Transactions of Materials and Heat Treatment

Title：Prediction of drawing deformation for heavy forgings based on machine learning

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ClassificationCode：TG302

year,vol(issue):pagenumber：2020,45(10):209-216

Abstract：

The forming of heary forgings is usually studied by means of finite element simulation, and because of large size and long working procedure for heavy forgings, the finite element calculation takes a lot of time. Therefore, firstly the drawing process of heavy forgings was simulated by finite element software DEFORM, and the forming data were obtained to construct a data set which consisted of nineteen dimensional input characteristic variables and output characteristic variables of stress and strain. Then, the data set was learned by random forest and neural network methods in machine learning, and the corresponding model was trained. Finally, the stress and strain distributions of a new drawing process was predicted by the machine learning model. Compared with the results of finite element simulation, the predicted results were similar to those of finite element simulation. The results show that the machine learning quickly predicts the result of drawing and analyzes the forming quality to save a lot of calculation time.

Funds：

国家重点研发计划(2017YFB0701803)

张梓煜（1995-），男，硕士研究生 E-mail：zyzhang17@mails.tsinghua.edu.cn 通讯作者：雷丽萍（1968-），女，博士，副教授 E-mail：leilp@tsinghua.edu.cn

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