Istrazivanja i projektovanja za privreduJournal of Applied Engineering Science


DOI: 10.5937/jaes0-31764 
This is an open access article distributed under the CC BY 4.0
Creative Commons License

Volume 19 article 894 pages: 1120-1125

Vadim Potemkin*
Saint Petersburg Mining University, Mineral Processing Department, Saint Petersburg, Russian Federation

Tatiana Aleksandrova
Saint Petersburg Mining University, Mineral Processing Department, Saint Petersburg, Russian Federation

This article considers the possibility of developing a methodology for assessing the separation process of gold-sulfide raw materials, taking into account the rheological characteristics of the mineral suspension. The object of the study is the ore of the Mayskoye deposit, which is subjected to fine crushing followed by cyanidation, so the consideration of rheological properties is the most important aspect of achieving the necessary enrichment performance. In the course of the research, using the object-oriented programming language Python 3.8, a program for calculating the empirical coefficients of the three-component rheological equation was developed. The resulting equation is the determinant for the shear stress within the suspension as a function of the velocity gradient. The developed program has been used to calculate coefficients of rheological equations for three variants of solid concentration in feed which correspond to the minimum, average and maximum for hydrocyclone used in the research (400 g/l, 500 g/l and 700 g/l respectively). Then, using the Ansys Fluent software, the multiphase classification modeling problem in the hydrocyclone was solved, resulting in shear rate profiles in the cross-section of the apparatus, from which the conditions necessary for the suspension to reach a fully dispersed state were concluded. It was determined that solid concentration 400 g/l is the optimum value that ensures maximum dispersion of the mineral slurry.

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The work was carried out with the financial support of the Russian Science Foundation (project No.19-17-00096).

1. Shabarov, A.N., Nikolaeva, N.V. (2016). Integrated use of waste from thermal power plant processing. Journal of Mining Institute, vol. 220, 607–610.

2. Afanasova, A.V. (2019). Development of effective technological solutions for the processing of gold-bearing ores, taking into account their criteria of persistence: Ph.D thesis. Saint Petersburg Mining University, 146.

3. Rosenkranz, J., Lamberg, P. (2014). Sustainable processing of mineral resources. International Journal of the Society of Materials Engineering for Resources, vol. 20, no. 1, 17–22, DOI: 10.5188/ijsmer.20.17.

4. Avksentiev, S.Y., Makharatkin, P.N. (2017). Influence of rheology on pressure losses in hydrotransport system of iron ore tailings. Journal of Industrial Pollution Control, vol. 33, no. 1, 741–748.

5. Cruz, N., Forster, J., Bobicki, E.R. (2019). Slurry rheology in mineral processing unit operations: A critical review. The Canadian Journal of Chemical Engineering, vol. 97, no. 7, 2102–2120, DOI: 10.1002/cjce.23476.

6. Vieira, M.G., Peres, A.E.C. (2013). Effect of rheology and dispersion degree on the regrinding of an iron ore concentrate. Journal of Materials Research and Technology, vol. 2, no. 4, 332–339, DOI: 10.1016/j.jmrt.2013.07.002.

7. Avksentiev, S.Y., Nikolaev, A.K. (2017). Influence of Rheology on Pressure Losses in Hydrotransport System of Polymetallic Ores Tailings. IOP Conf. Series: Earth and Environmental Science, vol. 87, no. 5, DOI: 10.1088/1755-1315/87/5/052019.

8. Taner, H.A., Onen, V. (2016). Control of clay minerals effect in flotation. A review. E3S Web of Conferences, vol. 8, DOI: 10.1051/e3sconf/20160801062.

9. Cruz, N., Peng, Y., Wightman, E., & Xu, N. (2015). The interaction of clay minerals with gypsum and its effects on copper-gold flotation. Minerals Engineering, vol. 77, 121–130. DOI: 10.1016/j.mineng.2015.03.010.

10. Genc, A.M., Kilickaplan, I., Laskowski, J.S. (2012). Effect of pulp rheology on flotation of nickel sulphide ore with fibrous gangue particles. Canadian Metallurgical Quarterly, vol. 51, no. 4, 368–375. DOI: 10.1179/1879139512Y.0000000006.

11. Lvov, V.V., Andreev, E.E. (2013). Study of the influence of slurry rheology on classification parameters in the hydrocyclone. Mining informational and analytical bulletin (scientific and technical journal), no. 2, 233–238.

12. Yang, L., Tian, J. L., Yang, Z., Li, Y., Fu, C. H., Zhu, Y. H., & Pang, X. L. (2015). Numerical analysis of non-Newtonian rheology effect on hydrocyclone flow field. Petroleum, vol. 1, no. 1, 68–74. DOI: 10.1016/j.petlm.2015.05.001.

13. Lvov, V.V., Upraviteleva, A.A. (2020). Study of the effect of the magnetic hydrocyclone in the classification of oxidized ferruginous quartzite. Scientific basis and practice of ore and technogenic raw material: conference proceedings 2020, p. 175–180.

14. Valeev, S.I., Savchuk, V.A. (2020). Calculation of the effective viscosity in the hydrocyclone. Technology of mechanical engineering and materials science, vol. 4, p. 16–18.

15. Jiang, L., Liu, P., Zhang, Y., Yang, X., Li, X., Zhang, Y., & Wang, H. (2021). The performance prediction model of W-shaped hydrocyclone based on experimental research. Minerals, vol. 11, no. 2, 1–17. DOI: 10.3390/min11020118.

16. Andreev, E.E., Lvov, V.V., Fadina, A.V. (2013). Causes and meaning of hydrocyclone efficiency curves. Journal of Mining Institute, no. 202, p. 131–136.

17. Karimi, M., Akdogan, G., Bradshaw, S. M., & Mainza, A. (2012). Numerical Modelling of Air Core in Hydrocyclones. Ninth International Conference on CFD in the Minerals and Process Industries 2012, p. 1–6.

18. Durango-Cogollo, M., Garcia-Bravo, J., Newell, B., & Gonzalez-Mancera, A. (2020). CFD modeling of hydrocyclones - A study of efficiency of hydrodynamic reservoirs. Fluids, vol. 5, no. 3, DOI: 10.3390/fluids5030118.

19. Zhukov, V.V., Sharikov, F., Turunen, I., Laari, A. (2013). Simulation of the batch process of gold leaching by cyanidation. Journal of Mining Institute, vol. 202, 178–180.

20. Kuranov, A.D. (2013). Application of Numerical Modeling for Selecting Safe Parameters of Ore Deposit Development Systems in Highly Stressed Massifs. Journal of Mining Institute, vol. 206, no. 7, 60–64.

21. Kaartinen, J., Pietilä, J., Remes, A., & Torttila, S. (2013). Using a virtual flotation process to track a real flotation circuit. IFAC Proc. Volumes, vol. 46, no. 16, 116–121, DOI: 10.3182/20130825-4-US-2038.00061.

22. Parekh, J., Rzehak, R. (2018). Euler–Euler multiphase CFD-simulation with full Reynolds stress model and anisotropic bubble-induced turbulence. International Journal of Multiphase Flow, vol. 99, 231–245, DOI: 10.1016/j.ijmultiphaseflow.2017.10.012.

23. Potemkin V.A., Aleksandrova T.N. (2020). Program for calculating empirical coefficients of the rheological equation: pat. no. RU2020618724. Russian Federation.