Micromine Rus, Moscow, Russia:

G. S. Fedotov, Head of Department for Educational Institutions and Training Guidance, Candidate of Engineering Sciences, grigoriyfedotov.s@gmail.com
B. V. Kurtsev, CEO

Research Center for Applied Geomechanics and Convergent Technologies in Mining, NUST MISIS’ College of Mining, Moscow, Russia:
A. M. Yanbekov, Project Engineer
A. R. Umarov, Project Engineer, Post-Graduate Student

In 2016 Russian Railways made a decision to reconstruct the upper structure of the track and drainageand-transport adit in Severomuysky Tunnel in order to mitigate the impacts of adverse factors and to increase the tunnel capacity. As a rule, such work goes with the creation of a 3D model of subsoil in the area of reconstruction. The area of Severomuysky Tunnel features difficult geological and geotectonic conditions. The seismically active zones, subvertical tectonic delamination of granitoid rock mass in the Baikal Mega Dome, as well as the thermal and cold groundwater complicate operation and require special control activities to be undertaken. Creation of the geomechanical model is discussed, the modeling stages are described, the source data of the modeling are given, and the calculation procedure to find geomechanical determinants for the modeling is delineated. The modeling is performed in geological and mining information system Micromine Origin & Beyond. Visualization of distribution of quantitative data on rock mass quality and real-time updating of the model when new geomechanical observations arrive allow enhancing quality of project solutions, including designs of tunnel lining and new underground openings. With the block model at hand, it is possible to identify hazardous areas in rock mass and to predict rock mass damages in three and in two dimensions. The geological and mining information systems are usable both in solid mineral mining and in construction / reconstruction of various-purpose underground structures. At the comparatively low labor cost of modeling, specialists gain an offing to improve essentially the computational accuracy and to minimize the risks associated with construction and operation of objects in difficult geotechnical conditions.

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10. Sidorov D. V., Potapchuk M. I., Sidlyar A. V. Forecasting rock burst hazard of tectonically disturbed ore massif at the deep horizons of Nikolaevskoe polymetallic deposit. Journal of Mining Institute. 2018. Vol. 234. pp. 604–611.
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18. Using the Q-system. Rock Mass classification and support design : Handbook. Revised and new edition. Oslo : NGI, 2022. 56 p.