Empress Catherine II Saint-Petersburg Mining University, Saint-Petersburg, Russia

A. P. Gospodarikov, Head of Department, Doctor of Engineering Sciences, Professor, kafmatem@spmi.ru
V. I. Kirilenko, Post-Graduate Student

Medvezhiy Ruchey LLC, Norilsk, Russia
A. S. Milkov, Chief Engineer of Zapolyarny Mine

Nornickel’s Polar Division, Norilsk, Russia
S. Yu. Shilenko, Director of Industrial Safety and Production Control Department

The system of mining with sublevel caving enjoys wide application as it provides high technical-and-economic indexes. However, in the event of the use of this system, the quality indicators of ore from geological surveying often differ from the data obtained at a concentration factory, which is conditioned by the ore loss in the back and sidewalls of a stope during ore drawing. The authors discuss determination of boundary conditions for the discrete element modeling which allows investigation of interaction between ore and host rock particles. The data for setting boundary conditions and characteristics of granular materials are critical in discrete modeling of ore flow process during drawing. The model needs a wide range of parameters of a granular material to be set: size, shape and density of particles, and coefficients of friction between particles and different components of the model. The investigation was carried out as a case-study of enclosing rock mass and ore body at the Zapolyarny Mine. The model parameters were: density, Young’s modulus and Poisson’s ratio; grain size composition; static and dynamic friction coefficients; coefficient of restitution. In-situ measurements of grain size composition provided average size of particles, oversize yield and an aggregate grading curve. The experimental particles had different weights and shapes. Verification of the results included comparison of the data obtained in laboratoryscale tests and in numerical modeling of an angle of repose. The implemented laboratory tests produced parameters required for setting properties of a test material in a computer program. The article illustrates laboratory tests and modeling process.

1. Vasileva M. A., Golik V. I., Zelentsova A. A. Methods of intensification of pipeline transportation of hydraulic mixtures when backfilling mined-out spaces. Journal of Mining Institute. 2025. Vol. 274. pp. 104–116.
2. Zubov V. P., Trofimov A. V., Kolganov A. V. Influence of ground control features on indicators of dilution in mines of the Talanakh ore province. MIAB. 2024. No. 12-1. pp. 87–106.
3. Fedorova E. R., Morgunov V. V., Pupysheva E. A. Effect of variation of internal diameter along the length of a rotary kiln on material movement. Non-ferrous Metals. 2024. No. 1. pp. 28–34.
4. Kaung P. A., Gorelkina E. I., Abdulaev E. K., Mishenina N. A. Expenditure policy of a mining company in changing geopolitical settings. Gornaya Promyshlennost. 2023. No. 3. pp. 143–153.
5. Litvinenko V. S., Petrov E. I., Vasilevskaya D. V., Yakovenko A. V., Naumov I. A., Ratnikov M. A. Assessment of the role of the state in the management of mineral resources. Journal of Mining Institute. 2023. Vol. 259. pp. 95–111.
6. Malinovsky E. G., Golovanov A. I., Akhpashev B. A. Studies of the influence of the granulometric composition of the broken ore mass on the extraction indicators with a system of forced block caving of ore by physical modeling. Vestnik Kuzbasskogo gosudarstvennogo tekhnicheskogo universiteta. 2022. No. 3(151). pp. 41–53.
7. Rozhkov A. A., Baranovsky K. V., Dyachkov P. S. Study of the influence of mininggeological and mining-technical factors on the amount of losses of enriched ore fines during the extraction of flat deposits of medium thickness. Problemy nedropolzovaniya. 2024. No. 4(43). pp. 16–29.
8. Laptev V.V. The analysis of studies on the field of the ore draw process simulation for developing systems by caving of ore and enclosing rocks. Problemy nedropolzovaniya. 2018. No. 2(17). pp. 107–112.
9. Shibaeva D. N., Vlasov B. A., Shumilov P. A., Tereshchenko S. V., Bulatov V. V. Application of numerical and physical modeling in designing of an X-ray luminescence separator intended for separation of ores containing luminescent minerals. Gornaya Promyshlennost. 2021. No. 6. pp. 82–88.
10. Laptev V. V. Numerical modelling of fragmented mined rock flow during ore drawing using the ROCKY DEM programme. Vestnik MGTU. Trudy Murmanskogo gosudarstvennogo tekhnicheskogo universiteta. 2019. Vol. 22, No. 1. pp. 149–157.
11. Shibaeva D. N., Tereshchenko S. V., Asanovich D. A., Shumilov P. A. On the need to classify rock mass fed to dry magnetic separation. Journal of Mining Institute. 2022. Vol. 256. pp. 603–612.
12. Zhukovskiy Yu. L., Korolev N. A., Malkova Ya. M. Monitoring of grinding condition in drum mills based on resulting shaft torque. Journal of Mining Institute. 2022. Vol. 256. pp. 686–700.

13. Beloglazov I. I., Ikonnikov D. A. Application of the discrete element method for modeling of rocks crushing in a jaw crusher. Izvestiya vuzov. Priborostroenie. 2016. Vol. 59, No. 9. pp. 780–786.
14. Zubkov V. P., Petrov D. N. Influence of ore draw mode on freezing losses during underground mining of permafrost deposits. Gornaya Promyshlennost. 2022. No. 2. pp. 76–80.
15. Sánchez V., Castro R. L., Palma S. Gravity flow characterization of fine granular material for Block Caving. International Journal of Rock Mechanics and Mining Sciences. 2019. Vol. 114. pp. 24–32.
16. Firouzabadi M., Esmaeili K., Rashkolia G. S., Asadi M. A discrete element modelling of gravity flow in sublevel caving considering the shape and size distribution of particles. International Journal of Mining, Reclamation and Environment. 2023. Vol. 37, Iss. 4. pp. 255–276.
17. Liu Q., Shi F., Wang X., Zhao M. Statistical estimation of blast fragmentation by applying 3D laser scanning to muck pile. Shock and Vibration. 2022. Vol. 2022. ID 3757561.
18. Jang H., Kitahara I., Kawamura Y., Endo Y., Topal E. et al. Development of 3D rock fragmentation measurement system using photogrammetry. International Journal of Mining, Reclamation and Environment. 2020. Vol. 34, Iss. 4. pp. 294–305.
19. Sanchidrián J. A., Segarra P., Ouchterlony F., Gómez S. The infuential role of powder factor vs. delay in full-scale blasting: A perspective through the fragment size-energy fan. Rock Mechanics and Rock Engineering. 2022. Vol. 55, Iss. 5. pp. 4209–4236.
20. Vinogradov Yu. I., Khokhlov S. V., Bazhenova A. V., Sokolov S. T. Methodological principles of measuring granulometric composition. Izvestiya Tulskogo gosudarstvennogo universiteta. Nauki o Zemle. 2020. No. 3. pp. 112–123.
21. Guo Q., Wang Y., Yang S., Xiang Z. A method of blasted rock image segmentation based on improved watershed algorithm. Scientific Reports. 2022. Vol. 12. DOI: 10.1038/s41598-022-11351-0
22. Rackl M., Hanley K. J. A methodical calibration procedure for discrete element models. Powder Technology. 2017. Vol. 307. pp. 73–83.
23. Quist J., Evertsson M. Framework for DEM model calibration and validation. Proceedings of the 14^th European Symposium on Comminution and Classification. Gothenburg, 2015. pp. 103–108.
24. Ketterhagen W., Wassgren C. A perspective on calibration and application of DEM models for simulation of industrial bulk powder processes. Powder Technology. 2022. Vol. 402. ID 117301.
25. Boikov A., Savelev R., Payor V., Potapov A. Universal approach for DEM parameters calibration of bulk materials. Symmetry. 2021. Vol. 13, Iss. 6. ID 1088.
26. Boikov A. V., Savel ev 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. Vol. 20. pp. 3–6.
27. Ghodki B. M., Patel M., Namdeo R., Carpenter G. Calibration of discrete element model parameters: soybeans. Computational Particle Mechanics. 201 9. Vol. 6, Iss. 1. pp. 3–10.
28. Song X., Dai F., Zhang F., Wang D., Liu Y. Calibration of DEM models for fertilizer particles based on numerical simulations and granular experiments. Computers and Electronics in Agriculture. 2023. Vol. 204. ID 107507.
29. Roessler T., Richter C., Katterfeld A., Will F. Development of a standard calibration procedure for the DEM parameters of cohesionless bulk materials—Part I: Solving the problem of ambiguous parameter combinations. Powder Technology. 2019. Vol. 343. pp. 803–812.
30. Han Y.-L., Jia F.-G., Tang Y.-R., Liu Y., Zhang Q. Influence of granular coefficient of rolling friction on accumulation characteristics. Acta Physica Sinica. 2014. Vol. 63, No. 17. ID 174501.
31. Han D.-D., Xu Y., Huang Y. -X., He B., Dai J.-W. et al. DEM parameters calibration and verification for coated maize particles. Computational Particle Mechanics. 2023. Vol. 10, Iss. 6. pp. 1931–1941.
32. Bao M., Wu W., Tian G., Qiu B. Research on discrete element parameter calibration of ore particles based on Tavares breakage model in a SAG mill. Particuology. 2025. Vol. 96. pp. 44–56.
33. Jiang C., An X., Li M., Wu Y., Gou D. et al. DEM modelling and analysis of the mixing characteristics of sphere-cylinder granular mixture in a rotating drum. Powder Technology. 2023. Vol. 426. ID 118653.
34. Hoshishima C., Ohsaki S., Nakamura H., Watano S. Parameter calibration of discrete element method modelling for cohesive and non-spherical particles of powder. Powder Technology. 2021. Vol. 386. pp. 199–208.
35. Zhu B., Liu J., Chen X., Yu J., Liu M. et al. Parameter calibration of soil in the Poyang Lake region based on discrete element method. American Journal of Biochemistry and Biotechnology. 2020. Vol. 16, No. 4. pp. 538–548.