Comparison of flow behaviors of near beta Ti-55511 alloy during hot compression based on SCA and BPANN models

作     者：Shuang-xi SHI Xiu-sheng LIU Xiao-yong ZHANG Ke-chao ZHOU 史双喜;刘秀生;张晓泳;周科朝

作者机构：State Key Laboratory of Powder MetallurgyCentral South UniversityChangsha 410083China Wuhan Research Institute of Materials ProtectionWuhan 430030China Shenzhen Research InstituteCentral South UniversityShenzhen 518057China 

出 版 物：《Transactions of Nonferrous Metals Society of China》 (中国有色金属学报（英文版）)

年 卷 期：2021年第31卷第6期

页      面：1665-1679页

核心收录：

学科分类：08[工学] 080502[工学-材料学] 0805[工学-材料科学与工程（可授工学、理学学位）] 

基　　金：financial supports from the National Natural Science Foundation of China(No.51871242) Guangdong Province Key-Area Research and Development Program,China(No.2019B010943001) 

主　　题：Ti-55511 alloy flow stress Arrhenius constitutive equation back-propagation artificial neural network finite element 

摘      要：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 *** stress−strain data extended by two models were implanted into finite element to simulate hot compression *** results indicate that the flow stress is sensitive to deformation temperature and strain rate,and increases with increasing strain rate and decreasing *** 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 *** cross-validation tests also confirm that the BPANN model has high prediction *** models are effective and feasible in simulation,but BPANN model is superior in accuracy.