为研究含稀土元素铈的镁合金中高温流变行为,利用热模拟试验机对Mg-6Zn-0.5Zr-1.5Ce合金在变形温度523～673 K、应变速率0.001～1 s-1范围内进行热压缩实验.基于真应力真应变实验数据构建了单隐层前馈误差反向传播人工神经网络模型,利用该模型对ZK60-1.5Ce合金的流变应力行为进行预测,并分析了变形温度、应变速率与真应变对流变应力的影响.研究表明：Ce添加可显著细化晶粒;该镁合金的流变应力随变形温度降低和应变速率升高而增加;其流变应力行为可用双曲正弦函数进行描述,依据峰值应力拟合求得该合金的表观激活能为161.13 kJ/mol;变形温度和应变速率对流变应力的影响高于真应变.所建立的人工神经网络模型可以很好地描述该镁合金的流变应力,其预测值与实验数值吻合良好.
To investigate the rheological behavior of ZK60 alloy with rare earth addition, a T4 -ttreated Mg -6Zn- 0.5Zr- 1.5Ce magnesium alloy was investigated by compressive test using Gleeble 3800 thermal-simu- lator. The deformation temperature and the strain rate are in the range of 523 -673 K and 0.001 - 1 s-1 ,re- spectively. According to the true strain-true stress curves, a feed-forward back-propagation artificial neural net- work (ANN) was established to study the flow behaviors. We found that the addition of Ce resulted in refine- ment of microstructure. The flow stress increased as the deformation temperature decreased or as the strain rate increased. The flow stress behavior can be described using the hyperbolic sine constitutive equation and the av- erage activation energy of this alloy was calculated as 161.13 kJ/mol. The effects of deformation temperature, strain rate and strain on the flow stress behavior were studied by comparing the experimental and predicted re- suits using the developed ANN model, A good agreement between experimental and predicted result was ob-tained.
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