Research on constitutive model of aluminum alloy 7075 thermal deformation based on deep neural network

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成果类型：

期刊论文

作者：

Wang, Guan;Zhang, Pei;Kou, Linyuan;Wu, Yan;Wen, Tianxiang;...

通讯作者：

Guan Wang

作者机构：

[Wang, Guan; Wen, Tianxiang; Wu, Yan; Zhang, Pei; Kou, Linyuan; Shang, Xin] Ningxia Univ, Sch Mech Engn, Yinchuan 750000, Ningxia, Peoples R China.

[Wang, Guan; Wu, Yan; Zhang, Pei; Kou, Linyuan; Shang, Xin] Ningxia Univ, Ningxia Key Lab Comp Aided Engn Technol Intellige, Yinchuan 750000, Ningxia, Peoples R China.

[Wen, Tianxiang] Zooml Heavy Ind Sci & Technol Co Ltd, Changsha 410131, Peoples R China.

[Liu, Zhiwen] Univ South China, Sch Mech Engn, Hengyang 421001, Peoples R China.

通讯机构：

[Guan Wang] S

School of Mechanical Engineering, Ningxia University, Yinchuan, China<&wdkj&>Ningxia Key Laboratory of Computer Aided Engineering Technology for Intelligent Equipment, Ningxia University, Yinchuan, China

语种：

英文

关键词：

Constitutive model;Deep neural network;Arrhenius equation;Aluminum alloy 7075;The flow stress

期刊：

Journal of Mechanical Science and Technology

ISSN：

1738-494X

年：

2023

卷：

期：

页码：

707-717

DOI：

10.1007/s12206-023-0114-5

机构署名：

本校为其他机构

院系归属：

机械工程学院

摘要：

The hot deformation behavior of the Al-Zn-Mg-Cu alloy was studied by isothermal tensile tests in the temperature range of 200-350 degrees C and the strain rate range of 0.001-0.1 s(-1). A data-driven deep neural network (DNN) constitutive model and a phenomenological Arrhenius constitutive model were developed for the studied alloy model. The parameters of the DNN model were optimized to improve the prediction accuracy of flow stress. The results show that the accuracy of predictions of the DNN model is better than the Arrhenius model for the hot deformation behavior of 7075 aluminum alloy. Th...

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Research on constitutive model of aluminum alloy 7075 thermal deformation based on deep neural network

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