Phase Transformation Temperature Prediction in Steels via Machine Learning
Yupeng Zhang,
Lin Cheng,
Aonan Pan
et al.
Abstract:The phase transformation temperature plays an important role in the design, production and heat treatment process of steels. In the present work, an improved version of the gradient-boosting method LightGBM has been utilized to study the influencing factors of the four phase transformation temperatures, namely Ac1, Ac3, the martensite transformation start (MS) temperature and the bainitic transformation start (BS) temperature. The effects of the alloying element were discussed in detail by comparing their infl… Show more
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