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在等温恒应变速率压缩试验的基础上 ,将人工神经网络和耗散结构理论相结合 ,以确定 GH1 41和 GH90 7这两种变形高温合金的热力参数稳定区。研究结果表明 ,本方法与以数理方法建立的本构关系为动力学方程用耗散结构理论所确定的热力参数稳定区相比 ,更符合生产实际 ,从而可促进耗散结构理论在金属塑性加工中的应用
Based on the isothermal constant strain rate compression test, the artificial neural network and the dissipative structure theory are combined to determine the stable thermal parameters of two deformed superalloys GH1 41 and GH90 7. The results show that the constitutive relationship established by this method and the mathematical method is more in line with the actual production than that of the thermal parameter determined by the dissipative structure theory of the dynamic equation and thus can promote the application of dissipative structure theory in the metal plastic working In the application