Simulation of intermixing in ore drawing process

Authors: Tyrtigina NA

Stabilization of crude ore composition can be implemented through blending, which means averaging of product quality within a certain volume, and intermixing which allows uniform distribution of useful component in this volume. The necessary arrangements include planning, management and control of the mining process, and are mainly aimed at ore blending. On the other hand, production processes, which use machines or mine constructions (ore pass, bunkers) are mostly connected with mechanical mixing of different-quality ore flows. Accordingly, it is expedient to estimate separately the blending and intermixing capacities of ore composition stabilization with regard to their specific functions. A mine structure includes the main, district, block and other ore passes where ore flows physically intermix, and ore quality gets transformed. Deficiency of information on transformation and variability of mineral quality is attempted to be overcome using simulation. The analysis of the production data and the physical simulation results shows that the by-pass process has a chief influence on the stability of the ore flow composition if the mine flow chart lacks special mixing facilities. Intermixing in an ore chute takes place by gravity, which makes the process the least energy-consuming tool of stabilization among the other kinds of mixers. This study assumes an ore chute as a powerful mixer in the process flow chart of a mine, which can reduce ore quality fluctuation within a certain production output and is capable to stabilize ore quality. Efficiency of the mixing capacity of an ore chute is governed by the ore chute parameters and by the features of ore flow during inlet and outlet. Thus, it is required to investigate the process of uniform distribution (intermixing) of useful components during ore drawing process. This article presents an estimation model with complementary options, capable to determine probability distribution of particles in outlet ore flow based on stochastic modeling of ore drawing in an ore chute. The computeraided modeling used the mathematical apparatus of theory of random functions, with display of the data in the graphical form. The first stage is the analysis of ore flow out of the ore chute bottom, i.e. via a single opening. The computer-aided modeling determines that probability distribution of the central cell output, which governs the trajectory path of particles, depends on the ore flowability. The obtained dependence has allowed evaluating the ore flow resistance ratio with regard to the outlet ellipsoid diameter. The static tests prove that the flow resistance ratio decreases with higher ore flowability and with lager outlet ellipsoid diameter. That is, the volume of the ore outlet ellipsoid is conditioned by its area. A wider outlet allows larger contact area between different quality ore layers and enables more effective intermixing of ore. Based on the modeling results on the ore flow mixing process, it is proposed to re-design the ore chute and to create a stabilization facility within the mine flow chart in order to ensure efficient intermixing of ore flows.

Keywords: stabilization, ore flow, ore chute, bunker, intermixing process, stochastic modeling, estimation model, distribution curve, flowability ratio, outlet shape.
For citation:

Turtygina N. A. Simulation of intermixing in ore drawing process. MIAB. Mining Inf. Anal. Bull. 2021;(1):146-159. [In Russ]. DOI: 10.25018/0236-1493-2021-1-0-146-159.

Issue number: 1
Year: 2021
Page number: 146-159
ISBN: 0236-1493
UDK: 622.013.364:622.646
DOI: 10.25018/0236-1493-2021-1-0-146-159
Article receipt date: 28.01.2020
Date of review receipt: 27.04.2020
Date of the editorial board′s decision on the article′s publishing: 10.12.2020
About authors:

N. A. Turtygina, Cand. Sci. (Eng.), Assistant Professor, e-mail:, Norilsk State Industrial Institute, 663310, Norilsk, Russia.


For contacts:

1. Turtygina N. A., Okhrimenko A. V., Koval'chuk A. A. Mine planning as a management tool of mineral quality control in a mine. MIAB. Mining Inf. Anal. Bull. 2018. Special edition 17, pp. 3–11. [In Russ]. DOI: 10.25018/0236-1493-2018-5-17-3-11.

2. Laptev V. V. Research of computer-aid modeling of ore drawing process for systems of mining with caving: Review. Problemy nedropol'zovaniya. 2018, no 2, pp. 107 — 112. [In Russ]. DOI: 10.25635/2313-1586.2018.02.107.

3. Turtygina N. A., Okhrimenko A. V. Quantitative assessment of natural variability of copper ore quality in intrusive roof . MIAB. Mining Inf. Anal. Bull. 2019, no 8, pp. 146–156. [In Russ]. DOI: 10.25018/0236-1493-2019-08-0-146-156.

4. Turtygina N. A., Okhrimenko A. V. Tsilliakus K. S., Volkov N. A. True parameters of ore chute to find stabilization capacity of a mine mixer. MIAB. Mining Inf. Anal. Bull. 2019. Special edition 2, pp. 3—15. [In Russ]. DOI: 10.25018/0236-1493-2019-3-2-3-15.

5. Golik V. I., Luk'yanov V. G., Komashchenko V. I. Modeling ore quality in mining with caving. Izvestiya Tomskogo politekhnicheskogo universiteta. Inzhiniring georesursov. 2016, vol. 327, no 10, pp. 6–12. [In Russ].

6. Rayo J. D., Mercado J. M., Encina V. Simulation of block caving operation using a discrete element method (DEM). Conference Paper of Minin 2016 — 6th International Conference on Innovation in Mine Operations, Santiago, Chile.

7. Chursin S. M. Ustanovlenie usrednitel'nogo vozdeystviya rudospuskov na rudopotoki podzemnykh rudnikov [Blending effect of ore chutes on ore flows in underground mines], Candidate’s thesis, Moscow, MGI, 1992, 16 p.

8. Lomonosov G. G. Proizvodstvennye protsessy podzemnoy razrabotki rudnykh mestorozhdeniy: monografiya [Production processes in underground ore mining, monograph], Moscow, Izd-vo «Gornaya kniga», 2013, 512 p.

9. Mohamed F., Riadh B., Abderazzak S., Radouane N., Mohamed S., Ibsa Т. Distribution analysis of rock fragments size based on the digital image processing and the kuz-ram model cas of jebel medjounes quarry. Aspects in Mining & Mineral Science. 2018. Vol. 2. No 4. Pp. 325–329.

10. Kabelko S. S., Dunaev V.A., Gerasimov A. V. Computer technology of ore drawing process performance prediction in mining with caving systems. Izvestiya vysshikh uchebnykh zavedeniy. Gornyy zhurnal. 2018, no 8, pp. 54—61. [In Russ].

11. Mustafin V. I. Obosnovanie parametrov etazhnogo tortsevogo vypuska pri dvukh"yarusnom raspolozhenii burodostavochnykh vyrabotok [Validation of sublevel stoping system parameters with double-deck drilling-and-haulage drifts: Candidate of Engineering Sciences Dissertation], Candidate’s thesis, Moscow, 2015.

12. Pavlishina D. N., Shumilov P.A., Tereshchenko S. V. Ore quality control program module design. Sbornik nauchnykh trudov KF Petr GU [Collection of scientific papers of the Kola Division of the Petrozavodsk State University], Apatity, Izd-vo KF Petr GU, 2015, pp. 27—30.

13. Oggeri C., Oreste P. Underground quarrying for marble: stability assessment through modelling and monitoring. International Journal of Mining Science (IJMS). 2015. Vol. 1. No 1. Pp. 35–42.

14. Matthews T. Dilution and ore loss projections: Strategies and considerations. Mining: Navigating the Global Waters: 2015 SME Annual Conference and Expo and CMA 117th National Western Mining Conference. Denver, United States, 15–18 February 2015. Pp. 529–532.

15. Schwarz S., Richardson J. M. Modeling and simulation of mineral processing circuits using JK Sim Met and JK Sim Float. SME Annual Meeting & Exhibit (SME 2013) and CMA 115th National Western Mining Conference: Proceedings of a meeting held 24–27 February 2013, Denver, Colorado, USA. NY: Curran Associates, Inc., 2013.

16. Gornaya promyshlennost', available at:

17. Gornyy zhurnal, available at:

Подписка на рассылку

Раз в месяц Вы будете получать информацию о новом номере журнала, новых книгах издательства, а также о конференциях, форумах и других профессиональных мероприятиях.