摘要
通过采用单向拉伸实验,在高温蠕变试验机上测定了含稀土耐高温ME20M镁合金板料在不同拉伸速度、不同温度下的力学性能,并分析了其特点与原因;利用实验得出的应力应变数据,校验了目前提出的适用于工程实际应用的含常软化因子的镁合金高温流变应力数学模型,在含常软化因子的镁合金高温流变应力数学模型的基础上,提出了适用于更大应变速率范围、温度范围的含非常软化因子的镁合金高温流变应力数学模型。通过与BP神经网络预测结果等比较,上述两个数学模型能较好地预测不同温度、应变速率范围的镁合金流变应力,但精度不如神经网络模型。
An experiment study on the mechanical properties of ME20M magnesium alloy under different temperatures and strain rates was performed on High Temperature Creep Test System under uniaxial tension, the characteristics and causes were analyzed. Utilizing stress-strain data verified mathematic model of magnesium alloy flow stress at high temperature which includes a constant intenerate factor bring forward presently, a new mathematic model of magnesium alloy flow stress at high temperature which includes a variational intenerate factor was bringed forward first based on mathematic model of magnesium alloy flow stress at high temperature which includes a constant intenerate factor. Two mathematic model mentioned above can preferably forecast magnesium alloy flow stress at different temperature and strain rate through comparing with results of BP neural network.
出处
《塑性工程学报》
EI
CAS
CSCD
北大核心
2008年第5期17-21,共5页
Journal of Plasticity Engineering
基金
江西省教育厅科研资助项目(GJJ08429)
关键词
镁合金
流变应力
数学模型
BP神经网络
magnesium alloy
flow stress
mathematic model
BP neural network