Unified modeling of the microstructure and densification of TC4 powder titanium alloy during hot deformation

被引:8
作者
Liu, Ronge [1 ,2 ]
Wang, Baoyu [1 ,3 ]
Hu, Shushan [1 ,2 ]
Zhang, Huibo [1 ]
Feng, Pengni [1 ]
机构
[1] Univ Sci & Technol Beijing, Sch Mech Engn, Beijing 100083, Peoples R China
[2] Ordos Inst Technol, Ordos 017000, Peoples R China
[3] 30 Xueyuan Rd, Beijing 100083, Peoples R China
来源
JOURNAL OF MATERIALS RESEARCH AND TECHNOLOGY-JMR&T | 2023年 / 24卷
基金
中国国家自然科学基金;
关键词
Powder titanium alloy; Microstructure evolution; Pore evolution; Constitutive modeling; Relative density; FLOW BEHAVIOR; PLASTICITY THEORY; STAINLESS-STEEL; YIELD FUNCTION; TI-6AL-4V; EVOLUTION; MECHANISMS; WORKING; KINETICS; CREEP;
D O I
10.1016/j.jmrt.2023.04.106
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
An accurate material constitutive model is very important to apply numerical simulation technology to predict, establish and optimize the thermoplastic forming process parameters of powder titanium alloy. To achieve this goal, the microstructure evolution and densification of TC4 powder titanium alloy were investigated during compression at temperatures from 860 & DEG;C to 960 & DEG;C, strain rates from 0.05 s-1 to 20 s-1and strains from 0.357 to 1.204. The results show that the microstructure undergoes dynamic recrystallization under different conditions. High temperature, large deformation degree and low strain rate are helpful to reduce porosity, pore size and pore colony. Plastic deformation and diffusion are two main mechanisms of densification. The microstructure evolution and densification model were established, combining the power constitutive law, a unified constitutive model was proposed to predict flow stress, microstructure and relative density of TC4 powder titanium alloy. The model constants were determined through a genetic algorithm. The predicted values of flow stress and relative density agreed well with the experimental values. The variations in relative density with temperature, strain rate and strain were analyzed based on the prediction results.& COPY; 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
引用
收藏
页码:4904 / 4918
页数:15
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