铝锂合金高温变形流变应力的人工神经网络模型
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TG146.21

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航天工业总公司国防军工配套研制项目! (70 3 14 2 )


Artificial Neural Networks Models for Flow Stress during High Temperature Plastic Deformation of Al-Li Alloy
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    摘要:

    对所获试验数据采用数理统计方法建立合金材料的高温塑性变形稳态流变应力模型,其精度较低,同时建模过程复杂且工作量大。以Gleeble-1500热模拟试验机得到的实验数据为基础,根据BP人工神经网络算法原理,建立了1420Al-Li合金高温塑性变形稳态流变应力与应变速率和变形温度对应关系的预测模型。结果表明,神经网络用于稳态流变应力建模是可行的,模型计算值与实测值的偏差<5%,较好地反映了实际变形过程的特征。

    Abstract:

    Using gained experimental data to develop the models of stable flow stresses at high temperature plastic deformation by statistical methods for alloy materials, precision of the models is poor and at the same time the processes of modeling are complicated with great workload. On the basis of the data obtained on Gleeble-1500 Thermal Simulator,the predicting models for the relation between stable flow stress during high temperature plastic deformation and deformation strain, strain rate and temperature for 1420 Al-Li alloy have been developed with BP Artificial Neural Network method. The results show that the model on basis of BPNN is practical and it reflects the real feature of the deforming process. It states that the difference between the real value and the output of the model is in order of 5 percent.

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刘雪峰 汪凌云.铝锂合金高温变形流变应力的人工神经网络模型[J].重庆大学学报,2001,24(2):68-71.

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  • 最后修改日期:2000-06-21
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