研究了含氢TCA合金的热变形行为,基于径向基函数(RBF)人工神经网络建立了含氢TCA合金热变形流变应力的预测模型,该模型的样本数据取自热压缩试验数据,模型的输入量为变形温度、应变速率、应变量和氢含量,输出量为流变应力.研究表明:随着变形温度的升高和应变速率的降低,合金的流变应力降低;随着氢含量的增多,流变应力先降低后升高;RBF网络有较好的非线性逼近能力,训练相关性系数为0.999,训练速度较快,网络测试结果的最大相对误差为11.8%.
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