Abstract
In the present paper, a novel method was developed to predict the dynamic recrystallization (DRX) behavior during hot rolling based on machine learning in combination with physical models of niobium (Nb) micro-alloyed steels. It has been demonstrated that the comprehensive modeling could accurately predict the DRX behavior under different compositional and processing conditions, which not only exhibited higher precisions but also was in better agreement with physical metallurgical principles than traditional methods.
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Acknowledgments
Authors would like to acknowledge the financial supports from Ministry of Science and Technology, China (No. 2017YFB0305002), the project from Liaoning Province (No. XLYC1902034), and National Natural Science Foundation of China (51774083) and (51704066). Dr. Wu Siwei has provided valuable assistance in the revise of the manuscript, for which we are deeply appreciated.
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Manuscript submitted December 21, 2020; accepted April 25, 2021
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Li, X., Zhou, XG., Cao, GM. et al. Machine Learning Hot Deformation Behavior of Nb Micro-alloyed Steels and Its Extrapolation to Dynamic Recrystallization Kinetics. Metall Mater Trans A 52, 3171–3181 (2021). https://doi.org/10.1007/s11661-021-06315-4
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DOI: https://doi.org/10.1007/s11661-021-06315-4