粉末冶金Fe-2Cu-0.5C钢高温拉伸变形行为  

Elevated temperature tensile deformation behavior of powder metallurgy Fe−2Cu−0.5C steels

作　　者：简杰 郭彪[1] 李强 李肖 宋久鹏 张羽 敖进清[1] 黄勇 JIAN Jie;GUO Biao;LI Qiang;LI Xiao;SONG Jiupeng;ZHANG Yu;AO Jinqing;HUANG Yong(School of Materials Science and Engineering,Xihua University,Chengdu 610039,China;GKN(Bazhou)Metal Powder Co.,Ltd.,Bazhou 065701,China)

机构地区：[1]西华大学材料科学与工程学院,成都610039 [2]吉凯恩(霸州)金属粉末有限公司,廊坊065701

出　　处：《粉末冶金技术》2023年第6期577-585,共9页Powder Metallurgy Technology

基　　金：四川省科技厅重点研发计划项目(2022YFG0346)。

摘　　要：使用Gleeble-3500型热模拟机对粉末冶金Fe-2Cu-0.5C钢在变形温度850~1000℃、应变速率0.1~10.0 s^(-1)下进行高温拉伸测试,定量分析变形温度、应变速率对粉末冶金钢高温拉伸变形行为的影响。通过应力应变曲线计算了该粉末冶金钢高温拉伸过程的断裂功,建立了断裂功与变形温度、应变速率的数学模型。基于Hensel-Spittel模型和BP神经网络模型建立了该粉末冶金钢的本构模型,用于表征其高温拉伸流变行为,并将两种模型的预测结果进行比较。结果表明:所建立的断裂功模型能够描述该粉末冶金钢在不同变形温度和应变速率下的抗断裂能力。Hensel-Spittel本构模型的预测值与实验值的平均绝对相对误差为3.16%,决定系数为0.9743,而BP神经网络模型的预测值与实验值的平均绝对相对误差为0.17%,决定系数为0.9999,说明BP神经网络模型的预测能力更强,能更好地表征粉末冶金Fe-2Cu-0.5C钢的高温拉伸流变行为。The elevated temperature tensile tests of the powder metallurgy(P/M)Fe−2Cu−0.5C steels at the deformation temperatures of 850~1000℃and strain rates of 0.1~10.0 s^(-1) were carried out by Gleeble-3500 thermal simulator.The effects of deformation temperature and strain rate on the elevated temperature tensile deformation behaviors of the P/M steels were quantitatively analyzed.The fracture work of the P/M steels during the elevated temperature tensile was calculated using the stress-strain curves.The mathematical model characterizing the relationship of fracture work,deformation temperature,and strain rate was established.The Hensel-Spittel model and BP neural network model were used to establish the constitutive equation of the P/M steels to characterize the flow behaviors during the elevated temperature tensile.The predicted results of the two models were compared.The results show that the fracture work model can describe the capacity of the P/M steels to resist fracture at different deformation temperatures and strain rates.The average absolute relative error between the predicted values of Hensel-Spittel constitutive model and the experimental values is 3.16%,and the coefficient of determination is 0.9743.While the average absolute relative error and the coefficient of determination between the predicted values of BP neural network model and the experimental values are 0.17%and 0.9999,respectively,indicating that the BP neural network model has the stronger predictive capacity and can characterize the elevated temperature tensile deformation behaviors of the P/M Fe−2Cu−0.5C steels better.

关 键 词：粉末冶金钢 高温拉伸 断裂功 本构模型 Hensel-Spittel模型 BP神经网络 

分 类 号：TF124.8[冶金工程—粉末冶金]