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    温飞娟, 温奇飞, 龙樟, 宋檬, 曹立清. TC17钛合金热变形行为及本构模型[J]. 机械工程材料, 2023, 47(8): 86-92. DOI: 10.11973/jxgccl202308014
    引用本文: 温飞娟, 温奇飞, 龙樟, 宋檬, 曹立清. TC17钛合金热变形行为及本构模型[J]. 机械工程材料, 2023, 47(8): 86-92. DOI: 10.11973/jxgccl202308014
    WEN Feijuan, WEN Qifei, LONG Zhang, SONG Meng, CAO Liqing. Hot Deformation Behavior and Constitutive Model of TC17 Titanium Alloy[J]. Materials and Mechanical Engineering, 2023, 47(8): 86-92. DOI: 10.11973/jxgccl202308014
    Citation: WEN Feijuan, WEN Qifei, LONG Zhang, SONG Meng, CAO Liqing. Hot Deformation Behavior and Constitutive Model of TC17 Titanium Alloy[J]. Materials and Mechanical Engineering, 2023, 47(8): 86-92. DOI: 10.11973/jxgccl202308014

    TC17钛合金热变形行为及本构模型

    Hot Deformation Behavior and Constitutive Model of TC17 Titanium Alloy

    • 摘要: 对TC17钛合金进行不同温度(600~950 ℃)和不同应变速率(0.001~10 s-1)的热压缩试验,研究了TC17钛合金的热变形行为,建立了TC17钛合金多元线性回归本构模型,并进行了试验验证。结果表明:TC17钛合金的流变应力随变形温度的升高而减小,随应变速率的增大而增大;在低温段(600~850 ℃)变形时,真应力-真应变曲线整体上呈应变软化特征,在高温段(850~950 ℃)变形时,则呈稳态流动特征,流变应力软化现象不明显;由TC17钛合金多元线性回归本构模型得到的流变应力的计算值与试验值较为接近,模型具有较高的预测精度。

       

      Abstract: The thermal compression test of TC17 titanium alloy at different temperatures (600~950 ℃) and different strain rates (0.001~10 s-1) was carried out, and the hot deformation behavior of TC17 titanium alloy was studied. The multiple linear regression constitutive model of TC17 titanium alloy was established and verified by experiments. The results show that the flow stress of TC17 titanium alloy decreased with the increase of deformation temperature, but increased with the increase of strain rate. At low temperatures (600~850 ℃), the true stress-true strain curve showed strain softening characteristics on the whole, while at high temperatures (850~950 ℃) showed steady flow characteristics, and the softening of flow stress at high temperatures was not obvious. The calculated value of the flow stress by the multiple linear regression constitutive model of TC17 titanium alloy was close to the experimental value, indicating the model had relatively high prediction accuracy.

       

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