Transactions of Nonferrous Metals Society of China The Chinese Journal of Nonferrous Metals

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中国有色金属学报

ZHONGGUO YOUSEJINSHU XUEBAO

第21卷    第11期    总第152期    2011年11月

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文章编号:1004-0609(2011)11-2880-08
挤压态7075铝合金高温流变行为及神经网络本构模型
王 煜, 孙志超, 李志颖, 杨 合

(西北工业大学 凝固技术国家重点实验室,材料学院,西安 710072)

摘 要: 采用Gleeble1500D热模拟实验机研究挤压态7075铝合金在变形温度为250~450 ℃、应变速率为0.01~10 s−1下单道次压缩过程的高温流变行为。结果表明:材料在350 ℃及以下变形时,流变应力曲线呈动态回复型;在温度为350 ℃以上、应变速率为0.1 s−1时,流变曲线局部陡降明显;当应变速率为10 s−1时,流变曲线发生波动,呈动态再结晶型;挤压态7075铝合金的流变应力曲线峰值应力及稳态应力均高于铸态合金的,且在变形温度较高时,挤压态材料更易于发生动态软化。基于BP神经网络建立挤压态7075铝合金的本构关系模型,预测值与实验值对比表明:所建立的本构模型整体误差在5.35%以内,拟合度为2.48%,该模型可以用于描述7075铝合金的高温变形流变行为,为该合金热变形过程分析和有限元模拟提供基础。

 

关键字: 7075铝合金;流变行为;本构关系;BP神经网络

High temperature flow stress behavior of
as-extruded 7075 aluminum alloy and neural network constitutive model
WANG Yu, SUN Zhi-chao, LI Zhi-ying, YANG He

State Key Laboratory of Solidification Processing, School of Materials Science and Engineering,
Northwestern Polytechnical University, Xi’an 710072, China

Abstract:The flow stress behavior of the as-extruded 7075 aluminum alloy was studied through single-pass compression experiment by using Gleeble 1500D simulator within a temperature range of 250−450 ℃ and a strain rate range of 0.01−10 s−1. The results indicate that the flow stress curves show the characteristics of dynamic recovery when the temperature is no higher than 350 ℃. Above 350 ℃, the dynamic recrystallization occurs in local zone. Compared with the as-cast 7075 alloy, the peak stress and steady stress of the as-extruded 7075 alloy are larger, and the dynamic softening is prone to occur at high temperature. The constitutive relationship model of the as-extruded 7075 alloy was constructed based on BP neural network. The global error is less than 5.35%, while the fitting degree is 2.48%. It is evident that the model can be used to describe the flow stress behavior of the 7075 alloy at high temperature, and can be used for analysis and finite element simulation of 7075 alloy in hot working process.

 

Key words: 7075 aluminum alloy; flow behavior; constitutive relationship; BP neural network

ISSN 1004-0609
CN 43-1238/TG
CODEN: ZYJXFK

ISSN 1003-6326
CN 43-1239/TG
CODEN: TNMCEW

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