Application of computer models of rock mass quality and stress–strain behavior for stability assessment of mine openings

Underground mining is a key element of the economy in Russia. When working at great depths, the level of threats associated with rockburst hazards increases, which presents new challenges for technical personnel. In the Severny deep mine, roof fractures and rock falls appear because of: stress concentration induced by front and geometry of stopes; heavy fracturing in rock mass. Determination of the nature of roof fractures is a top-priority task when selecting mine roof support methods. There are different approaches to mine roof support in mining, but the required resources should be planned beforehand, which means unambiguous understanding of all necessary measures that should be undertaken to support underground excavations for the near year period of a mine operation. This article examines the tools available for solving the problem on the nature of deformation in mine openings for planning the necessary materials to ensure mine roof support, as well as the destressing drilling amount. Considering the present fund of worktime and material resources, it was decided to use the methods of prediction of changes in the stress–strain behavior of rock mass during mining at minimum resources required. The study used two models of rock mass quality and stress–strain behavior. The results revealed the stoping impact zones with high probability of rock falls, and made it possible to take into account the scale of rock mass damage using a quantitative indicator. This allows mine planning to eliminate the presence of mine personnel and equipment in underground excavations with possible stress concentrations, as well as to use resources more efficiently and to reduce the risk of emergency situations. This approach can potentially be extended to other mines, including outside Russia. The research findings can be aimed at studying influence of different factors on stability of mine workings, at development of new methods to predict and prevent emergency situations, and at improvement of the current modeling technique.