研究论文

Ti551合金的热变形行为及热加工图构建

  • 尹建年 ,
  • 马英杰 ,
  • 杨锐 ,
  • 雷家峰 ,
  • 齐敏 ,
  • 周丽
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  • 1 烟台大学 机电汽车工程学院 烟台 264005
    2 中国科学院金属研究所 沈阳材料科学国家研究中心 沈阳 110016
尹建年,男,2001年生,硕士生
齐 敏,mqi17s@imr.ac.cn,主要从事结构钛合金研究; 周 丽,lizhou@ytu.edu.cn,主要从事复合材料成形加工研究

收稿日期: 2025-06-06

  修回日期: 2025-12-15

  网络出版日期: 2026-08-24

基金资助

国家重点研发计划项目(2024YFB3714201);山东省自然科学基金项目(ZR2023ME097)

Hot Deformation Behavior and Hot Processing Map Construction of the Ti551 Alloy

  • YIN Jiannian ,
  • MA Yingjie ,
  • YANG Rui ,
  • LEI Jiafeng ,
  • QI Min ,
  • ZHOU Li
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  • 1 School of Electromechanical and Vehicle Engineering, Yantai University, Yantai 264005, China
    2 Shenyang National Laboratory for Materials Science, Institute of Metal Research, Chinese Academy of Sciences, Shenyang 110016, China
QI Min, Tel: 18742418386, E-mail: mqi17s@imr.ac.cn; ZHOU Li, professor, Tel: 13889124507, E-mail: lizhou@ytu.edu.cn

Received date: 2025-06-06

  Revised date: 2025-12-15

  Online published: 2026-08-24

Supported by

National Key Research and Development Program of China(2024YFB3714201);Natural Science Foundation of Shandong Province(ZR2023ME097)

摘要

Ti551合金的热变形行为及其微观组织演变高度复杂,为拓展该合金的工程应用,需确定其热加工工艺窗口。本工作利用Gleeble-3500热模拟试验机在变形温度(T)为800~1100 ℃、应变速率(ε˙)为0.001~10 s-1条件下对Ti551合金进行热压缩实验,研究其热变形行为,构建热加工图并确定热加工窗口。在摩擦修正和温度修正的基础上,采用应变补偿Arrhenius (SCA)模型和反向传播人工神经网络(BPANN)模型建立了Ti551合金的本构关系,并通过统计分析对模型精度进行评估,发现BPANN模型在预测数据上表现出良好的拟合能力。基于动态材料模型建立Ti551合金的热加工图,确定其最佳加工区域为:ε˙ = 0.001~0.1 s-1T = 900~1050 ℃。失稳区主要集中在高温高应变速率区域(T ≥ 1000 ℃、ε˙ ≥ 1 s-1)。变形温度和应变速率对应力影响显著,随着温度下降或应变速率增加,流变应力明显增加,体现了典型的热激活变形特征。微观组织分析表明,Ti551合金在热压缩过程中的组织演化与应变、温度和应变速率密切相关,应变越大,晶粒变形越显著,随温度的降低或应变速率的增大,动态再结晶晶粒尺寸明显细化。此外,Ti551合金热变形过程中的主要动态再结晶机制为连续动态再结晶和不连续动态再结晶。

本文引用格式

尹建年 , 马英杰 , 杨锐 , 雷家峰 , 齐敏 , 周丽 . Ti551合金的热变形行为及热加工图构建[J]. 金属学报, 2026 , 62(8) : 1427 -1442 . DOI: 10.11900/0412.1961.2025.00157

Abstract

The Ti551 alloy exhibits exceptional thermal stability, retaining over 80% of its room-temperature strength within 300-400 oC, outperforming most α-type Ti alloys. Consequently, it has emerged as the primary structural material for applications in extreme operating environments, such as deep-sea oil drilling pipes. Despite this advantage, the Ti551 alloy exhibits considerably complex thermal deformation behavior and microstructural evolution. Establishing the alloy's precise hot processing window is critical to broaden its engineering applications. Therefore, this study investigated the thermal deformation behavior of the Ti551 alloy using a Gleeble-3500 thermal simulation tester. Specifically, isothermal compression tests were conducted over the temperatures (T) of 800-1100 oC and a strain rate (ε˙) of 0.001-10 s-1. Considering friction and temperature corrections, strain-compensated Arrhenius (SCA) and back-propagation artificial neural network (BPANN) models were selected to establish a constitutive model of the Ti551 alloy. The accuracies of both models were evaluated using the correlation coefficient, average absolute relative error, and relative error. The results demonstrate that the BPANN model outperformed the SCA model, yielding superior accuracy in predicting the flow stress. Thereafter, a hot processing map was constructed based on the dynamic materials model, and the corresponding microstructural evolution during thermal compression was systematically analyzed. Analysis of the hot processing map identified the optimal processing window with the following parameters: ε˙ = 0.001-0.1 s-1 and T = 900-1050 oC. Additionally, the instability zone was primarily concentrated in the high-T, high-ε˙ region (T ≥ 1000 °C, ε˙ ≥ 1 s-1). These findings demonstrate that the deformation T and ε˙ substantially influenced the flow stress. Specifically, the flow stress markedly increased with the decrease in T or increase in ε˙. During hot compression, the microstructural evolution of the Ti551 alloy exhibited a close relationship with T and ε˙, and the dynamic recrystallized grain size notably decreased as T decreased or ε˙ increased. Furthermore, the dominant dynamic recrystallization (DRX) mechanisms during hot deformation comprised continuous and discontinuous DRX processes.

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