Constructing processing map of M50NiL steel by artificial neural network model
Materials Today Communications(2023)
摘要
The processing map for M50NiL steel was established by hot compression tests at temperatures of 950–1150 °C and strain rates of 0.002–1.0 s−1. Based on the experimental results of hot compression tests, the predictability in both reproducing experimental flow stresses and predicting flow stresses using the Arrhenius, physical-based, and artificial neural network (ANN) models was compared. The results showed that the average absolute relative errors of Arrhenius, physical-based, and ANN models in both reproducing and predicting flow stresses were 6.04 % and 8.01 %, 6.61 % and 7.78 %, and 1.91 % and 4.74 %, respectively. The ANN model had a considerably higher accuracy in reproducing and predicting flow stresses than the other two models. In addition, a processing map of M50NiL steel was established using the predicted flow stresses by the ANN model. This processing map indicated that the optimized processing parameters were 975–1050 °C/0.01–0.002 s−1. Instability occurred during deformation at 950–975 °C at 1.0 s−1 and 1075–1150 °C at 0.01 s−1. The instability prediction was verified by the microstructure evolution.
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关键词
M50NiL steel,Processing map,Predictability,Arrhenius model,Physical-based model,Artificial neural network (ANN)
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