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Mathematical Modeling in Education, Research and Low-Energy Metallurgical Technologies

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Abstract

The paper presents a retrospective of the scientific and educational activities of the creative team from the Department of Applied Information Technologies and Programming. Established in 1980, the team of the department set a task to create a new type of specialists (problem programmers), who were skillful at methods of research and mathematical object description (including metallurgical objects), as well as computer programming. By a special order of the Ministry of Higher Education of the Russian Soviet Federative Socialist Republic (RSFSR), a new specialization was created on a trial basis: “Mathematical support and computers in metallurgy”, which, after the 20-year pedagogical experiment, have translated into a specialty “Information systems and technologies (branch-wise).” This department was the first to have such specialists graduate not only in the region, but also in the country, which was then adopted by other universities. The team of the newly created department was one of the first in the country to start creating mathematical metallurgical modeling, followed by simulators and training systems on its basis. An activity-based approach to learning based on a mathematical model of a specific subject area was adopted as a pedagogical concept; many years of experience in applying this approach have shown its high efficiency. For the first time in the world metallurgy, a concept and a set of models of a fundamentally new metallurgical process and a unit with elements of self-organization, which is characterized by an order of magnitude lower specific volume and one and a half times lower energy consumption, have been created. Together with the designers and specialists of West-Siberian Metal Plant (ZSMK), a large-scale pilot installation for the JER process and unit is created, on which the correctness of the proposed concept is confirmed, the main design points are worked out, and the practical feasibility of a number of new developed technologies is shown. In the creation of the new process, software tools have been developed: an interrelated process and unit algorithm, an Engineering–Metallurgy system, a complex heat transfer modeling system, and a particle level simulation system using the Monte Carlo method.

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Notes

  1. I.A. Rybenko, S.P. Mochalov, A.B. Yuriev, V.V. Sokolov, V.P. Tyutyulnikov, S.V. Shchipanov, A.A. Rybushkin, E.V. Suzdaltsev, K.M. Shakirov, A.G. Padalko, E.I. Livertz, and S.Yu. Krasnoperov took part in the project.

REFERENCES

  1. Tsymbal, V.P., Control of oxidizing ability of open hearth furnace based on the static model using boiling bath self-regulating, Izv. Vyssh. Uchebn. Zaved., Chern. Metall., 1975, no. 4, pp. 162–165.

  2. Kurdyumov, S.P. and Malinetskii, G.G., Sinergetika—teoriya samoorganizatsii (Synergetics—Theory of Self-Organization), Moscow: Znanie, 1983.

  3. Nicolis, G. and Prigogine, I., Self-Organization in Non-Equilibrium Systems, New York: Wiley, 1977.

    Google Scholar 

  4. Haken, H., Synergetics, Berlin: Springer-Verlag, 1978.

    Book  Google Scholar 

  5. Prigogine, I. and Stengers, I., Order Out of Chaos. Man’s New Dialogue with Nature, London: Heinemann, 1984.

    Google Scholar 

  6. Klimontovich, Yu.L., Turbulentnoe dvizhenie i struktura khaosa. Novyi podkhod k statisticheskoi teorii otkrytykh sistem (Turbulent Motion and Chaos Structure: A New Approach to Statistical Theory of Open Systems), Moscow: Nauka, 1990.

  7. Knyazeva, E.N. and Kurdyumov, S.P., Osnovaniya sinergetiki: Rezhimy s obostreniem, samoorganizatsiya, tempomiry (Principles of Synergetics: Exacerbated Modes, Self-Organization, Temp Worlds), St. Petersburg: Aleteiya, 2002.

  8. Tsymbal, V.P., Mochalov, S.P., Rybenko, I.A., et al., Protsess SER—metallurgicheskii struino-emul’sionnyi reaktor (JER Process—Metallurgical Jet-Emulsion Reactor), Moscow: Metallurgizdat, 2014.

  9. Tsymbal, V.P., Mochalov, S.P., and Shakirov, K.M., Controlling the composition of the metal in the direct reduction of dust-sized materials and waste products in a jet-emulsion reactor, Metallurgist, 2015, vol. 59, nos. 1–2, pp. 119–125.

    Article  CAS  Google Scholar 

  10. Nakoryakov, V.E., Pokusaev, B.G., and Shreiber, I.R., Wave Propagation in Gas-Liquid Media, Boca Raton: CRC Press, 1993.

    Google Scholar 

  11. Gordon, Ya.M., Spirin, N.A., Shvydkii, V.S., et al., Scrap metal as an important secondary resource for improving energy efficiency and resource saving in steel industry, in Metallurgiya: tekhnologii, innovatsii, kachestvo (Metallurgy: Technology, Innovation, and Quality), Novokuznetsk, 2017, part 1, pp. 390–400.

  12. Korostelev, A.A., S’emshchikov, N.S., Semin, A.E., et al., Increase in EAF lining life with use of hot-briquetted iron in a charge, Refract. Ind. Ceram., 2018, vol. 59, no. 2, pp. 107–114.

    Article  CAS  Google Scholar 

  13. Luckhoff, J., Apfel, J., and Buttler, J., Application of different kinds of metal charge materials in EAF operation, Chern. Met., 2017, no. 10, pp. 28–33.

  14. Abd Elkader, M., Fathy, A., Eissa, M., and Sayed, Sh., Effect of direct reduced iron proportion in metallic charge on technological parameters of EAF steelmaking process, ISIJ Int., 2016, vol. 5, no. 2, pp. 2016–2024.

    Google Scholar 

  15. Sulimova, M.A. and Litvinova, T.E., Metallurgical production waste treatment efficiency increase, Proc. 16th Int. Multidisciplinary Scientific GeoConference (SGEM 2016) “Ecology, Economics, Education and Legislation,” Red Hook, NY: Curran Associates, 2016, vol. 2, pp. 569–575.

    Google Scholar 

  16. Duarte, P. and Beserra, Kh., Production of high-carbon iron by direct carbon reduction (DRI) using Energiron DR technology, Chern. Met., 2016, no. 6, pp. 24–30.

  17. Dorofeev, G.A., Yantovskii, P.R., Smirnov, K.G., and Stepanov, Ya.M., The process “orient” for smelting of high-quality steels from ore and energy raw materials based on the principle of the energy self-supplying, Chern. Met., 2017, no. 5, pp. 17–23.

  18. Kinaci, M.E., Lichtenegger, T., and Schneiderbauer, S., Direct reduction of iron-ore in fluidized beds, Proc. 28th European Symp. on Computer Aided Process Engineering, Graz, 2018, vol. 43, pp. 217–222.

  19. Schenck, J. and Lungen, H., Review of application of DRI processes in EC countries, Chern. Met., 2017, no. 2, pp. 25–31.

  20. Meijer, K., van der Stel, J., Zeilstra, C., et al., The HIsarna ironmaking process, Proc. METEC and 2nd ESTAD, June 15–19,2015, Düsseldorf, 2015, pp. 15–19.

  21. Basdag, A. and Arol, A.I., Coating of iron oxide pellets for direct reduction, Scand. J. Metall., 2002, vol. 31, no. 3, pp. 229–233.

    Article  CAS  Google Scholar 

  22. Rybenko, I.A. and Olennikov, A.A., RF Inventor’s Certificate no. 2017617445, 2017.

  23. Vatolin, N.A., Moiseev, G.K., and Trusov, B.G., Termodinamicheskoe modelirovanie v vysokotemperaturnykh neorganicheskikh sistemakh (Thermodynamic Modeling in High-Temperature Inorganic Systems), Moscow: Metallurgiya, 1994.

  24. Kroese, D.P., Brereton, T., Taimre, T., and Botev, Z.I., Why the Monte Carlo method is so important today, WIREs Comput. Stat., 2014, vol. 6, no. 6, pp. 386–392.

    Article  Google Scholar 

  25. Tsymbal, V., Olennikov, A., Rybenko, I., et al., Mathematical modeling of SER jet-emulsion process, Proc. 2017 Sustainable Industrial Processing Summit and Exhibition (SIPS 2017), Kongoli, F., Conejo, A., and Gomez-Marroquin, M.C., Eds., Montreal, 2017, vol. 9, pp. 104–115.

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Authors and Affiliations

  1. Siberian State Industrial University, 6540007, Novokuznetsk, Kemerovo oblast, Russia

    V. P. Tsymbal, V. N. Buintsev, V. I. Kozhemyachenko, S. N. Kalashnikov & P. A. Sechenov

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  1. V. P. Tsymbal
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  2. V. N. Buintsev
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  3. V. I. Kozhemyachenko
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  4. S. N. Kalashnikov
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  5. P. A. Sechenov
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Correspondence to V. P. Tsymbal, V. I. Kozhemyachenko or P. A. Sechenov.

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Translated by A. Kolemesin

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Tsymbal, V.P., Buintsev, V.N., Kozhemyachenko, V.I. et al. Mathematical Modeling in Education, Research and Low-Energy Metallurgical Technologies. Steel Transl. 50, 317–326 (2020). https://doi.org/10.3103/S0967091220050113

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