Saint Petersburg Mining University, Saint Petersburg, Russia:

V. Yu. Bazhin, Head of the Metallurgy Department, Professor, Doctor of Technical Sciences, e-mail: bazhin_vyu@pers.spmi.ru
T. R. Kosovtseva, Associate Professor at the Department of Computer Science and Technology, Candidate of Technical Sciences, e-mail: Kosovtceva_TR@pers.spmi.ru
A. Z. Muzipov, Postgraduate Student at the Department of Process and Plant Automation, e-mail: s225026@stud.spmi.ru

The process of copper matte conversion has been in use for a long time at multiple sites around the world. The steady operation of furnaces and converters can be achieved through a good selection of blasting modes aimed at minimi zing raw material losses and hazardous emissions. With the aim to develop the resource and energy saving plan and tackle the environmental issues, this paper considers a digital model of a converter equipped with adjustable water-cooled tuyeres. It describes how copper-bearing burden can be processed based on a completely new technique of delivering the oxygen-air mixture into the melt. It is a spatially oriented technique, which helps combine as much as possible the heat generation and heat transfer zones inside a unit. Experiments were conducted, which confirmed a significant increase of specific blasting rate compared with known blasting techniques. With the help of mathematical modelling, the authors built a 3D model to demonstrate that, by creating spatially-oriented jets coming from the converter tuyeres, one can raise the specific capacity of an autogenous cylindrical converter while reducing the loss of melt droplets, as well as heat radiation. The resultant mathematical models suggest that the steady operation of a converter can be secured by regular, controlled heat and mass transfer, which can be achieved by making the gas phase move centrifugally above the melt and making the melt move in a certain way inside the converter. Considering the size of the converter and, correspondingly, the different values of kinetic jet energy, as well as the different melt behaviour, the authors looked at the changing melt rotation speed field. The developed scheme can be used with vertical converters, which will ensure more efficient processing of copper-bearing burden. The described model can be adapted to other types of furnaces – in particular, to those used for processing copper-bearing raw materials.

1. Litvinenko V. S., Tsvetkov P. S., Molodtsov K. V. The social and market mechanism of sustainable development of public companies in the mineral resource sector. Eurasian Mining. 2020. No. 1. pp. 36–41. DOI: 10.17580/em.2020.01.07
2. Litvinenko V., Bowbrick I., Naumov I., Zaitseva Z. Global guidelines and requirements for professional competencies of natural resource extraction engineers: Implications for ESG principles and sustainable development goals. Journal of Cleaner Production. 2022. Vol. 338. pp. 1–9. DOI: 10.1016/j.jclepro.2022.130530
3. Shalygin L. M. Analyzing the efficiency of using oxygen for matte conversion. Tsvetnye Metally. 1996. No. 2. pp. 12–16.
4. Baptizmanskiy V. I. Theory of basic oxygen process. Moscow : Metallurgiya, 1975. 374 p.
5. Tsemekhman L. Sh., Ryabko A. G., Lukashev L. P. Autogenous smelting of copper and copper-nickel sulphide material and middlings in top-blown oxygen converters. Tsvetnye Metally. 1998. No. 2. pp. 26–32.
6. ANSYS CFX, Release 11.0. Ansys Inc., 2007.
7. Menter F. R. Two-equation eddy-viscosity turbulence models for engineering applications. AIAA Journal. 1994. Vol. 32, No. 8. pp. 1598–1605.
8. Snegirev A. Yu. Applied physics and high-performance calculations. Numerical modelling of turbulent flows: Learner’s guide. St. Petersburg : Izdatelstvo Politekhnicheskogo universiteta, 2008. 142 p.
9. Menter F. R., Kuntz M., Langtry R. Ten years of experience with the SST turbulence model. Turbulence, Heat and Mass Transfer 4. Ed. by K. Hanjalic, Y. Nagano, M. Tummers. Begell House Inc., 2003. pp. 625–632.
10. Colton H. A., Konovalov G. V., Kosovtseva T. R. Mathematical description of rotation of liquid under the influence of tangential stresses. International Journal of Pure and Applied Mathematics. 2018. Vol. 119, No. 10. Special Issue. pp. 423–426.
11. Kuskova Y. V., Erokhina O. O., Simakov A. S. Problematics and perspectives of the development of automatic control systems for concentration tables using computer simulation. Journal of Physics: Conference Series. IOP Publishing, 2019. Vol. 1384, No. 1. p. 012023. DOI: 10.1088/1742-6596/1384/1/012023
12. Fedorova E., Pupysheva E., Morgunov V. Modelling of red-mud particlesolid distribution in the feeder cup of a Thickener using the combined CFDDPM approach. Summetry. 2022. Vol. 14. 2314. DOI: 10.3390/sym14112314
13. Martynov S. A., Masko O. N., Fedorov S. N. Innovative ore-thermal furnace control systems. Tsvetnye Metally. 2022. No. 4. pp. 87–94. DOI: 10.17580/tsm.2022.04.11
14. Pardo F. R. O. et al. Metallographic properties evaluation of the specimens obtained by the vibratory method (cast iron ISO 400-12). Journal of Physics: Conference Series. IOP Publishing. 2022. Vol. 2388, No. 1. p. 012058. DOI: 10.1088/1742-6596/2388/1/012058
15. Ishimbaev A. V., Matyukhin V. I. Computer simulation of fluid dynamics in an oxygen converter. Important problems of engineering sciences: Proceedings of the 24^th Regional Competition of Research Papers Olympus of Science in the area of Engineering Sciences. Yekaterinburg : Uralskiy federalnyi universitet, 2021. pp. 75–80.
16. Nakamura H., Makino S., Ishii M. Continuous shear thickening and discontinuous shear thickening of concentrated monodispersed silica slurry. Advanced Powder Technology. 2020. Vol. 31, No. 4. pp. 1659–1664.
17. Shestakov A. K., Petrov P. A., Nikolaev M. Yu. Automatic system for detecting visible emissions in a potroom of aluminium plant based on technical vision and a neural network. Metallurg. 2022. No. 10. pp. 105–112. DOI: 10.52351/00260827_2022_10_105
18. Konovalov G. V. Peculiarities of mass transfer under the influence of radial-axial blasting jets. Journal of Mining Institute. 2002. Vol. 150. pp. 120–122.
19. Beloglazov I., Krylov K. An interval-simplex approach to determine technological parameters from experimental data. Mathematics. 2022. Vol. 10, No. 16. p. 2959. DOI: 10.3390/math10162959
20. Sharikov F. Y., Sharikov Y. V., Krylov K. A. Selection of key parameters for green coke calcination in a tubular rotary kiln to produce anode petcoke. ARPN Journal of Engineering and Applied Sciences. 2020. Vol. 15. pp. 2904–2912.
21. Shestakov A. K., Sadykov R. M., Petrov P. A. Multifunctional crust breaker for automatic alumina feeding system of aluminum reduction cell. E3S Web of Conferences. EDP Sciences, 2021. Vol. 266. 09002. DOI: 10.1051/e3sconf/202126609002
22. Zakharov L. А., Martyushev D. А., Ponomareva I. N. Predicting dynamic formation pressure using artificial intelligence methods. Journal of Mining Institute. 2022. Vol. 253. pp. 23–32. DOI: 10.31897/PMI.2022.11
23. Vasilyeva N. V. et al. Automated digitization of radial charts. Journal of Mining Institute. 2021. Vol. 247. pp. 82–87. DOI: 10.31897/PMI.2021.1.9
24. Shklyarskiy Y. E., Batueva D. E. Operation mode selection algorithm development of a wind-diesel power plant supply complex. Journal of Mining Institute. 2022. Vol. 253. pp. 115–126. DOI: 10.31897/PMI.2022.7
25. Bazhin V. Y., Nguyen H. H. Vietnamese metallurgy on the way out of the crisis with the use of automated control systems. AIP Conference proceedings. AIP Publishing LLC. 2022. Vol. 2467. 030018. DOI: 10.1063/ 5.0092750
26. Simakov A. S., Trifonova M. E., Gorlenkov D. V. Virtual Analyzer of the Voltage and Current Spectrum of the Electric Arc in Electric Arc Furnaces. Russian Metallurgy (Metally). 2021. Vol. 2021, No. 6. pp. 713–719. DOI: 10.1134/S0036029521060252
27. Kulchitskii A. A., Kashin D. A. The choice of a method for non-contact assessment of the composition of briquetted charge materials. Journal of Physics: Conference Series. IOP Publishing. 2019. Vol. 1399, No. 4. p. 044108. DOI: 10.1088/1742-6596/1399/4/044108
28. Boikov A., Payor V. The present issues of control automation for levitation metal melting. Symmetry. 2022. Vol. 14, No. 10. p. 1968. DOI: 10.3390/sym14101968
29. Skuratov A. P., Skuratova S. D. Design options and thermal design of electric smelters: Learner’s guide. Krasnoyarsk : Sibirskiy federalnyi universitet, 2012. 168 p.
30. Voronin v. A., Nepsha F. S. Simulation modelling of the electric drive of a shearer for analyzing the efficiency of the power supply system. Journal of Mining Institute. 2020. Vol. 246. pp. 633–639. DOI: 10.31897/PMI.2020.6.5
31. Davenport W. G. I. et al. Extractive metallurgy of copper. Elsevier, 2002. 432 p. DOI: 10.1016/B978-0-12-821875-4.00017-1
32. Skuratov A. P., Ivlev A. V., Pianykh A. A. Calculated study of the influence of overheating aluminum melt on the dynamics the granulation process. Journal of Siberian Federal University. Engineering & Technologies. 2020. Vol. 13, No. 1. pp. 84–93.
33. Shalygin L. M., Konovalov G. V. The structure of heat balance, heat generation and heat transfer in autogenous metallurgical units of different type. Tsvetnye Metally. 2003. No. 10. pp. 17–24.
34. Sizyakov V. M., Konovalov G. V. Spatially-oriented unsubmerged jets as the basis of the novel design autogenous units. Tsvetnye Metally. 2016. No. 10. pp. 14–20. DOI: 10.17580/tsm.2016.10.02
35. Solero L., Lidozzi A., Pomilio J. A. Design of multiple-input power converter for hybrid vehicles. IEEE Transactions on Power Electronics. 2005. Vol. 20, Iss. 5. pp. 1007–1016. DOI: 10.1109/TPEL.2005.854020