Development of numerical geomechanical models with different levels of detail using the example of the Angidrit underground mine of the Kayerkansky ore mine

Yu.Yu. Golovchenko¹ , I.S. Lepekhin², A.E. Rumyantsev¹, M.A. Sonnov³, A.V. Trofimov^1
1 Gipronickel Institute, St. Petersburg, Russian Federation
² Norilsk Support Complex LLC, Norilsk, Russian Federation
³ Fidesys LLC, Moscow, Russian Federation
Russian Mining Industry №4 / 2023 р. 79-88

Abstract: As mining conditions are getting more complex, numerical modelling is becoming one of the most promising areas to obtain data for developing efficient technological solutions. However, creation of high-quality numerical models is an extremely labour-intensive and knowledge consumptive task. Optimization of the numerical modelling process is currently highly demanded. The use of global numerical models with a high level of detail not only makes it possible to evaluate the stress-and-strain state of the rock mass over a large area, but also to qualitatively assess some local effects. Such models help to select more correctly the most hazardous areas for designing local calculation models. Thanks to the high level of detail of the simulated underground structure, the global numerical model can act as a "donor" of the initial geometry for local calculation models, and the exported stress tensor can be used as the boundary conditions, which will increase the accuracy of the local numerical simulation. This approach to numerical modelling can significantly improve the quality of numerical simulations. Although the detailed global numerical models can represent some local phenomena of the rock mass response, they should not be taken as a cure-all solution. The results obtained in a global numerical model are rather aggregated and in case of local tasks only indicate the presence of this or that phenomenon in a particular zone, but cannot describe it quantitatively. Therefore, the transition from global to local numerical models is a necessary part of the work. This paper provides an example of a complete cycle of creating a set of detailed global and local numerical models. The cycle includes all stages of development from optimization of the initial geometry to the step-by-step calculation and analysis of the obtained results. Thanks to the approach used, both qualitative and quantitative convergence was achieved with the results of in-situ observations.

Keywords: mining operations, rocks, numerical modelling, numerical geomechanical model, numerical model of an underground structure, pillars, room-and-pillar mining system

For citation: Golovchenko Yu.Yu., Lepekhin I.S., Rumyantsev A.E., Sonnov M.A., Trofimov A.V. Development of numerical geomechanical models with different levels of detail using the example of the Angidrit underground mine of the Kayerkansky ore mine. Russian Mining Industry. 2023;(4):79–88. https://doi.org/10.30686/1609-9192-2023-4-79-88

Article info

Received: 18.06.2023

Revised: 12.07.2023

Accepted: 13.07.2023

Information about the authors

Yuriy Yu. Golovchenko – Research Associate, Laboratory of Geotechnical Engineering, Gipronickel Institute, St. Petersburg, Russian Federation; ORCID: https://orcid.org/0000-0003-2980-2173; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

IliyaS. Lepekhin – Deputy Mine Director for Mining Operations, Norilsk Support Complex LLC, Norilsk, Russian Federation; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Alexandr E. Rumyantsev – Cand. Sci. (Eng.), Chief Specialist, Laboratory of Geotechnical Engineering, Gipronickel Institute, St. Petersburg, Russian Federation; https://orcid.org/0000-0002-2204-961X; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Maksim A. Sonnov – Full-fledged member of the Russian Academy of Mining Sciences, Deputy Director General for Sales, Fidesys LLC, Moscow, Russian Federation; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Andrey V. Trofimov – Cand. Sci. (Eng.), Head of Laboratory of Geotechnical Engineering, Gipronickel Institute, St. Petersburg, Russian Federation; https://orcid.org/0000-0001-7557-9801; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

References

1. Zubov V.P., Anisimov K.A. Resource-saving underground mining technology for diamond-bearing kimberlite ore under protective cushion below open pit mine bottom. Gornyi Zhurnal. 2023;(4):23–38. (In Russ.) https://doi.org/10.17580/gzh.2023.04.05

2. Cheban A.Yu. Mixed work-face narrow vein mining. Mining Informational and Analytical Bulletin. 2021;(6):145–152. (In Russ.) https://doi.org/10.25018/0236_1493_2021_6_0_145

3. Petrov A.N., Petrova L.V., Sivtseva A.I., Alekseev A.M. Mining of lower horizons at badran gold ore deposit using self-propelled equipment. Izvestiya Tulskogo gosudarstvennogo universiteta. Nauki o Zemle. 2019;(2):175–184. (In Russ.)

4. Sonnov M.A., Rumyantsev A.E., Trofimov A.V., Vilchinskiy V.B. Finite-element modeling-based geotechnological grounding of the development of mineral deposits confined to tectonic faults. Russian Mining Industry. 2018;(5):107–110. (In Russ.) https://doi.org/10.30686/1609-9192-2018-5-141-107-110

5. Khokhlov S.V.1, Vinogradov Yu.I.1, Noskov A.P.2, Bazhenova A.V. Predicting displacements of ore body boundaries in generation of blasted rock pile. Mining Informational and Analytical Bulletin. 2023;(3):40–56. (In Russ.) https://doi.org/10.25018/0236_1493_2023_3_0_40

6. Wang Y., Huang J., Wang G. Numerical analysis for mining-induced stress and plastic evolution involving influencing factors: High in situ stress, excavation rate and multilayered heterogeneity. Engineering Computations. 2022;39(8):2928–2957. https://doi.org/10.1108/EC-10-2021-0614

7. Jing L., Hudson J.A. Numerical methods in rock mechanics. International Journal of Rock Mechanics and Mining Sciences. 2002;39(4):409–427. https://doi.org/10.1016/S1365-1609(02)00065-5

8. Bobet A. Numerical methods in geomechanics. Arabian Journal for Science and Engineering. 2010;35(1B):27–48.

9. Li J., Shen C., He X., Zheng X., Yuan J. Numerical solution for circular tunnel excavated in strain-softening rock masses considering damaged zone. Scientific Reports. 2022;12:4465. https://doi.org/10.1038/s41598-022-08531-3

10. Xi P., Huo Y., Zhu D., Xing C., Wang Z. Development and application of triangulation joint network based on an FEM program (RS2). Journal of Geophysics and Engineering. 2022;19(2):245–254. https://doi.org/10.1093/jge/gxac013

11. Gospodarikov A.P., Kirkin A.P., Trofimov A.V., Kovalevsky V.N. Determination of physical and mechanical properties of rocks using anti-burst destress measures. Gornyi Zhurnal. 2023;(1):26–34. (In Russ.) https://doi.org/10.17580/gzh.2023.01.04

12. Biryuchev I.V., Makarov A.B., Usov A.A. Geomechanical model of underground mine. Part I. Creation. Gornyi Zhurnal. 2020;(1):42– 48. (In Russ.) https://doi.org/10.17580/gzh.2020.01.08

13. Rasskazov M.I., Tsoi D.I., Kryukov V.G., Potapchuk M.I., Fedotova Yu.V. Albyn gold deposit: Geological features, physical and mechanical properties. Mining Informational and Analytical Bulletin. 2021;(5-2):146–161. (In Russ.) https://doi.org/10.25018/0236_1493_2021_52_0_146

14. Marysyuk V.P., Sabyanin G.V., Trofimov A.V., Kolganov A.V. Methodology of geomechanical block modeling of rock mass in Taimyrsky Mine field. Gornyi Zhurnal. 2022;(10):39–45. (In Russ.) https://doi.org/10.17580/gzh.2022.10.06

15. Pisetsky V.B., Lapin S.E., Levin V.A., Gorbunov V.A., Chevdar S.M. On selection of a criterion to assess the risk of stability state loss by the rock mass based on seismic, aerogas and geomechanical data. In: Labour safety and production efficiency at mining operations using the underground mining method: Proceedings of the 1st International Scientific and Technical Conference, Ekaterinburg, April 6 – June 7, 2016. Ekaterinburg: Ural State Mining University; 2016, pp. 59–65. (In Russ.)

16. Dang V.K., Do N.A., Dinh V.D. Estimating the radial displacement on the tunnel boundary by rock mass classification systems. International Journal of GEOMATE. 2022;22(92):9–15. https://doi.org/10.21660/2022.92.19

17. Hoek E., Diederichs M.S. Empirical estimation of rock mass modulus. International Journal of Rock Mechanics and Mining Sciences. 2006;43(2):203–215. https://doi.org/10.1016/j.ijrmms.2005.06.005

18. Vasarhelyi B., Kovacs D. Empirical methods of calculating the mechanical parameters of the rock mass. Periodica Polytechnica Civil Engineering. 2017;61(1):39–50. https://doi.org/10.3311/PPci.10095