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本文将人工神经网络（ＡＮＮ）用于建立热粘塑性材料的本构关系，意在探索出一种描述材料变形力学行为的新方法。文中给出了应用人工神经网络建立热粘塑性材料本构关系的ＢＰ模型和学习算法过程，并应用于４５号钢在高温和高速变形条件下的流动应力计算。计算结果与实测结果比较表明，二者吻合良好。因此，应用人工神经网络建立热粘塑性材料的本构关系具有重要的工程应用价值。
In this paper, artificial neural network (ANN) is used to establish the constitutive relation of thermoviscous plastic materials, and a new method to describe the mechanical behavior of materials is proposed. In this paper, the BP model and learning algorithm process of establishing the constitutive relation of thermal viscoplastic material by using artificial neural network are given. The calculation of the flow stress of 45 steel under high temperature and high speed deformation is given. Comparing the calculated result with the measured result shows that the two agree well. Therefore, the application of artificial neural network to establish the constitutive relation of thermoviscous plastic material has important engineering application value.