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Hot compression experiments were performed on alloy 5182 with small additions of Sc and Zr. The 5182 alloy containing Sc and Zr is critical for expanding the 5182 alloy’s range of applications, and a thorough understanding of its thermal processing behavior is of great importance to avoid processing defects. Alloy microstructure, including grain structures and Al3(ScxZr1−x) dispersoids were analyzed by EBSD and TEM. Stable flow stresses were observed below a strain rate of 1 s−1 for the Sc-Zr containing alloy. The results of constitutive models, with and without strain−compensation, and artificial neural network (ANN) were used to compare to the experimental results. The Al3(ScxZr1−x) dispersoid data was introduced into the ANN model as a nonlinear influence factor. Addition of the Al3(ScxZr1−x) dispersoid information as input data improved the accuracy and practicality of the artificial neural network in predicting the deformation behavior of the alloy. The squared correlation coefficients of ANN prediction data reached 0.99.

Study of Thermal Compression Constitutive Relation for 5182-Sc-Zr Alloy Based on Arrhenius-Type and ANN Model