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Three different mathematical models to predict the hot deformation behavior of TA32 titanium alloy

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Abstract

To characterize the TA32 titanium alloy (Ti–5.5Al–3.5Sn–3.0Zr–0.7Mo–0.3Si–0.4Nb–0.4Ta, wt%) hot deformation behavior, the isothermal constant strain rate tensile tests in range of temperature 600–720 ℃ with strain rate 0.0001–0.1 s−1 were performed. Based on strain compensation of Arrhenius constitutive, physically based constitutive and BP neural network constitutive model were used to regress the high-temperature flow stress and the prediction accuracy were evaluated by correlation coefficient and average relative error. A cross-validation approach was used to evaluate the predictability of the three constitutive models. The result show that the tensile strength is more sensitive to strain rate than deformation temperature, according to the fitting results and sixteen cross-validation tests indicate that the BP model can provide the most accurate prediction for TA32 hot flow behavior. As revealed by micrographs, both high temperature and low strain rate are benefited for dynamic recrystallization and spheroidization with β phase.

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Cross-validation of three models.

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Data availability statement

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Acknowledgments

The study was supported by the project of Test processing of titanium alloy engine exhaust device.

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Authors and Affiliations

  1. Nanjing University of Aeronautics and Astronautics, Nanjing, 210001, Jiangsu, China

    Rui Feng, Minghe Chen & Lansheng Xie

  2. AECC Hunan Aviation Powerplant Research Institute, Zhuzhou, 412002, Hunan, China

    Youlin Bao, Yongshun Ding & Yan Ge

Authors
  1. Rui Feng
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  2. Youlin Bao
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  3. Yongshun Ding
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  4. Minghe Chen
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  5. Yan Ge
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Correspondence to Youlin Bao or Minghe Chen.

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Feng, R., Bao, Y., Ding, Y. et al. Three different mathematical models to predict the hot deformation behavior of TA32 titanium alloy. Journal of Materials Research 37, 1309–1322 (2022). https://doi.org/10.1557/s43578-022-00532-2

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