Transactions of Materials and Heat Treatment

Title：Accurate prediction on TA15 high temperature tensile deformation behavior based on deep neural network

Authors： Tang Xuefeng1 Huang Zhen1 Wen Hongning1 Wang Xin2 3 Liu Peng2 Liu Zhao3 Wang Xinyun1

Unit：

KeyWords：

ClassificationCode：TG301

year,vol(issue):pagenumber：2021,46(9):67-75

Abstract：

The tensile deformation and softening behavior of TA15 titanium alloy sheet were studied by isothermal tensile experiments at different temperatures (760, 810, 860, and 910 ℃) and different strain rates (0.01, 0.1 and 0.5 s-1）, and a high temperature tensile constitutive model of TA15 titanium alloy based on deep neural network (DNN) was established to accurately predict the high temperature tensile deformation behavior of TA15 titanium alloy. The results show that DNN model accurately predicts the flow stress of TA15 titanium alloy under different tensile deformation conditions, the average absolute error between the predicted results and the actual results is 1.3%, and the correlation coefficient reaches 0.999. Moreover, compared with a neural network with a single hidden layer, DNN model with multiple hidden layers has higher prediction accuracy and better generalization ability. In addition, the hot processing map of TA15 titanium alloy is constructed, and the theoretical analysis is carried out to verify the hot processing map, which shows the accuracy and effectiveness of the hot processing map.

Funds：

国家自然科学基金重大项目（52090043）；华中科技大学自主创新基金（2020kfyXJJS053）

唐学峰（1989-），男，博士，讲师 E-mail：xftang@hust.edu.cn 通信作者：王新云（1973-），男，博士，教授 E-mail：wangxy_hust@hust.edu.cn

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