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ArticleName Settling parameters determined during thickening and washing of red muds
DOI 10.17580/tsm.2023.04.10
ArticleAuthor Fedorova E. R., Pupysheva E. A., Morgunov V. V.

Saint Petersburg Mining University, Saint Petersburg, Russia:

E. R. Fedorova, Associate Professor at the Department of Process and Plant Automation, Candidate of Technical Sciences, e-mail:
E. A. Pupysheva, Postgraduate Student of the Department of Process and Plant Automation, e-mail:
V. V. Morgunov, Master’s Student of the Department of Process and Plant Automation, e-mail:


This paper substantiates why it is necessary to reduce the concentration of sodium hydroxide in red mud before it can be transported to the mud disposal area and why the liquid-to-solid ratio should be maintained after each unit of the thickening and washing line. The main unit is a single-tier radial thickener comprised of flocculation, free settling, hindered settling and rake zones. The paper gives a brief overview of the basic mathematical formulas describing the hindered and free settling zones of the thickener, as well as the basic material balance equations for describing the countercurrent washers. At the studied site, no reagent is added at the washing stage and there is no flocculation zone in the washers. The first part of experimental study focused on red mud thickening with addition of dissolved flocculant that is normally used at the studied site, considering how it is prepared and injected. Sedimentation curves for red mud samples with different concentrations of solids in the feed stream were obtained. The authors substantiate the application of modified Kynch method for calculating empirical parameters based on sedimentation curves. The following parameters were calculated: settling rate, average Stokes diameter of a flocculated particle, critical concentration (gel point), hindered settling index. The Kynch flux density functions were calculated for different concentrations of solids in the initial slurry. The second part of experimental study focused on countercurrent washing of the earlier flocculated slurry. Following a series of periodic experiments on sedimentation of flocculated slurry involving 3, 4, 5 and 6 cycles of countercurrent washing, conclusions were drawn on the concentration of sodium hydroxide at each washing stage, and the washing efficiency was estimated. The described results will be used for building a mathematical model of a radial thickener at the thickening and washing stage.

keywords Red mud, thickening, washing, settling zone, mathematical model, causticity, washing efficiency, machine vision

1. Zinoveev D., Pasechnik L., Fedotov M. et al. Extraction of valuable elements from red mud with a focus on using liquid media — A Review. Recycling. 2021. Vol. 6, Iss. 38. DOI: 10.3390/recycling6020038
2. Mishra Brajendra, Gostu Sumedh. Materials sustainability for environment: Red-mud treatment. Frontiers of Chemical Science and Engineering. 2017. Vol. 11. DOI: 10.1007/s11705-017-1653-z
3. Piirainen V. Yu., Barinkova A., Starovoytov V. N., Barinkov V. Deactivation of red mud by primary aluminum production wastes. Materials Science Forum. 2021. Vol. 1040. pp. 109–116. DOI: 10.4028/
4. Alam Md Kh., Zanganeh J., Moghtaderi B. The composition, recycling and utilisation of Bayer red mud. Resources Conservation and Recycling. 2018. Vol. 141. pp. 483–498. DOI: 10.1016/j.resconrec.2018.11.006
5. Pyagay I. N., Kremcheev E. A., Pasechnik L. A., Yatsenko S. P. Carbonization processing of bauxite residue as an alternative rare metal recovery process. Tsvetnye Metally. 2020. No. 10. pp. 56–63. DOI: 10.17580/tsm.2020.10.08
6. Raghubanshi A. S. et al. Recycling and potential utilization of red mud (Bauxite Residue) for construction industry applications. Indian Journal of Engineering and Materials Sciences. 2022. Vol. 29, Iss. 4. pp. 401–410.
7. Archambo M. New horizons for processing and utilizing red mud. Houghton, Michigan : Michigan Technological University, 2021. 213 p.
8. Tanvar Himanshu, Mishra Brajendra. Hydrometallurgical recycling of red mud to produce materials for industrial applications: alkali separation, iron leaching and extraction. Metallurgical and Materials Transactions B. 2021. Vol. 52. pp. 1–15. DOI: 10.1007/s11663-021-02285-5
9. Piirainen V. Yu., Mikhaylov A. V., Barinkova A. A. The concept of modern ecosystem for the Ural Aluminium Smelter. Tsvetnye Metally. 2022. No. 7. pp. 39–45. DOI: 10.17580/tsm.2022.07.04
10. Fawell Ph., Nguyen T., Solnordal C., Stephens D. Enhancing gravity thickener feedwell design and operation for optimal flocculation through the application of computational fluid dynamics. Mineral Processing and Extractive Metallurgy Review. 2021. Vol. 42. pp. 496–510. DOI: 10.1080/08827508.2019.1678156
11. Brichkin V. N., Vasilyev V. V., Nagornaya E. А., Gumenyuk A. M. Bauxite grade improvement through selective grinding. Obogashchenie Rud. 2017. No. 3. pp. 3–9. DOI: 10.17580/or.2017.03.01
12. Alexandrov V. I., Kibirev V. I., Serzhan S. L. The effectiveness of polyurethane coatings on internal surfaces of slurry lines in tailings slurry hydrotransport systems. Obogashchenie Rud. 2020. No. 4. pp. 35–41. DOI: 10.17580/or.2020.04.06
13. Avksentyev S. Yu., Makharatkin P. N., Safiullin R. N., Aleksandrov V. I. Specific pressure loss calculations for tailings hydrotransport at the Kachkanar GOK. Obogashchenie Rud. 2022. No. 3. pp. 45–51. DOI: 10.17580/or.2022.03.08
14. Tian J. L., Zhang Z. Y., Jiang Y. H. The application of intelligent control to red mud settling and washing in an alumina refinery. Minerals, Metals and Materials Series. Springer Science and Business Media Deutschland GmbH, 2021. Vol. 6. pp. 3–9.
15. Li H., Ai-xiang Wu, Hong-Jiang Wang, Hui Chen et al. Changes in underflow solid fraction and yield stress in paste thickeners by circulation. International Journal of Minerals, Metallurgy and Materials. 2021. Vol. 28, No. 3. pp. 349–357.
16. Boikov A. V., Savelev R. V., Payor V. A., Potapov A. V. Evaluation of bulk material behavior control method in technological units using DEM. Part 2. CIS Iron and Steel Review. 2020. No. 2. pp. 3–6. DOI: 10.17580/cisisr.2020.02.01
17. Li L., Iskander M. Use of machine learning for classification of sand particles. Acta Geotechnica. 2022. DOI: 10.1007/s11440-021-01443-y
18. Madarász L., Köte Á., Hambalkó B., Csorba K. et al. In-line particle size measurement based on image analysis in a fully continuous granule manufacturing line for rapid process understanding and development. International Journal of Pharmaceutics. 2022. Vol. 612. DOI: 10.1016/J.IJPHARM.2021.121280
19. Beloglazov I., Petrov P., Bazhin V. The concept of digital twins for tech operator training simulator design for mining and processing industry. Eurasian Mining. 2020. No. 2. pp. 50–54. DOI: 10.17580/em.2020.02.12
20. 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
21. Precision Light & Air. Available at: (Accessed: 15.12.2022).
22. Aleksandrova T. N., Potemkin V. A. Development of a methodology to assess the hydrocyclone process with account of the rheological properties of the mineral slurry. Journal of Mining Institute. 2021. Vol. 252. pp. 908–916. DOI: 10.31897/PMI.2021.6.12
23. Sizyakov V. M., Litvinova T. E., Brichkin V. N., Fedorov A. T. Modern physicochemical equilibrium description in Na2O – Al2O3 – H2O system and its analogues. Journal of Mining Institute. 2019. Vol. 237. pp. 298–306. DOI: 10.31897/pmi.2019.3.298
24. Zhang Hualu, Wang Fuli, Li Kang, Luping Zhao. Stochastic chance-constrained optimization framework for the thickening-dewatering process with an uncertain feed quantity. Chemical Engineering Research and Design. 2021. Vol. 173. DOI: 10.1016/j.cherd.2021.07.013
25. Nemchinova N. V., Tyutrin A. A., Somov V. V. Determining optimum parameters of fluorine leaching from the carbon part of spent pot lining. Journal of Mining Institute. 2019. Vol. 239. p. 544. DOI: 10.31897/pmi. 2019.5.544
26. Liu X., Yin H., Zhao J., Guo Z. et al. Understanding the coagulation mechanism and floc properties induced by Fe(VI) and FeCl3: population balance modeling. Water Science and Technology. IWA Publishing, 2021. Vol. 83, No. 10. pp. 2377–2388.
27. Loginova I. V., Kyrchikov A. V., Penyugalova N. P. Alumina production process : Learner’s guide. Ed. by I. V. Loginova. Yekaterinburg : Izdatelstvo Uralskogo universiteta, 2015. 336 p.
28. Salamatov V. I., Salamatov O. V. Understanding the process kinetics of thickening and washing of low-silicon bauxite residues. Vestnik Irkutskogo gosudarstvennogo tekhnicheskogo universiteta. 2018. Vol. 22, No. 4. pp. 191–202. DOI: 10.21285/1814-3520-2018-4-191-202
29. Gandurina L. V. Use of organic flocculants for treatment of natural and industrial wastewater and for sludge treatment. Construction site utility services: An overview. VNIINTPI. Moscow, 2000. Iss. 2. 59 p.
30. Fedorova E. R., Firsov A. Yu. Red mud thickening process simulation. Gornyy informatsionno-analiticheskiy byulleten. 2016. No. 11. pp. 3–28.
31. Romashev A. O., Nikolaeva N. V., Gatiatullin B. L. An adaptive approach built on the basis of machine vision used for determining concentrate settling parameters. Journal of Mining Institute. 2022. Vol. 256. pp. 677–685. DOI: 10.31897/PMI.2022.77
32. Salamatov O. V., Salamatov V. I. On the effect of flocculants on the process kinetics of thickening and washing of low-silicon bauxite residues in alumina production. Vestnik Irkutskogo gosudarstvennogo tekhnicheskogo universiteta. 2019. Vol. 23, No. 2. pp. 404–414. DOI: 10.21285/1814-3520-2019-2-404-414
33. Chernigov D. A., Bogorodskiy A. V., Nabiulin R. N., Mineeva T. S. Understanding the processes of thickening gold ore process slurries. Vestnik Irkutskogo gosudarstvennogo tekhnicheskogo universiteta. 2021. Vol. 25, No. 3. pp. 391–401. DOI: 10.21285/1814-3520-2021-3-391-401
34. Laros T., Slottee S., Baczek F. Testing, sizing, and specifying sedimentation equipment. Mineral Processing Plant Design, Practice and Control. 2022. Vol. 1. 2243 p.
35. Kynch G. J. A theory of sedimentation. Transactions of the Faraday Society. 1952. Vol. 48. p. 166.
36. Labiosa A. A. Dynamic simulation of red mud washers used in aluminum industries. School of Civil, Environmental and Chemical Engineering RMIT University VICTORIA. Australia, 2010. 143 p.

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