DOI QR코드

DOI QR Code

A Review of Kinetic Model for Production of Highgrade Steel : Part. 1. Simulation Model Based on Coupled Reaction

고급강 제조 반응 모델의 검토 : Part. 1. Coupled Reaction 기반 시뮬레이션 모델

  • Kim, Jeong-In (Dep. of Advanced Materials Engineering, Chosun University) ;
  • Kim, Sun-Joong (Dep. of Materials Engineering & Science, Chosun University)
  • 김정인 (조선대학교 첨단소재공학과) ;
  • 김선중 (조선대학교 재료공학과)
  • Received : 2020.08.19
  • Accepted : 2020.12.23
  • Published : 2021.02.28

Abstract

In the secondary refining process for the production of high-grade steel, the proper composition is maintained by alloying elements, and non-metallic inclusions are controlled for high cleanliness. Complex reactions occur simultaneously between the molten steel, slag, inclusions, refractories, and alloying elements during the secondary refining process. Previous works have reported simulation models based on kinetics to predict the compositional changes in molten steel, slag, and inclusions in actual processes. Analytical reviews are required for the models to predict the process accurately. In this study, we reviewed and analyzed simulation models based on the coupled reaction model for the secondary refining process.

고급강은 소비자가 원하는 적절한 조성을 갖추고 있고 비금속 개재물의 제어를 통해 높은 청정도를 지닌 강을 의미하며, 철강 제품의 품질은 2차 정련 공정에서 제어하는 것이 지배적이다. 2차 정련에서는 시간이 흐름에 따라 용강, 슬래그, 비금속 개재물, 내화물 및 합금원소 간의 복잡한 반응이 동시에 일어나기 때문에 공정에 대한 제어가 쉽지 않다. 따라서 이전 연구자들은 2차 정련의 공정 예측을 위해 Kinetic 기반의 시뮬레이션 모델을 발표하였고, 정밀한 공정 예측을 위해 현재까지 발표된 시뮬레이션 모델들의 검토 및 분석이 필요하다. 본 연구에서는 Coupled Reaction 모델 기반의 2차 정련 모델들을 분석 및 검토하였고, 시뮬레이션 결과를 검토하였다.

Keywords

References

  1. K. W. Lange, 1988 : Thermodynamic and kinetic aspects of secondary steelmaking processes, Int. Mater. Reviews, 33(1), pp.53-89. https://doi.org/10.1179/imr.1988.33.1.53
  2. J. H. Park and Y. Kang, 2017 : Inclusions in Stainless Steels - A Review, Steel Res. Int., 88, 1700130. https://doi.org/10.1002/srin.201700130
  3. J. H. Park and H. Todoroki, 2010 : Control of MgO·Al2O3 Spinel Inclusions in Stainless Steels, ISIJ Int., 50(10), pp.1333-1346. https://doi.org/10.2355/isijinternational.50.1333
  4. A. Harada, G. Miyano, N. Maruoka, et al., 2014 : Dissolution Behavior of Mg from MgO into Molten Steel Deoxidized by Al, ISIJ Int., 54(10), pp.2230-2238. https://doi.org/10.2355/isijinternational.54.2230
  5. C. Liu, F. Huang and X. Wang, 2016 : The Effect of Refining Slag and Refractory on Inclusion Transformation in Extra Low Oxygen Steels, Metall. Mater. Trans. B, 47(2), pp.999-1009. https://doi.org/10.1007/s11663-016-0592-2
  6. T. Nishi and K. Shinme, 1998 : Formation of Spinel Inclusions in Molten Stainless Steel under Al Deoxidation with Slags, Tetsu-to-Hagane, 84(12), pp.837-843. https://doi.org/10.2355/tetsutohagane1955.84.12_837
  7. J. H. Park and Y. -B. Kang, 2006 : Effect of Ferrosilicon Addition on the Composition of Inclusions in 16Cr-14Ni-Si Stainless Steel Melts, Metall. Trans. B, 37(5), pp.791-797.
  8. J. R. Kim, Y. S. Lee, D. J. Min, et al., 2004 : Influence of MgO and Al2O3 Contents on Viscosity of Blast Furnace Type Slags Containing FeO, ISIJ Int., 44(8), pp.1291-1297. https://doi.org/10.2355/isijinternational.44.1291
  9. Z. Zhang, G. Wen, P. Tang, et al., 2008 : The Influence of Al2O3/SiO2 Ratio on the Viscosity of Mold Fluxes, ISIJ Int., 48(6), pp.739-746. https://doi.org/10.2355/isijinternational.48.739
  10. G. Wranglen, 1974 : Pitting and Sulphide Inclusions in Steel, Corrosion Science, 14(5), pp.331-349. https://doi.org/10.1016/S0010-938X(74)80047-8
  11. E. G. Webb, T. Suter and R. C. Alkire, 2001 : Microelectrochemical Measurements of the Dissolution of Single MnS Inclusions, and the Prediction of the Critical Conditions for Pit Initiation on Stainless Steel, Jour. of the Electrochemical Society, 148(5), pp.B186-B195.
  12. J. Guo, S. Cheng, Z. Cheng, et al., 2013 : Thermodynamics for Precipitation of CaS Bearing Inclusion and Their Deformation During Rolling Process for Al-Killed Ca-Treated Steel, Steel Res. Int., 84(6), pp.545-553. https://doi.org/10.1002/srin.201200253
  13. X. Wang, 2017 : Ladle Furnace Temperature Prediction Model Based on Large-scale Data With Random Forest, IEEE/CAA Jour. of Automatica Sinica, 4(4), pp.770-774. https://doi.org/10.1109/JAS.2016.7510247
  14. D. G. C. Robertson, B. Deo and S. Ohguchi, 1984 : Multi-component Mixed-Transport -Control Theory for Kinetics of Coupled Slag/Metal and Slag/Metal/Gas Reactions: Application to desulphurization of molten iron, Ironmaking and Steelmaking, 11(1), pp.44-55.
  15. S. Ohguchi, D. G. C. Robertson, B. Deo, et al., 1984 : Simultaneous dephosphorization and desulphurization of molten pig iron, Ironmaking and Steelmaking, 11(4), pp.202-213.
  16. X. Zhang, B. Xie, H. Y. Li, et al., 2013 : Coupled reaction kinetics of duplex steelmaking process for high phosphorus hot metal, 40(4), pp.282-289. https://doi.org/10.1179/1743281212Y.0000000036
  17. P. Wei, M. Ohya, M. Hirasawa, et al., 1990 : Interfacial Oxygen Potential in Phosphorus Reaction between Iron Oxide Containing Slag and Molten Iron of High Carbon Concentration, Tetsu-to-Hagane, 76(9), pp.1488-1495. https://doi.org/10.2355/tetsutohagane1955.76.9_1488
  18. D. J. Kim and J. H. Park, 2012 : Interfacial Reaction Between CaO-SiO2-MgO-Al2O3 Flux and Fe-xMn-yAl (x=10 and 20 mass pct, y=1,3, and 6 mass pct) Steel at 1873 K (1600℃), Metall. Mater. Trans. B, 43(4), pp.875-886. https://doi.org/10.1007/s11663-012-9667-x
  19. A. N. Conejo, F. R. Lara, M. Macias-Hernandez, et al., 2007 : Kinetic Model of Steel Refining in a Ladle Furnace, Steel Res. Int., 78(2), pp.141-150. https://doi.org/10.1002/srin.200705871
  20. Y. N. Jia, L. G. Zhu, C. J. Zhang, et al., 2016 : Mass transfer behaviour of Mg in low carbon aluminium killed steel during LF refining, Ironmaking and Steelmaking, 44(10), pp.796-802. https://doi.org/10.1080/03019233.2016.1240848
  21. Y. Liu, M. -F. Jiang, L. -X. Xu, et al., 2012 : Mathematical Modeling of Refining of Stainless Steel in Smelting Reduction Converter Using Chromium Ore, ISIJ Int., 52(3), pp.394-401. https://doi.org/10.2355/isijinternational.52.394
  22. S. -J. Kim, 2019 : Past and present of secondary refining model for inclusion composition control, Kinzoku, 89(9), pp.53-59. (Japanese)
  23. K. J. Graham and G. A. Iron, 2008 : Coupled Kinetic Phenomena in Ladle Metallurgy, In Proc. of the 3rd international conference on process development in iron and steelmaking, pp.385-396, SCANMET III, MEFOS, Lulea, Sweden.
  24. K. J. Graham, 2008 : Integrated Ladle Metallurgy Control, Thesis, McMaster University, Canada.
  25. K. J. Graham and G. A. Iron, 2009 : Toward Integrated Ladle Metallurgy Control, Iron and Steel Tech., 6(1), pp. 164-173.
  26. J. Lehmann, 2016 : Applications of Arcelormittal Thermodynamic Computation Tools to Steel Production, Advances in Molten Slags, Fluxes, and Salts: Proc. of the 10th International Conference on Molten Slags, Fluxes and Salts 2016, pp.697-706, Springer, Cham.
  27. A. Harada, N. Maruoka, H. Shibata, et al., 2013 : A Kinetic M odel to Predict the Compositions of M etal, Slag and Inclusions during Ladle Refining: Part 1. Basic Concept and Application, ISIJ Int., 53(12), pp.2110-2117. https://doi.org/10.2355/isijinternational.53.2110
  28. A. Harada, N. Maruoka, H. Shibata, et al., 2013 : A Kinetic M odel to Predict the Compositions of M etal, Slag and Inclusions during Ladle Refining: Part 2. Condition to Control the Inclusion Composition, ISIJ Int., 53(12), pp. 2118-2125. https://doi.org/10.2355/isijinternational.53.2118
  29. S. -J. Kim, A. Harada and S. Kitamura, 2011 : Condition to suppress spinel formation in ladle treatment predicted by the kinetics simulation model, Proc. of AISTech 2015, 3261, Cleveland, Ohio, USA.
  30. M. Hino and K. Ito, 2010 : Thermodynamic data for steelmaking, pp.10, Tohoku University Press, Sendai, Japan.
  31. FactSage 7.1, Thermfact/CRCR and GTT-Technologies, 1976-2020.
  32. J. -I. Kim, S. -J. Kim and S. Kitamura, 2018 : Effect of inclusions behaviors on the formation of Al2O3 and Spinel inclusions in ladle treatment by simulation model, Proc.of ICS2018, CD-ROM, Venice, Italy.
  33. J. -I. Kim and S. -J. Kim, 2018 : Evolution of inclusions during ladle treatment via simulation model with introduction of changes of Mg content in Mg-Al spinel inclusion, Abst. of 176th ISIJ 2018 meeting, Sendai, Japan.
  34. J. -I. Kim and S. -J. Kim, 2019 : Composition changes in inclusions from Al2O3 to MgO via spinel formation during ladle treatment by simulation model, Abst. of 177th ISIJ 2019 meeting, Tokyo, Japan.
  35. J. -I. Kim and S. -J. Kim, 2020 : Evolution of Mg-Al-based Inclusions with Changes in Mg Content during Ladle Treatment Based on a Coupled Reaction Model, ISIJ Int., 60(4), pp.691-698. https://doi.org/10.2355/isijinternational.isijint-2019-488
  36. J. -I. Kim and S. -J. Kim, 2020 : Influence of Cr Content in Steel on the Behavior of MgO·Al2O3 Spinel Inclusions During Ladle Treatment by Using Kinetic Reaction Model, Trans. Indian Inst. Met., Online-publised, Springer Link.
  37. C. Liu, M. Yagi, X. Gao, et al., 2018 : Kinetics of Transformation of Al2O3 to MgO·Al2O3 Spinel Inclusions in Mg-Containing Steel, Metall. Mater. Trans. B, 49(1), pp. 113-122. https://doi.org/10.1007/s11663-017-1122-6
  38. Q. Shu, O. Volkova, S. Lachmann, et al., 2011 : Modification of Inclusion Composition in Steel During Secondary Metallurgical Ladle Treatment - A Comprehensive Process Simulation Model, Proc of AISTech 2011, pp.537-547, Indianapolis, Ind., USA.