Skip to main content
SpringerLink
Log in

An Improved Constitutive Model Based on BP Artificial Neural Network and 3D Processing Maps of a Spray-Formed Al–Cu–Li Alloy

  • Original Article
  • Published:
Transactions of the Indian Institute of Metals Aims and scope Submit manuscript

Abstract

The flow stress behavior of an innovative spray-formed aluminum–copper–lithium (Al–Cu–Li) alloy was successfully investigated via isothermal compression tests under a deformation temperature range of 350–450 °C (25 °C interval) and a strain rate range of 0.01, 0.1, 1, 5, 10 s−1. The constitutive relationship was established based on backpropagation artificial neural network (BP-ANN) algorithm. And the 3D processing maps were constructed as well. The results show that the constitutive model is in great agreement with the experiment data where the correlation coefficient goes up to 0.99963 and the average residual error lies only 1.06%. Moreover, from the 3D processing maps, the area of the instable regions tends to enlarge by virtue of the increasing strain, and the optimum processing domain is advised to be 440–450 °C. The microstructure evolution is found consistent with the prediction of the processing map.

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

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8.
Fig. 9
Fig. 10

Similar content being viewed by others

References

  1. Wang F Y, Wang X J, Sun W, Yu F, and Cui J Z, Acta Metall Sin-Engl 33 (2020) 338.

    Article  CAS  Google Scholar 

  2. Jiang N, Gao X, and Zheng Z Q, T Nonferr Metal Soc 20 (2010) 740.

    Article  CAS  Google Scholar 

  3. Li J F, Huang J L, Liu D Y, Chen Y L, Zhang X H, and Ma P C. T Nonferr Metal Soc 29 (2019) 15.

    Article  CAS  Google Scholar 

  4. Niu S Y, Yue Y M, Yan D J, Ma Z W, and Ji S D, J Mater Eng Perform 28 (2019) 5763.

    Article  CAS  Google Scholar 

  5. Wang Y X, Zhao G Q, Xu X, Chen X X, and Zhang W D, J Mater Eng Perform 727 (2018) 78.

    Article  CAS  Google Scholar 

  6. Ma Y L, Huang C, Li J F, Liu D Y, Ye Z H, Wang J X, and Zheng Z Q, T Metal Heat Treat 37 (2016) 60.

    CAS  Google Scholar 

  7. Xu X, Zhao G Q, Yu S B, Wang Y X, Chen X X, and Zhang W D, J Mater Res Techno 9 (2020) 2662.

    Article  CAS  Google Scholar 

  8. Fan Y Q, Xie S J, Luo J, and Pu Q H, Special-cast and Non-ferrous Alloys 12 (2020) 25.

    Google Scholar 

  9. Lu L., Hou L G., Zhang J X., Wang H B., Cui H., Huang J F., Zhang Y A., and Zhang J S, Mater Charact 117 (2016) 1.

    Article  CAS  Google Scholar 

  10. Molak R M, Araki H, Watanabe M, Katanoda H, Ohno N, and Kuroda S, J Therm Spray Techn 23 (2014) 197.

    Article  CAS  Google Scholar 

  11. Wang T, Wan Z P, Sun Y, Li Z, Zhang Y, and Hu L X, Acta Metall Sin 54 (2018) 83.

    CAS  Google Scholar 

  12. Ramana A V, Balasundar I, Davidson M J, Balamuralikrishnan R, and Raghu T, T Indian I Metals 72 (2019) 1.

    Article  Google Scholar 

  13. Luo R, Zheng Q, Tang Z D, Cao Y Q, Xu G F, Li D S, and Cheng X N, High Temp Mat Pr-Isr 36 (2017) 467.

    Article  CAS  Google Scholar 

  14. Pu E X, Feng H, Liu M, Zheng W J, Dong H, and Song Z G, J Iron Steel Res Int 23 (2016) 178.

    Article  Google Scholar 

  15. Luo J., Li M Q., and Ma D W, Adv Mater Sci Eng 532 (2011) 548.

    Google Scholar 

  16. Wang X D, Pan Q L, Xiong S W, and Liu L L, J Alloy Compd 735 (2018) 1931.

    Article  CAS  Google Scholar 

  17. Zhou F, Wang K L, Lu S Q, Wan P, and Chen X H, J Mater Civil Eng 47 (2019) 141.

    Google Scholar 

  18. Wu X X, Special-cast and Non-ferrous Alloys 34 (2014) 1011.

    Google Scholar 

  19. Prasad Y V R K, Metall Mater Trans A 27 (1996) 235.

    Article  Google Scholar 

  20. Ye L Y, Zhai Y W, Zhou L Y, Wang H Z, and Jiang P, J Manuf Process 59 (2020) 535.

    Article  Google Scholar 

  21. Malas J C, and Seetharaman V, J Met 44 (1992) 8.

    CAS  Google Scholar 

  22. Wang M H, Chen M L, Wang R, and Wang G T, J Cent South Univ 47 (2016) 741.

    CAS  Google Scholar 

  23. Sun Y, Cao Z H, Wan Z P, and Hu L X, J Alloy Compd 742 (2018) 356.

    Article  CAS  Google Scholar 

  24. Hadadzadeh A, and Wells M A, J Mater Sci Eng 5 (2017) 369.

    CAS  Google Scholar 

  25. Chen L L, Luo R, Yang Y T, Peng C T, Gui X, Zhang J, Song K Y, Gao P, and Cheng X N, T Indian I Metals 72 (2019) 2997.

    Article  CAS  Google Scholar 

  26. Cao Y, and Di H S, Acta Metall Sin 49 (2013) 811.

    Article  CAS  Google Scholar 

  27. Yin Q, Tan F, Chen H X, and Yin G F, J Springer London 101 (2019) 1699.

    Google Scholar 

  28. Shi Z Y, Quan G Z, An C, Qiu H M, Wang W Y, and Zhang Z H, T Nonferr Metal Soc 29 (2019) 2090.

    Article  CAS  Google Scholar 

  29. Chang R H, Cai Z Y, Cheng L R, Che C J, and Chi J X, Mater Rep 31 (2017) 136.

    Google Scholar 

  30. Shuang Fa, Fang S, Zhang M C, and Dong Y P, J Phys Conf Ser 1637 (2020) 1.

  31. Li Z H, Xiong B Q, Zhang Y G, Zhu B H, Wang F, and Liu H G, Mater Charact 59 (2008) 278.

  32. Wang W H, Li B, Su H S, Sun Y, Li Z, and Qu F H, Heat Treat Met 44 (2019) 170.

    CAS  Google Scholar 

  33. Liu Q, Zhu R H, Li J F, Chen Y L, Zhang X H, Zhang L, and Zheng Z Q, T Nonferr Metal Soc 26 (2016) 607.

    Article  CAS  Google Scholar 

Download references

Acknowledgements

The authors are grateful to Qingtao Liu, Gengyun Zhang, Fei Yuan, Yanlin Zhang, Donghua Sheng, Xiaopeipei Zhang from Jiangsu University for helping in high-temperature compression tests. The authors also acknowledge the financial support of China Postdoctoral Science Foundation (Grant No. 2019M661738), Natural Science Foundation of the Jiangsu Higher Education Institutions of China (Grant No. 19KJB430001), National Science Foundation of China (Grant No. 51971206), and the Defense Industrial Technology Development Program (Grant No. JCKY2017205B032).

Author information

Author notes

  1. Rui Luo and Yun Cao have contributed equally to this work and should be considered co-first authors.

Authors and Affiliations

  1. School of Materials Science and Engineering, Jiangsu University, Zhenjiang, People’s Republic of China

    Rui Luo, Yun Cao, Shugang Cui, Ching-Tun Peng, Yuyan Yang, Tian Liu, Leli Chen, Yiming Zhou & Xiaonong Cheng

  2. College of Materials Science and Engineering, Chongqing University, Chongqing, People’s Republic of China

    Yu Cao

  3. AVIC Manufacturing Technology Institute, Beijing, People’s Republic of China

    Yu Qiu & Yanjin Xu

Authors
  1. Rui Luo
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yun Cao
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Shugang Cui
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yu Cao
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Ching-Tun Peng
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Yuyan Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Tian Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Leli Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Yiming Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Yu Qiu
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Yanjin Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Xiaonong Cheng
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Rui Luo.

Additional information

Publisher's Note

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

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Luo, R., Cao, Y., Cui, S. et al. An Improved Constitutive Model Based on BP Artificial Neural Network and 3D Processing Maps of a Spray-Formed Al–Cu–Li Alloy. Trans Indian Inst Met 74, 1809–1817 (2021). https://doi.org/10.1007/s12666-021-02259-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12666-021-02259-w

Keywords

Search

Navigation