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Influence of Segregation on Microstructure and Hot Workability of Grade 250 Maraging Steel

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Abstract

The optimal process parameters of grade 250 maraging steel for hot forging were investigated with a process map and microstructure analysis. To generate the process map, hot compression tests were performed at 800–1200 °C and strain rates of 0.01–5 s−1. The flow stress–strain curves were calibrated by Bayesian artificial neural network (ANN) modeling to compensate the heat generated by dynamic deformation. The Ni and Mo segregation during the solidification of the ingot caused alternating layers of Ni- and Mo-rich and -lean bands, which affected the recrystallization behavior during hot compression. According to the calculated process map, 1100–1200 °C × 0.01–0.7 s−1 and 1000–1200 °C × 0.01–0.2 s−1 are favorable process conditions that ensure wide process windows in terms of strain rate and temperature, respectively. The common features of the microstructure deformed under both conditions were relatively coarse martensite blocks and low values in the electron backscattered diffraction (EBSD) kernel average misorientation (KAM) results (i.e., low residual stresses), which were attributed to a low fraction of fine martensite block region.

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References

  1. W. Sha, Z. Guo, Maraging steels: Modeling of microstructure, properties and applications (Woodhead Publishing, Cambridge, 2009)

    Book  Google Scholar 

  2. A.P. Mouritz, Introduction to aerospace materials, 1st edn. (Woodhead Publishing, Cambridge, 2012)

    Book  Google Scholar 

  3. K.F. Best, Aircr. Eng. Aerosp. Tec. 58, 14 (1986)

    Article  Google Scholar 

  4. M.K. Banerjee, in Comprehensive materials finishing, ed. By M.S.J. Hashmi (Elsevier, 2017), p. 180

  5. W. Sha, Mater. Sci. Tech. 16, 1434 (2000)

    Article  CAS  Google Scholar 

  6. N. Takata, R. Nishida, A. Suzuki, M. Kobashi, M. Kato, Metals 8, 440 (2018)

    Article  Google Scholar 

  7. X. Xu, S. Ganguly, J. Ding, P. Dirisu, F. Martina, X. Liu, S.W. Williams, Mater. Sci. Eng., A 747, 111 (2019)

    Article  CAS  Google Scholar 

  8. T. Bhardwaj, M. Shukla, Mater. Sci. Eng., A 734, 102 (2018)

    Article  CAS  Google Scholar 

  9. S. Jelvani, R.S. Razavi, M. Barekat, M. Dehnavi, Met. Mater. Int. 26, 668 (2020)

    Article  CAS  Google Scholar 

  10. S. Lee, J. Kim, D.-S. Shim, S.-H. Park, Y.S. Choi, Met. Mater. Int. 26, 708 (2020)

    Article  CAS  Google Scholar 

  11. V.D. Sadovskii, G.N. Bogacheva, V.M. Umova, Met. Sci. Heat Treat. 11, 258 (1969)

    Article  Google Scholar 

  12. H. Hou, L. Qi, Y.H. Zhao, Mater. Sci. Eng., A 587, 209 (2013)

    Article  CAS  Google Scholar 

  13. H.L. Gegel, in Proceedings of Symposium of Experimental Verification of Process Models, ed. By C.C. Chen (American Society for Metals, 1981), pp. 21-23

  14. R. Raj, Metall. Trans. A 12A, 1089 (1981)

    Article  Google Scholar 

  15. Y.V.R.K. Prasad, H.L. Gegel, S.M. Doraivelu, J.C. Malas, J.T. Morgan, K.A. Lark, D.R. Barker, Metall. Trans. A 15A, 1883 (1984)

    Article  CAS  Google Scholar 

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

    Article  CAS  Google Scholar 

  17. Y.V.R.K. Prasad, T. Seshacharyulu, Int. Mater. Rev. 43, 243 (1998)

    Article  CAS  Google Scholar 

  18. Y.V.R.K. Prasad, J. Mater. Eng. Perform. 12, 638 (2003)

    Article  CAS  Google Scholar 

  19. C.H. Park, D. Cha, M. Kim, N.S. Reddy, J.-T. Yeom, Met. Mater. Int. 25, 768 (2019)

    Article  Google Scholar 

  20. P.L. Narayana, C.-L. Li, J.-K. Hong, S.-W. Choi, C.H. Park, S.-W. Kim, S.E. Kim, N.S. Reddy, J.-T. Yeom, Met. Mater. Int. 25, 1063 (2019)

    Article  CAS  Google Scholar 

  21. N.S. Reddy, Y.H. Lee, C.H. Park, C.S. Lee, Mater. Sci. Eng., A 492, 276 (2008)

    Article  Google Scholar 

  22. D.J.C. MacKay, Neural Comput. 4, 415 (1992)

    Article  Google Scholar 

  23. D.J.C. MacKay, Neural Comput. 4, 448 (1992)

    Article  Google Scholar 

  24. R.M. Neal, Tech. Rep. CRG-TR-91-1, Dep. Of Comput. Sci., Univ. of Toronto (1992)

  25. R.M. Neal, Bayesian learning for neural networks, Lecture Notes in Statistics No. 118, (Springer, New York, 1996)

  26. G.V. Voort, Microsc. Microanal. 16, 774 (2010)

    Article  Google Scholar 

  27. J. Drápala, J. Luňáček, L. Kuchař, L. Kuchař Jr., Mater. Sci. Eng., A 173, 73 (1993)

    Article  Google Scholar 

  28. W. Roberts, H. Bodén, B. Ahlblom, Met. Sci. 13, 195 (1979)

    Article  CAS  Google Scholar 

  29. Thermo-Calc Software TCFE9 Steels/Fe-Alloys database (accessed 7 January 2020)

  30. S. Morito, A.H. Pham, T. Ohba, T. Hayashi, T. Furuhara, G. Miyamoto, Microscopy 66, 380 (2017)

    Article  CAS  Google Scholar 

  31. R. Schnitzer, R. Radis, M. Nöhrer, M. Schober, R. Hochfellner, S. Zinner, E. Povoden-Karadeniz, E. Kozeschnik, H. Leitner, Mater. Chem. Phys. 122, 138 (2010)

    Article  CAS  Google Scholar 

  32. J.-M. Cloué, B. Viguier, E. Andrieu, Metall. Mater. Trans. 36A, 2633 (2005)

    Article  Google Scholar 

  33. S.W. Ooi, P. Hill, M. Rawson, H.K.D.H. Bhadeshia, Mater. Sci. Eng., A 564, 485 (2013)

    Article  CAS  Google Scholar 

  34. T. Maki, K. Akasaka, K. Okuno, I. Tamura, Trans. ISIJ 22, 253 (1982)

    Article  Google Scholar 

  35. T. Sakai, A. Belyakov, R. Kaibyshev, H. Miura, J.J. Jonas, Prog. Mater Sci. 60, 130 (2014)

    Article  CAS  Google Scholar 

  36. H. Lee, M.C. Jo, S.S. Sohn, S.-H. Kim, T. Song, S.-K. Kim, H.S. Kim, N.J. Kim, S. Lee, Mater. Charact. 147, 233 (2019)

    Article  CAS  Google Scholar 

  37. J. Liu, C. Chen, Q. Feng, X. Fang, H. Wang, F. Liu, J. Lu, D. Raabe, Mater. Sci. Eng., A 703, 236 (2017)

    Article  CAS  Google Scholar 

  38. K. Nakazawa, Y. Kawabe, S. Muneki, Trans. ISIJ 22, 893 (1982)

    Article  Google Scholar 

  39. R.D.K. Misra, T.V. Balasubramanian, P.R. Rao, J. Mater. Sci. Lett. 6, 125 (1987)

    Article  CAS  Google Scholar 

  40. V.X.L. Filho, I.F. Barros, H.F.G. de Abreu, Mater. Res. 20, 10 (2017)

    Article  CAS  Google Scholar 

  41. M.J. Luton, C.M. Sellars, Acta Metall. 17, 1033 (1969)

    Article  CAS  Google Scholar 

  42. G. Saul, J.A. Roberson, A.M. Adair, Metall. Mater. Trans. B 1, 383 (1970)

    Article  CAS  Google Scholar 

  43. T. Maki, K. Tsuzaki, I. Tamura, Trans. ISIJ 20, 207 (1980)

    Article  CAS  Google Scholar 

Download references

Acknowledgements

This research was supported by a grant from the Fundamental R&D Program of Korea Institute of Materials Science (PNK6750) funded by the Ministry of Science and ICT, Republic of Korea. The authors are grateful to HANSCO for the material supply.

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Correspondence to Hyungsoo Lee.

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Lee, H., Jeong, H.W., Seo, S.M. et al. Influence of Segregation on Microstructure and Hot Workability of Grade 250 Maraging Steel. Met. Mater. Int. 27, 691–704 (2021). https://doi.org/10.1007/s12540-020-00771-0

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