Modeling of Flow Stress of As-Rolled 7075 Aluminum Alloy during Hot Deformation by Artificial Neural Network and Application

被引:0
|
作者
Yang, Hongbin [1 ]
Li, Mengnie [1 ]
Bu, Hengyong [1 ]
Lu, Xin [1 ]
Yang, Hongmei [1 ]
Qian, Zhuo [1 ]
机构
[1] Kunming Univ Sci & Technol, Fac Mat Sci & Engn, Kunming 650093, Yunnan, Peoples R China
关键词
7075 aluminum alloy; ANN model; finite element simulation; flow stress; hot deformation; MG-CU ALLOY; CONSTITUTIVE MODEL; MICROSTRUCTURE EVOLUTION; ELEVATED-TEMPERATURES; BP-ANN; BEHAVIOR; PREDICT; COMPENSATION; COMPRESSION; WORKABILITY;
D O I
10.1007/s11665-022-07474-0
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
To analyze deformation behavior and construct a valid constitutive relationship using an ANN model. Hot compression studies on as-rolled 7075 aluminum alloy were carried out using a TA DIL805 D thermal simulator at a temperature ranging from 573 to 733 K and a strain rate ranging from 0.001 to 1.0 s(-1). Subsequently, the predicted flow stress data were applied to perform finite element simulations of hot compression experiments. The correlation coefficient and error analysis findings reveal that the ANN model has a high prediction accuracy for flow stress. The effective strain distribution in the hot-compressed specimens is not uniform, and it gradually decreases from the center of the deformed specimen to the side and end faces. The uniformity of the effective strain distribution and the tendency of crack generation are influenced by deformation parameters. Within the experimental circumstances of this study, the optimal deformation parameters are obtained, which are the temperature above 653 K and the strain rate between 0.01 and 0.1 s(-1).
引用
收藏
页码:5666 / 5677
页数:12
相关论文
共 50 条
  • [1] Modeling of Flow Stress of As-Rolled 7075 Aluminum Alloy during Hot Deformation by Artificial Neural Network and Application
    Hongbin Yang
    Mengnie Li
    Hengyong Bu
    Xin Lu
    Hongmei Yang
    Zhuo Qian
    [J]. Journal of Materials Engineering and Performance, 2023, 32 : 5666 - 5677
  • [2] Piecewise Modeling of Flow Stress of 7075-T6 Aluminum Alloy in Hot Deformation
    Mei, Ruibin
    Bao, Li
    Cai, Ban
    Li, Changsheng
    Liu, Xianghua
    [J]. MATERIALS TRANSACTIONS, 2016, 57 (07) : 1147 - 1155
  • [3] Modeling the Hot Deformation Behaviors of As-Extruded 7075 Aluminum Alloy by an Artificial Neural Network with Back-Propagation Algorithm
    Quan, Guo-zheng
    Zou, Zhen-yu
    Wang, Tong
    Liu, Bo
    Li, Jun-chao
    [J]. HIGH TEMPERATURE MATERIALS AND PROCESSES, 2017, 36 (01) : 1 - 13
  • [4] Correction and Modeling of Flow Stress during Hot Deformation of 7055 Aluminum Alloy
    Yu, Renhai
    Wang, Pengcheng
    Li, Guisheng
    Fang, Ming
    Xu, Gaoshan
    Zhang, Mingya
    [J]. JOURNAL OF MATERIALS ENGINEERING AND PERFORMANCE, 2022, 31 (08) : 6870 - 6879
  • [5] Correction and Modeling of Flow Stress during Hot Deformation of 7055 Aluminum Alloy
    Renhai Yu
    Pengcheng Wang
    Guisheng Li
    Ming Fang
    Gaoshan Xu
    Mingya Zhang
    [J]. Journal of Materials Engineering and Performance, 2022, 31 : 6870 - 6879
  • [6] Artificial neural network modeling to predict the hot deformation behavior of an A356 aluminum alloy
    Haghdadi, N.
    Zarei-Hanzaki, A.
    Khalesian, A. R.
    Abedi, H. R.
    [J]. MATERIALS & DESIGN, 2013, 49 : 386 - 391
  • [7] Artificial Neural Network Modeling to Evaluate the Dynamic Flow Stress of 7050 Aluminum Alloy
    Guo-zheng Quan
    Tong Wang
    Yong-le Li
    Zong-yang Zhan
    Yu-feng Xia
    [J]. Journal of Materials Engineering and Performance, 2016, 25 : 553 - 564
  • [8] Artificial Neural Network Modeling to Evaluate the Dynamic Flow Stress of 7050 Aluminum Alloy
    Quan, Guo-zheng
    Wang, Tong
    Li, Yong-le
    Zhan, Zong-yang
    Xia, Yu-feng
    [J]. JOURNAL OF MATERIALS ENGINEERING AND PERFORMANCE, 2016, 25 (02) : 553 - 564
  • [9] Dynamic behavior and modified artificial neural network model for predicting flow stress during hot deformation of Alloy 925
    Zhu, Yulong
    Cao, Yu
    Liu, Cunjian
    Luo, Rui
    Li, Na
    Shu, Gang
    Huang, Guangjie
    Liu, Qing
    [J]. MATERIALS TODAY COMMUNICATIONS, 2020, 25
  • [10] Artificial Neural Network Modeling of Flow Stress in Hot Rolling
    Aghasafari, Parya
    Abdi, Hamid
    Salimi, Mahmoud
    [J]. ISIJ INTERNATIONAL, 2014, 54 (04) : 872 - 879