Skip to main content
SpringerLink
Log in

Research on hot deformation behavior and numerical simulation of microstructure evolution for Ti–6Al–4V alloy

  • Article
  • Published:
Journal of Materials Research Aims and scope Submit manuscript

Abstract

Accurate flow stress data and microstructure evolution mechanisms are essential for designing and optimizing thermal processing technology for a wide range of metal materials. In this paper, the compression experiment of Ti–6Al–4V alloy were carried out by Gleeble-3500 thermal simulation machine under high-temperature conditions. The constitutive model of alloy was established by the PSO-BP neural network based on the corrected flow stress. And the Najafizadeh–Jonas and Cingara–McQueen model were used to establish critical strain model. Then, JMAK equation and AGS model were constructed by the linear regression method. A numerical simulation model was also developed to simulate the hot behavior of titanium alloy. The results indicate that the prediction error of the FE model for predicting DRX volume fraction and AGS is less than 5%. The research results have a good prediction ability for predicting plastic deformation and microstructure in industrial production.

Graphical abstract

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9

Similar content being viewed by others

Data availability

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

References

  1. J. Alexander, E. Stefan, P. Aude et al., In-situ high-temperature EBSD characterization during a solution heat treatment of hot-rolled Ti–6Al–4V. Mater Charact 192, 112207 (2022). https://doi.org/10.1016/j.matchar.2022.112207

    Article  CAS  Google Scholar 

  2. D. Mahadule, D. Kumar, T.R. Dandekar et al., Modelling of flow stresses during hot deformation of Ti–6Al–4Mo–1V–0.1Si alloy. J. Mater. Res. 38, 3750–3763 (2023). https://doi.org/10.1557/s43578-023-01097-4

    Article  CAS  Google Scholar 

  3. Q.Y. Zhao, Q.Y. Sun, S.W. Xin et al., High-strength titanium alloys for aerospace engineering applications: a review on melting-forging process. Mater. Sci. Eng. A 845, 143260 (2022). https://doi.org/10.1016/j.msea.2022.143260

    Article  CAS  Google Scholar 

  4. C.X. Zhu, J. Xu, H.P. Yu et al., Hybrid forming process combining electromagnetic and quasi-static forming of ultra-thin titanium sheets: formability and mechanism. Int J Mach Tool Manu 180, 103929 (2022). https://doi.org/10.1016/j.ijmachtools.2022.103929

    Article  Google Scholar 

  5. F.Q. Li, J.H. Mo, J.L. Li, L. Huang, H.Y. Zhou, Formability of Ti–6Al–4V titanium alloy sheet in magnetic pulse bulging. Mater. Design. 52, 337–344 (2013). https://doi.org/10.1016/j.matdes.2013.05.064

    Article  CAS  Google Scholar 

  6. R. Feng, Y. Bao, Y. Ding et al., Three different mathematical models to predict the hot deformation behavior of TA32 titanium alloy. J. Mater. Res. 37(7), 1309–1322 (2022). https://doi.org/10.1557/s43578-022-00532-2

    Article  CAS  Google Scholar 

  7. C. Nagarjuna, S.K. Dewangan, A. Sharma et al., Application of artificial neural network to predict the crystallite size and lattice strain of CoCrFeMnNi high entropy alloy prepared by powder metallurgy. Met. Mater. Int. 29, 1968–1975 (2023). https://doi.org/10.1007/s12540-022-01355-w

    Article  CAS  Google Scholar 

  8. X. Li, J. Wang, J. Ma et al., Thermal deformation behavior of Mg–3Sn–1Mn alloy based on constitutive relation model and artificial neural network. J. Mater. Res. Technol. 24, 1802–1815 (2023). https://doi.org/10.1016/j.jmrt.2023.03.096

    Article  CAS  Google Scholar 

  9. J. Yan, Q.L. Pan, A.D. Li et al., Flow behavior of Al–6.2Zn–0.70Mg–0.30Mn–0.17Zr alloy during hot compressive deformation based on Arrhenius and ANN models. T. Nonferr. Metal. Soc. 27, 638–647 (2017). https://doi.org/10.1016/S1003-6326(17)60071-2

    Article  CAS  Google Scholar 

  10. D. Zhou, Z. Li, D. Li et al., A polycrystal plasticity based discontinuous dynamic recrystallization simulation method and its application to copper. Int. J. Plast. 91, 48–76 (2017). https://doi.org/10.1016/j.ijplas.2017.01.001

    Article  CAS  Google Scholar 

  11. M. Tajally, Z. Huda, Recrystallization kinetics for aluminum alloy 7075. Met. Sci. Heat Treat. 53, 213–217 (2011). https://doi.org/10.1007/s11041-011-9371-5

    Article  CAS  Google Scholar 

  12. H. Zhang, X. Mao, S. Xu et al., A physically based elasto-viscoplastic constitutive model for modeling the hot deformation and microstructure evolution of a near α Ti alloy. Mater. Sci. Eng. A 872, 144994 (2023). https://doi.org/10.1016/j.msea.2023.144994

    Article  CAS  Google Scholar 

  13. R. Feng, M. Chen, L. Xie et al., Research on hot deformation behavior and constitutive relation of diffusion bonded TC4 titanium alloy. J. Mater. Sci. 57, 21777–21797 (2022). https://doi.org/10.1007/s10853-022-07977-0

    Article  CAS  Google Scholar 

  14. B. Roebuck, J.D. Lord, M. Brooks et al., Measurement of flow stress in hot axisymmetric compression tests. Mater. High Temp. 23(2), 59–83 (2006)

    Article  Google Scholar 

  15. R. Ebrahimi, A. Najafizadeh, A new method for evaluation of fraction in bulk metal forming. J. Mater. Process Tech. 152(2), 136–143 (2004). https://doi.org/10.1016/j.jmatprotec.2004.03.029

    Article  CAS  Google Scholar 

  16. A. Laasraoui, J.J. Jonas, Prediction of steel flow stresses at high temperatures and strain rates. Metall. Trans. A 22(7), 1545–1558 (1991)

    Article  Google Scholar 

  17. E. Alabort, D. Putman, R.C. Reed, Superplasticity in Ti–6Al–4V: characterisation, modelling and applications. Acta Mater. 95, 428–442 (2015). https://doi.org/10.1016/j.actamat.2015.04.056

    Article  CAS  Google Scholar 

  18. Y. Tabassam, R. Salaheddin, H. Christopher et al., Unravelling thermal-mechanical effects on microstructure evolution under superplastic forming conditions in a near alpha titanium alloy. J. Mater. Res. Technol. 18, 4285–4302 (2022). https://doi.org/10.1016/j.jmrt.2022.04.063

    Article  CAS  Google Scholar 

  19. Z. Yuan, M. Niu, H. Ma et al., Predicting mechanical behaviors of rubber materials with artificial neural networks. Int. J. Mech. Sci. 249, 108265 (2023). https://doi.org/10.1016/j.ijmecsci.2023.108265

    Article  Google Scholar 

  20. D. Hu, L. Wang, N. Wang et al., Hot tensile deformation behaviors of TA32 titanium alloy based on back-propagation neural networks and three-dimensional thermal processing maps. J. Mater. Res. Tech. 18, 4786–4795 (2022). https://doi.org/10.1016/j.jmrt.2022.04.144

    Article  CAS  Google Scholar 

  21. Y.V.R.K. Prasad, S. Sasidhara, Hot working guide: a compendium of processing maps [M] (ASM International, OH, 1997), pp.1–24

    Google Scholar 

  22. Y.V.R.K. Prasad, Processing maps: a status report. J. Mater. Eng. Perform. 12(6), 638–645 (2003). https://doi.org/10.1361/105994903322692420

    Article  CAS  Google Scholar 

  23. S.V.S.N. Murty, B.N. Rao, On the flow localization concepts in the processing maps of titanium alloy Ti–24Al–20Nb. J. Mater. Process Tech. 104(1–2), 103–109 (2000). https://doi.org/10.1016/S0924-0136(00)00517-3

    Article  Google Scholar 

  24. A. Najafizadeh, J.J. Jonas, Predicting the critical stress for initiation of dynamic recrystallization. Isij Int. 46(11), 1679–1684 (2006). https://doi.org/10.2355/isijinternational.46.1679

    Article  CAS  Google Scholar 

  25. A. Cingara, H.J. McQueen, New formula for calculating flow curves from high temperature constitutive data for 300 austenitic steels. J. Mater. Process Tech. 36(1), 31–42 (1992). https://doi.org/10.1016/0924-0136(92)90236-L

    Article  Google Scholar 

  26. C. Liu, S. Barella, Y. Peng et al., Modeling and characterization of dynamic recrystallization under variable deformation states. Int. J. Mech. Sci. 238, 107838 (2023). https://doi.org/10.1016/j.ijmecsci.2022.107838

    Article  Google Scholar 

  27. B. Venkatesh, F. Khan, B.N. Sahoo et al., A high temperature manufacturability study of ultrafine grained magnesium rare-earth alloy using processing map and constitutive analysis. J. Alloy. Compd. 954, 169991 (2023). https://doi.org/10.1016/j.jallcom.2023.169991

    Article  CAS  Google Scholar 

  28. H.C. Kaushik, M.H. Korayem, A. Hadadzadeh, Determination of α to β phase transformation kinetics in laser-powder bed fused Ti–6Al–2Sn–4Zr–2Mo-0.08Si and Ti–6Al–4V alloys. Mater. Sci. Eng. A 860, 144294 (2022). https://doi.org/10.1016/j.msea.2022.144294

    Article  CAS  Google Scholar 

  29. T. Paul, A. Loganathan, A. Agarwal et al., Kinetics of isochronal crystallization in a Fe-based a morphous alloy. J. Alloys Compd. 753, 679–687 (2018). https://doi.org/10.1016/j.jallcom.2018.04.133

    Article  CAS  Google Scholar 

  30. Y. Deng, Y. An, Y. Xiao et al., Deformation mechanism diagram and deformation instability of a Ti–5Al–5Mo–5V–1Cr–1Fe titanium alloy during the hot compression. J. Alloys Comp. 966, 171446 (2023). https://doi.org/10.1016/j.jallcom.2023.171446

    Article  CAS  Google Scholar 

  31. R. Fabiana, R. Fabrícia, A locally convergent inexact projected Levenberg–Marquardt-type algorithm for large-scale constrained nonsmooth equations. J. Comput. Appl. Math. 427, 115121 (2023). https://doi.org/10.1016/j.cam.2023.115121

    Article  Google Scholar 

  32. J. Zhao, K. Wang, K. Huang et al., Recrystallization behavior during hot tensile deformation of TA15 titanium alloy sheet with substantial prior deformed substructures. Mater Charact 151, 429–435 (2019). https://doi.org/10.1016/j.matchar.2019.03.029

    Article  CAS  Google Scholar 

Download references

Acknowledgments

This study was supported by the financial support from the National Natural Science Foundation of China (52375345) and Aviation Engine Independent Innovation Special Foundation of China (ZZCX-2018-031).

Author information

Authors and Affiliations

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

    Rui Feng, Minghe Chen & Lansheng Xie

Authors
  1. Rui Feng
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Minghe Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Lansheng Xie
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

RF contributed to Writing of the original draft, Methodology, and Investigation. MC contributed to Writing, reviewing, & editing of the manuscript, Supervision, and Project administration. LX contributed to Conceptualization.

Corresponding author

Correspondence to Minghe Chen.

Ethics declarations

Conflict of interest

The authors declare no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 86 KB)

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Feng, R., Chen, M. & Xie, L. Research on hot deformation behavior and numerical simulation of microstructure evolution for Ti–6Al–4V alloy. Journal of Materials Research 39, 1108–1127 (2024). https://doi.org/10.1557/s43578-024-01295-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1557/s43578-024-01295-8

Keywords

Search

Navigation