中国有色金属学报(英文版)
Transactions of Nonferrous Metals Society of China
| Vol. 31 No. 6 June 2021 |
（1. State Key Laboratory of Powder Metallurgy, Central South University, Changsha 410083, China;
2. Wuhan Research Institute of Materials Protection, Wuhan 430030, China;
3. Shenzhen Research Institute, Central South University, Shenzhen 518057, China）
Abstract:The flow behavior of Ti-55511 alloy was studied by hot compression tests at temperatures of 973-1123 K and strain rates of 0.01-10 s-1. Strain-compensated Arrhenius (SCA) and back-propagation artificial neural network (BPANN) methods were selected to model the constitutive relationship, and the models were further evaluated by statistical analysis and cross-validation. The stress-strain data extended by two models were implanted into finite element to simulate hot compression test. The results indicate that the flow stress is sensitive to deformation temperature and strain rate, and increases with increasing strain rate and decreasing temperature. Both the SCA model fitted by quintic polynomial and the BPANN model with 12 neurons can describe the flow behaviors, but the fitting accuracy of BPANN is higher than that of SCA. Sixteen cross-validation tests also confirm that the BPANN model has high prediction accuracy. Both models are effective and feasible in simulation, but BPANN model is superior in accuracy.
Key words: Ti-55511 alloy; flow stress; Arrhenius constitutive equation; back-propagation artificial neural network; finite element
