Al-Zn合金热成形本构模型  

Constitutive Model of Al-Zn Alloy Hot Forming

作　　者：程彬洋 刘祥 芦俊杰 庞秋 CHENG Bin-yang;LIU Xiang;LU Jun-jie;PANG Qiu(Hubei Key Laboratory of Advanced Technology of Automobile Parts,Wuhan University of Technology,Wuhan 430070,China;Hubei Provincial Engineering Center of Material Green Forming Technology and Equipment,Wuhan University of Technology,Wuhan 430070,China;Dongfeng(Wuhan)Industrial Co.,Ltd.,Wuhan 430040,China;School of Mechanical Automation,Wuhan University of Science and Technology,Wuhan 430081,China)

机构地区：[1]武汉理工大学现代汽车零部件技术湖北重点实验室,武汉43007 [2]武汉理工大学材料绿色成形技术与装备湖北省工程中心,武汉430070 [3]东风(武汉)实业有限公司,武汉430040 [4]武汉科技大学机械自动化学院,武汉430081

出　　处：《精密成形工程》2022年第4期11-19,共9页Journal of Netshape Forming Engineering

基　　金：国家重点研发计划(2019YFB1704500);国家自然科学基金(52075400);湖北省重点研发计划(2020BAB140)。

摘　　要：目的表征Al-Zn合金在预时效强化温热成形工艺下的流动行为。方法利用MMS200热模拟机对Al-Zn合金进行热拉伸试验,变形参数分别为变形温度180~220℃、应变速率0.01~1 s−1。通过对试验值进行修正,可得到不同变形条件下的真应力-应变曲线,并建立应变补偿的含Z参数本构模型和PSO-BP人工神经网络本构模型。结果Al-Zn合金热变形过程中呈现正的应变速率敏感性和热软化效应;应变补偿的含Z参数本构模型的R值和E_(AARE)值分别为0.961和8.761%;而PSO-BP人工神经网络本构模型的R值和E_(AARE)值分别为0.9935和2.51%。结论PSO-BP人工神经网络本构模型的预测值和试验值高度吻合,拥有更准确、更快速的数据采集和分析能力,对铝合金及其他合金材料的热变形行为预测有着重要意义。The work aims to characterize the flow behavior of Al-Zn alloy under the proposed pre-aged hardening warm forming(PHF)process.A MMS200 thermal simulator was used to conduct a hot tensile test on Al-Zn alloy.For deformation parameters,the deformation temperature was 180~220℃,and the strain rate was 0.01~1 s^(−1).By correcting the test values,the true stress-strain curves under different deformation conditions can be obtained,and a strain-compensated constitutive model with Z parameters and a PSO-BP artificial neural network constitutive model can be established.The Al-Zn alloy showed positive strain rate sensitivity and thermal softening effect during the hot deformation process;the R value and E_(AARE) value of the strain-compensated Z-parameter constitutive model were 0.961 and 8.761%,respectively;while the R value and E_(AARE) value of the PSO-BP artificial constitutive model were 0.9935 and 2.51%,respectively.The PSO-BP artificial neural network constitu-tive model shows a high degree of agreement between the predicted value and the experimental value,and has more accurate and faster data collection and analysis capabilities,which is of great significance to the prediction of the hot deformation behav-ior of aluminum alloys and other alloy materials.

关 键 词：预时效强化温热成形工艺 AL-ZN合金 本构模型 

分 类 号：TG146.21[一般工业技术—材料科学与工程]