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Numerical Analysis of the Effect of SEN Port Angle on Mold Level Fluctuation Based on Wavelet Transform

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Abstract

Reasonable mold level fluctuation is the key to maintaining stable mold production and ensuring the quality of the slab. In this study, a 0.6-scale water model was established, the wavelet transform was used to analyze the mold level fluctuation, and the particle image velocimetry (PIV) was used to measure the flow field of the mold. The results show that the wavelet transform provides more notable advantages for the investigation of the non-stationary signal of mold level fluctuation, which can be combined with the energy to make a more precise fluctuation characterization. The frequency of fluctuations consists of different frequency intervals, and the amplitude of each frequency interval changes with time. The fluctuation steadily reduces as the submerged entry nozzle (SEN) port angle increases. The contribution of waves with a frequency of 0.625 to 2.5 Hz to the fluctuation at the SEN and the narrow face of the mold (NF) presents a downward trend. At the 1/4 broad face of mold (1/4 WF), the contribution of 0.02 to 0.039 Hz decreases, and the contribution of 0.625 to 2.5 Hz increases. The different flow patterns in the mold are the main reasons for the frequency composition changes in the fluctuation. The fluctuation at the SEN and the NF is mainly related to the velocity in the Y direction of the upper circulating flow (UCF) and at the 1/4 WF is mainly related to the velocity in the X direction of the UCF.

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References

  1. H. Lei, J.J. Liu, G.F. Tang, H.W. Zhang, Z.J. Jiang, and P. Lv: Jom-Us., 2023, vol. 75, pp. 914–19.

    Article  ADS  Google Scholar 

  2. X.B. Zhang, Q.Q. Wang, W. Yang, S.D. Wang, and L.F. Zhang: Metall. Mater. Trans. B, 2018, vol. 49, pp. 2533–49.

    Article  CAS  Google Scholar 

  3. H.C. Zhou, L.F. Zhang, Q.Y. Zhou, W. Chen, R.B. Jiang, K. Yin, and W. Yang: Steel Res. Int., 2021, vol. 92, p. 2000547.

    Article  CAS  Google Scholar 

  4. Y. Guo, J. Yang, and J.Q. Liu: Steel Res. Int., 2023, vol. 14, pp. 23–66.

    Google Scholar 

  5. C.D. Huang, H.C. Zhou, L.F. Zhang, W. Yang, J. Zhang, Y. Ren, and W. Chen: Steel Res. Int., 2022, vol. 93, p. 2100350.

    Article  CAS  Google Scholar 

  6. H.H. Zhang and W.L. Wang: Metall. Mater. Trans. B, 2016, vol. 47, pp. 920–31.

    Article  CAS  Google Scholar 

  7. B.Z. Shen, H.F. Shen, and B.C. Liu: Ironmak. Steelmak., 2009, vol. 36, pp. 33–38.

    Article  CAS  Google Scholar 

  8. R. Chaudhary, G.-G. Lee, B.G. Thomas, and S.-H. Kim: Metall. Mater. Trans. B, 2008, vol. 39, pp. 870–84.

    Article  Google Scholar 

  9. Q.Q. Wang and L.F. Zhang: Jom-Us., 2016, vol. 68, pp. 2170–79.

    Article  CAS  Google Scholar 

  10. S.G. Zheng and M.Y. Zhu: Int. J. Miner. Metall. Mater., 2010, vol. 17, pp. 704–08.

    Article  CAS  Google Scholar 

  11. Z.K. Jiang, Z.J. Su, C.Q. Xu, J. Chen, and J.C. He: J. Iron. Steel Res. Int., 2020, vol. 27, pp. 160–68.

    Article  CAS  Google Scholar 

  12. H.Y. Duan, X.D. Wang, M. Yao, Y. Liu, and Y. Yu: Metall. Mater. Trans. B, 2020, vol. 51, pp. 1656–67.

    Article  CAS  Google Scholar 

  13. C.J. Hua, Y.P. Bao, M. Wang, and W. Xiao: J Mater Res Technol., 2022, vol. 19, pp. 2330–45.

    Article  CAS  Google Scholar 

  14. C. Yao, M. Wang, M.Y. Zhang, L.D. Xing, H.B. Zhang, and Y.P. Bao: J Mater Res Technol., 2022, vol. 19, pp. 1766–76.

    Article  CAS  Google Scholar 

  15. J.H. Wang, P.Y. Ni, C. Chen, M. Ersson, and Y. Li: Int. J. Miner. Metall. Mater., 2023, vol. 30, pp. 844–56.

    Article  CAS  Google Scholar 

  16. G.L. Zhang, G.G. Cheng, W.X. Dai, X. Zhang, and X.Y. Jiang: Chin. J. Eng., 2022, vol. 44, pp. 1324–30.

    CAS  Google Scholar 

  17. M.J. Gan, W.J. Pan, Q.Q. Wang, X.B. Zhang, and S.P. He: Metall. Mater. Trans. B, 2020, vol. 51, pp. 2862–70.

    Article  Google Scholar 

  18. W.J. Yang, L.J. Wang, S.Y. Liu, and K. Chou: ISIJ Int., 2022, vol. 62, pp. 1418–29.

    Article  CAS  Google Scholar 

  19. M.A. Tayfun: J Waterw Port Coast., 1990, vol. 116, pp. 686–707.

    Article  Google Scholar 

  20. M.T. Xuan and M. Chen: Metals., 2021, vol. 11, p. 1223.

    Article  Google Scholar 

  21. H.F. Shen, B.Z. Shen, and B.C. Liu: Steel Res. Int., 2007, vol. 78, pp. 531–35.

    Article  CAS  Google Scholar 

  22. W.H. Lee and K.W. Yi: Met. Mater. Int., 2021, vol. 27, pp. 4168–81.

    Article  CAS  Google Scholar 

  23. K.T. Zhang, J.H. Liu, H. Cui, and C. Xiao: Metall. Mater. Trans. B, 2018, vol. 49, pp. 1174–84.

    Article  CAS  Google Scholar 

  24. R. Miranda, M.A. Barron, J. Barreto, L. Hoyos, and J. Gonzalez: ISIJ Int., 2005, vol. 45, pp. 1626–35.

    Article  CAS  Google Scholar 

  25. Z.D. Wang, Q.L. Shan, Y. Gao, H.W. Pan, B.X. Lu, J.W. Wang, and H. Cui: Metall. Mater. Trans. B, 2023, vol. 54, pp. 2591–604.

    Article  CAS  Google Scholar 

  26. T. Teshima, J. Kubota, M. Suzuki, K. Ozawa, T. Masaoka, and S. Miyahara: Tetsu-to-Hagané., 1992, vol. 79, pp. 576–82.

    Article  Google Scholar 

  27. R. Kalter, M.J. Tummers, S. Kenjereš, B.W. Righolt, and C.R. Kleijn: Int. J. Heat. Fluid Fl, 2013, vol. 44, pp. 365–74.

    Article  Google Scholar 

  28. RPA do Pereira, GM de Almeida, JLF Salles, MASL de Cuadros, CT Valadão, RO de Freitas, T Bastos-Filho (2021) Metals, 11, 1458

    Article  CAS  Google Scholar 

  29. A. Bhattacharyya, L. Singh, and R.B. Pachori: Digit Signal Process., 2018, vol. 78, pp. 185–96.

    Article  Google Scholar 

  30. S.M. Zhou, B. Tang, and R. Chen: International Asia Symposium on Intelligent Interaction and Affective. Computing, 2009, vol. 2009, pp. 128–29.

    Google Scholar 

  31. A.A. Jaber and R. Bicker: Eur. Modell. Symp., 2014, vol. 2014, pp. 138–44.

    Google Scholar 

  32. M.V. Subbarao, and P. Samundiswary: 2016 10th International Conference on Intelligent Systems and Control (ISCO), 2016, pp. 1–6.

  33. B.G. Thomas, Q. Yuan, S. Sivaramakrishnan, T.B. Shi, S.P. Vanka, and M.B. Assar: ISIJ Int., 2001, vol. 41, pp. 1262–71.

    Article  CAS  Google Scholar 

  34. R. Chaudhary, B.T. Rietow, and B.G. Thomas: Mater. Sci. Tech. Lond., 2009, vol. 25, pp. 25–29.

    Google Scholar 

  35. N. Hess-Nielsen and M.V. Wickerhauser: Proc. IEEE, 1996, vol. 84, pp. 523–40.

    Article  Google Scholar 

  36. B. Jawerth and W. Sweldens: Siam Rev., 1994, vol. 36, pp. 377–12.

    Article  MathSciNet  Google Scholar 

  37. X. Zhang, Y. Wang, and R.P.S. Han: Seventh Int Conf. Fuzzy Syst. Knowl. Discov., 2010, vol. 5, pp. 2234–38.

    Google Scholar 

  38. M. Unser and A. Aldroubi: Proc. IEEE, 1996, vol. 84, pp. 626–38.

    Article  Google Scholar 

  39. S.-R. Tan, Y. Li, and K. Li: IEEE Int. Conf. Data Min. Works., 2014, vol. 2014, pp. 990–95.

    Google Scholar 

  40. C.R. Jung, and J. Schacanski: Proceedings XIV Brazilian Symposium on Computer Graphics and Image Processing. 2001, pp. 172–78.

  41. A.P. Bradley and W.J. Wilson: Clin. Neurophysiol., 2004, vol. 115, pp. 1114–28.

    Article  CAS  PubMed  Google Scholar 

  42. J. Tverdohleb, I. Limarev, V. Dubrovin, and V. Logominov: PIC S&T., 2017, pp. 12–20.

  43. M.F.M. Yusof, M.M. Quazi, S.A.A. Aleem, M. Ishak, and M.F. Ghazali: Weld World., 2023, vol. 67, pp. 1267–81.

    Article  Google Scholar 

  44. T. Renfei, L. Tao, and O. Min: Acta Geophys., 2023, vol. 71, pp. 1515–24.

    Article  ADS  Google Scholar 

  45. S.G. Mengistu, I.F. Creed, R.J. Kulperger, and C.G. Quick: Hydrol. Process., 2013, vol. 27, pp. 669–86.

    Article  ADS  Google Scholar 

  46. T. Cheng, B. Rivard, and A. Sánchez-Azofeifa: Remote Sens. Environ., 2011, vol. 115, pp. 659–70.

    Article  ADS  Google Scholar 

  47. I. Antoniou and K. Gustafson: Math. Comput. Simulat., 1999, vol. 49, pp. 81–104.

    Article  Google Scholar 

  48. A. Graps: IEEE Comput. Sci. Eng., 1995, vol. 2, pp. 50–61.

    Article  Google Scholar 

  49. M.V. Wickerhauser: Wellestey Massachusetts., 1994.

  50. S.G. Mallat: IEEE Trans. Pattern Anal., 1989, vol. 11, pp. 674–93.

    Article  Google Scholar 

  51. H.J. Landau: Proc. IEEE, 1967, vol. 55, pp. 1701–06.

    Article  Google Scholar 

  52. A. Bouzida, O. Touhami, R. Ibtiouen, A. Belouchrani, M. Fadel, and A. Rezzoug: IEEE Trans. Ind. Electron., 2011, vol. 58, pp. 4385–95.

    Article  Google Scholar 

  53. F.L. Niu and J. Huang: Int. Conf. Electr. Mach. Syst., 2005, vol. 2005(3), pp. 2274–77.

    Google Scholar 

  54. B. Bessam, A. Menacer, M. Boumehraz, and H. Cherif: Int J Syst Assur Eng., 2017, vol. 8, pp. 478–88.

    Article  Google Scholar 

  55. P.S. Addison: Philos Tans. R. Soc. A., 2018, vol. 376, p. 20170258.

    Article  ADS  Google Scholar 

  56. M.R. Mosavi, M. Pashaian, M.J. Rezaei, and K. Mohammadi: Iet Signal Process., 2015, vol. 9, pp. 457–64.

    Article  Google Scholar 

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Acknowledgments

The authors are grateful for the financial support of this work from the National Natural Science Foundation of China (Grant NO. U1860106).

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Authors and Affiliations

  1. Collaborative Innovation Center of Steel Technology, University of Science and Technology Beijing, Beijing, 100083, People’s Republic of China

    Zhendong Wang, Heng Cui, Rudong Wang, Jinrui Liu & Yu Gao

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Wang, Z., Cui, H., Wang, R. et al. Numerical Analysis of the Effect of SEN Port Angle on Mold Level Fluctuation Based on Wavelet Transform. Metall Mater Trans B 55, 863–876 (2024). https://doi.org/10.1007/s11663-024-02998-3

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