Using the results of the phase composition of magnetit ore for prediction of the concentrate yield

The purpose of the research was the development of a mathematical model for calculating the yield of magnetite concentrate with a given quality and calculating the mass fraction of iron in the tailings according to the phase composition of the original ore for iron. Predicting of the yield of concentrate with a given quality is possible using theoretical and experimental models. The predicted values of the mass fractions of total and magnetite iron in the tailings are calculated according to the equations of the technological balance with using the theoretical values of the concentrate yield. The analytical model for calculating the concentrate yield includes the sum of two components. The first component is characterized by the recovery of the magnetic phase of iron into the concentrate. The second component is characterized by the recovery of the non-magnetic phase of iron into the concentrate. The values of individual factors included in the analytical model are determined with high errors. Therefore, the analytical model was replaced by a regression model that includes experimental coefficients and two factors. The factors used were the mass fractions of total and magnetite iron in the ore. The absolute maximum error of prediction of the concentrate yield was ±0.31% at P = 95%. The mathematical model allows planning the mass fractions of total iron and magnetite in the ore in order to obtain the required concentrate yield and to identify the reasons for the decrease of the concentrate yield or an increase in the mass fraction of iron in the tailings.

Pelevin A. E. Using the results of the phase composition of magnetit ore for prediction of the concentrate yield. MIAB. Mining Inf. Anal. Bull. 2022;(5—1):131—144. [In Russ]. DOI: 10.25018/0236_1493_2022_51_0_131.

Pelevin A. E., Dr. Sci. (Eng.), Associate Professor, Professor of the Department of Mineral Processing at the Ural State Mining University, ORCID iD https://orcid.org/0000-00016063-3932, a-pelevin@yandex.ru, Ural State Mining University, 620144, 30, Kuibyshev st., Ekaterinburg, Russia.

1. Vaisberg L. A., Korovnikov A. N., Trofimov V. A. Innovative re-equipment of screening circuits (to commemorate the 100th anniversary of the Mekhanobr Institute). Gornyi Zhurnal. 2017, no. 1, pp. 11—17. [In Russ]. DOI: 10.17580/gzh.2017.01.02. DOI: 10.17580/gzh.2017.01.02.

2. Palaniandy S., Halomoan R., Ishikawa H. TowerMill circuit performance in the magnetite grinding circuit The multi-component approach. Minerals Engineering. 2019, vol. 133, рр. 10—18. DOI:10.1016/j.mineng.2018.12.019.

3. Pelevin A. E., Sytykh N. A. Increased magnetic field induction separators in titanium magnetite ore processing. Obogashchenie Rud. 2020, no 2, pp. 15—20. [In Russ]. DOI: 10.17580/or.2020.02.03.

4. Pelevin A. E., Tsypin E. F., Koltunov A. V., Komlev S. G. High-intensity magnetic separators with permanent magnets. Izvestiya Vysshikh Uchebnykh Zavedenii. Gornyi Zhurnal. 2001, no. 4—5. pp. 133—136. [In Russ].

5. Vaisberg L. A., Dmitriev S. V., Mezenin A. O. Controllable magnetic anomalies in mineral processing technologies. Gornyi Zhurnal. 2017, no. 10. pp. 26—32. [In Russ]. DOI: 10.17580/gzh.2017.10.06.

6. Pelevin A. E., Sytykh N. A. Fine hydraulic screening for staged separation of titanium-magnetite concentrate. Obogashchenie Rud. 2021, no. 1, pp. 8—14. [In Russ]. DOI: 10.17580/or.2021.01.02.

7. Opalev A. S., Birukov V. V., Scherbakov A. V. Stadial obtaining of the magnetite concentrate during the development of power resource-saving technology of benefication of ferruginous quartzites on JSC «Olcon». MIAB. Mining Inf. Anal. Bull. 2015, no. 11, pp. 60—62. [In Russ].

8. Pattanaik A., Rayasam V. Analysis of reverse cationic iron ore fines flotation using RSM-D-optimal design An approach towards sustainability. Advanced Powder Technology. 2018, vol. 29, is. 12, рр. 3404—3414. DOI:10.1016/j.apt.2018.09.021.

9. Veloso C. H., Filippov L. O., Filippova I. V., Ouvrard S., Araujo A. C.. Investigation of the interaction mechanism of depressants in the reverse cationic flotation of complex iron ores. Minerals Engineering. 2018, vol. 125, рр. 133—139. DOI: 10.1016/j.mineng.2018.05.031.

10. Matiolo E., Couto H. J. B., Lima N., Silva K., Freitas A. S. Improving recovery of iron using column flotation of iron ore slimes. Minerals Engineering. 2020, vol. 158, 106608. DOI: 10.1016/j.mineng.2020.106608.

11. Nemykin S. A., Kopanev S. N., Mezentseva E. V., Okunev S. M. Iron concentrate production with the increased content of useful component. Gornyi Zhurnal. 2017, no. 5, pp. 27—31. [In Russ]. DOI: 10.17580/gzh.2017.05.05.

12. Ismagilov R. I., Kozub A. V., Gridasov I. N., Shelepov E. V. Advanced solutions applied by JSC Andrei Varichev Mikhailovsky GOK to improve ferruginous quartzite concentration performance. Gornaya Promyshlennost’. 2020, no. 4, pp. 98—103. [In Russ]. DOI: 10.30686/1609—9192—2020—4—98—103.

13. Opalev A. S., Khokhulya M. S., Fomin A. V., Karpov I. V. Creation of innovative technologies for production of high-quality iron concentrate production in the North West of Russia. Gornyi Zhurnal. 2019, no 6, pp. 56—61. [In Russ]. DOI: 10.17580/gzh.2019.06.07.

14. Morozov V. V., Topchaev V. P., Ulitenko K. Ya., Ganbaatar Z., Delgerbat L. Razrabotka i primenenie avtomatizirovannyh sistem upravleniya processami obogashcheniya poleznyh iskopaemyh [Development and application of automated control systems for mineral processing]. Мoscow, Ruda i metally, 2013, 512 р. [In Russ].

15. Pelevin A. E. Effects of magnetic flocculation on iron-bearing ore concentration. Obogashchenie Rud. 2021, no 4, pp. 15—20. [In Russ]. DOI: 0.17580/or.2021.04.03.

16. Erdenesul J., Morozov V. V. Optimizing copper-molybdenum ore milling coarseness using model-oriented criteria. MIAB. Mining Inf. Anal. Bull. 2018, no. 8, pp. 176—183. [In Russ]. DOI: 10.25018/0236-1493-2018-8-0-176-183.

17. Оsipova N. V. Selecting parameters of feed control algorithm for wet autogenous mill for grinding iron ore. MIAB. Mining Inf. Anal. Bull. 2021, no. 10, рр. 146—156. [In Russ]. DOI: 10.25018/0236_1493_2021_10_0_146.

18. Melekhina   K. A., Ananyev   P. P.,   Plotnikova A. V.,   Timofeev A. S.,   Shestak

S. A. Modeling and optimization of complex ore pretreatment by disintegration in autogenous mills. MIAB. Mining Inf. Anal. Bull. 2020, no. 10, рр. 95—105. [In Russ]. DOI: 10.25018/0236—1493—2020—10—0—95—105.

19. Kuskov V. B., Lvov V. V., Yushina T. I. Increasing the recovery ratio of iron ores in the course of preparation and processing. CIS Iron and Steel Review, 2021, vol. 21, pp. 4—8. [In Russ]. DOI: 10.17580/cisisr.2021.01.01.

20. Pelevin A. E. Production of hematite concentrate from hematite–magnetite ore. MIAB. Mining Inf. Anal. Bull. 2020. No. 3—1, pp. 422—430. [In Russ]. DOI: 10.25018/0236— 1493—2020—31—0—422—430.

21. Tripathy S. K., Singh V, Murthy Y. R., Banerjee P. K., Suresh N. Influence of process parameters of dry high intensity magnetic separators on separation of hematite. International Journal of Mineral Processing. 2017, vol. 160, рр. 16—31. DOI:10.1016/j. minpro.2017.01.007.

22. Shrimali K., Atluri V., Wang Y., Bacchuwar S., Miller J. D. The nature of hematite depression with corn starch in the reverse flotation of iron ore. Journal of Colloid and Interface Science. 2018, vol. 524, рр. 337—349. DOI: 10.1016/j.jcis.2018.04.002.

23. Zhanglei Z., Zhen L., Wanzhong Y., Bin Y., Jinzhou Q., Ningning Z., Songjiang C., Yuexian Y., Jing C., Lijun L. Snap-in interactions between water droplets and hematite/ quartz surfaces with various roughness after conditioning with soluble starch and DDA using a dynamic microbalance. Minerals Engineering. 2022, vol. 177, 107358. DOI: 10.1016/j. mineng.2021.107358.

24. Karmazin V. V., Karmazin V. I. Magnitnye, elektricheskie i special’nye metody obogashcheniya poleznyh iskopaemyh. T. 1. Magnitnye i elektricheskie metody obogashcheniya poleznyh iskopaemyh [Magnetic, electrical and special methods for mineral processing. Vol. 1. Magnetic and electrical methods for mineral processing]. Мoscow, Gornaya Kniga, 2012, 672 p. [In Russ].

25. Doroshenko M. V., Bashlykova T. V. Tekhnologicheskie svojstva mineralov: spravochnik dlya tekhnologov [Technological properties of minerals: handbook for technologists]. Мoscow, Teploenergetik, 2007, 296 p. [In Russ].