在Gleeble-1500热模拟试验机上,以不同应变、应变速率和变形温度对LG铝合金进行了高温压缩流变试验,得出了真实应力曲线,并采用神经网络的方法建立了该合金高温变形抗力与应变、应变速率和变形温度对应关系的预测模型.结果表明:变形温度和应变速率的变化强烈地影响合金流变应力的大小,流变应力随变形温度的升高而降低,随应变速率的提高而增大;神经网络能够比较精确地预测材料的流变应力.
参考文献
[1] | Fzugwu E O;Wabg Z M .Titanium alloys and their machinability a review[J].Journal of Materials Processing Technology,1997,68:262-274. |
[2] | Lee Woei-shyan;Lam Han-fai .The deformation behavior and microstructure evolution of high-strength alloy at high rate[J].Journal of Materials Processing Technology,1996,57:233-240. |
[3] | Rao K P;Prased Y K .Neural network approach to flow stress evaluation in hot deformation[J].Journal of Materials Processing Technology,1995,53:552-566. |
[4] | Chun M S;Biglou J .Using networks to predict parameters in the hot working of aluminum alloys[J].Journal of Materials Processing Technology,1999,86:245-251. |
[5] | Korczak P Dyja .Using neural networks models for predicting mechanical properties after hot plate rolling processes[J].Journal of Materials Processing Technology,1998,80:481-486. |
[6] | 李萍,薛克敏,吕炎.热变形参数对Ti-15-3合金流动应力的影响[J].哈尔滨工业大学学报,2000(04):29. |
[7] | 俞汉清;陈金德.金属塑性成形原理[M].北京:机械工业出版社,1999 |
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