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5A06铝合金板材热态本构模型及韧性断裂准则
引用本文:刘康宁,郎利辉,续秋玉.5A06铝合金板材热态本构模型及韧性断裂准则[J].西南交通大学学报,2018,53(1):214-218.
作者姓名:刘康宁  郎利辉  续秋玉
作者单位:北京航天发射技术研究所;北京航空航天大学机械工程及自动化学院;航天材料及工艺研究所;
基金项目:国家自然科学基金资助项目51511130041
摘    要:为了获取材料在不同条件下成形性能指标,对5A06铝合金板材进行了热态单向拉伸试验,结合热态单向拉伸试验和韧性断裂试验结果,提出了一种修正Misiolek模型;利用修正模型的外插性能预测颈缩后板材流变应力,应用径向基函数神经网络算法建立了Cockroft-Latham韧性断裂阈值预测模型,并对该模型进行了预测精度评估.结果表明,流变应力对温度及应变速率敏感,对比径向基函数网络模型预测误差小于10.6%. 

关 键 词:铝合金    本构模型    热态    韧性断裂准则    径向基函数网络
收稿时间:2016-01-18

Modified Constitutive Model and Ductile Fracture Criterion for 5A06 Al-Alloy Sheets at Elevated Temperatures
LIU Kangning,LANG Lihui,XU Qiuyu.Modified Constitutive Model and Ductile Fracture Criterion for 5A06 Al-Alloy Sheets at Elevated Temperatures[J].Journal of Southwest Jiaotong University,2018,53(1):214-218.
Authors:LIU Kangning  LANG Lihui  XU Qiuyu
Abstract:In order to obtain the formation characteristics of 5A06 aluminium alloy sheets, uniaxial tensile tests were conducted under different conditions. From hot tensile and fracture tests, a modified Misiolek equation was defined that extrapolated the flow stress from the diffuse necking of the metal sheet. By using a radial basis unction (RBF) artificial neural network, a Crockroft-Latham ductile fracture threshold prediction model was also developed. An evaluation of the network compared model results with experimental data. Results show that the material flow stress is very sensitive to temperature and strain rate, and the RBF artificial neural network can predict the ductile fracture threshold with a maximum error of less than 10.6%. 
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