世强, 陈虚怀, 周峰. 基于应变补偿和PSO-BP神经网络的Ti-2.7Cu合金本构关系[J]. 材料工程, 2019, 47(4): 113-119.
WAN Peng, WANG Ke-lu, LU Shi-qiang, CHEN Xu-huai, ZHOU Feng. Constitutive modeling of Ti-2.7Cu alloy based on strain compensation and PSO-BP neural network. Journal of Materials Engineering, 2019, 47(4): 113-119.
链接本文:  
http://jme.biam.ac.cn/CN/10.11868/j.issn.1001-4381.2018.000426      或      http://jme.biam.ac.cn/CN/Y2019/V47/I4/113
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