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The Ground Penetrating Radar method is used to study a three-layered model of the surrounding rock-void-lining interface with regard to variation in the void thickness and in the electromagnetic properties of the void filler. The numerical modeling uses the method of finite differences in the time domain. The numerical modeling data are compared with the results of the physical simulation implemented using SIR-3000 GPR with the Model 52600 antenna having the working frequency of 2.6 GHz (S-band). It is found that the size of the void behind concrete lining and the electromagnetic properties of a material filling the void have influence on the accuracy of ranging to the lower boundary of the void and to the discontinuity in the form of a steel bolt located immediately behind the void in surrounding rock mass.

The article describes determination of oxidizability and spontaneous combustion of ore and rocks as a case-study of the Oktyabrsky deposit. The rate of oxidation of sulfide ore increases after watering. The authors present the studies on sensitivity of ore and enclosing rocks to spontaneous combustion, as well as on gas emission in isothermal conditions and in heating. It is found that sulfide ore, hornfels and gabbro-dolerite are sensitive to spontaneous combustion.

The article presents evaluation of preparability of iron ore from Yakovlevo deposit, Kursk Magnetic Anomaly, using magnetic, gravity and X-ray radiometric methods of coarse particle separation. The detailed study involved a material with particle size of - 100 + 25 mm, containing 25-45% Fe_total and 3-35% of Fe_magn and requiring dressing. It is found that effective separation of the initial feedstock into ore and dirt is ensured by the X-ray radiometric method of separation of coarse particles - 50 + 25 mm in size. At the analytical parameter equal to 2, the increase in the content of Fe_total in the ore product reaches 1.18 times at the loss of 5.52%.

The article describes the experimental studies on the recovery of chromite ore obtained from the Askale-Kop deposit (Erzurum/Turkey) using a laboratory-type KC-MD3 Knelson concentrator. For this purpose, the parameters of pulp feed rate, fluidization water flow rate, pulp solids ratio, bowl speed and particle size were examined as variables in the experimental studies. As a result of the experiments, the maximum Cr₂O₃ grade was obtained at 54.68% in chromite concentrate at fluidization water flow rate of 12 l/min, pulp feed rate of 1.5 l/min, pulp solids ratio of 20% and bowl speed of 800 rpm. The highest concentrate recovery value (76.85%) was obtained at fluidization water flow rate of 6 l/min, pulp feed rate of 1.5 l/min, pulp solids ratio of 20% and bowl speed of 1080 rpm.

The flotation process and magnetic separation are the most common methods for feldspar beneficiation containing approximately 0.4% Fe₂O₃ and 0.04% TiO₂. A model MIH (13) 111-5 Induced Roll dry high-intensity magnetic separator was used in this investigation to produce high-quality feldspar concentrate, and investigate the effects of magnetic field strength and roll speed on reducing coloring minerals. The best results were obtained at a magnetic field intensity of 16600 Gauss and a roller speed of 24 rpm. A feldspar concentrate containing 0.16% Fe₂O₃, 0.01% TiO₂ and 10.31% alkali minerals (K₂O + Na₂O) was obtained with a mass recovery of approximately 69.24%. As a result, the products that met the white glaze and ceramic requirements were produced.

The mixed explosive-and-reagent effect exerted on a cemented mineral mass, which simulated an ore body, by explosive charges arranged in reagent solutions was investigated. Pretreatment of the model material by explosive injection of different reagent systems leads to pre-oxidation of copper contained in the material, which stimulates its subsequent leaching. The maximal increment in copper recovery in pregnant solution reached 83% relative to the check value. For the pre-oxidation of copper contained in the model material, the mixed explosive-and-reagent treatment used: electrically activated solution sodium bicarbonate and peroxide, mixture of sodium hydroxide and peroxide, sodium hypochlorite and distilled water. The complexing agent in copper leaching was agent Jin Chan in standard and activated states. It is found that activation of solutions using electrochemically treated sodium bicarbonate before adding the complexing agent enables higher effective recovery of copper from model materials after mixed explosive-and-reagent injection preparation.

The optical polarization method with ring-shaped photoelastic sensors, digital photography of isochromatic patterns and their clarification using neural networks is developed for the stress measurement in rock mass. The case-studies of the photoelasticity application in solving various problems of elasticity and rock pressure analysis are reviewed. As a result of a lab-scale experiment, a data set of 15 000 isochromatic images is collected. The machine learning algorithm was a convolutional neural network, the Inception module. The authors recommend using downhole sensors for the continuous stress monitoring in underground mines and integrating the obtained data in a digital model with the help of IoT.

The features and trends of coal mining in the east of Russia are examined. The current and planned managerial decisions connected with coal production and supplies to competitive markets are analyzed. The coal products are ROM fuel, concentrate and middlings. The authors discuss approaches to effective mining and processing management within the chains of supplies, and to provision of the required quality of solid fuel produced and delivered to customers.

The present study analyzes the fatal accident occurrences of seventy years from 1951 to 2020 in Indian coal mines. The autoregressive integrated moving average (ARIMA) model, Brown’s double exponential smoothing method, Holt’s double exponential smoothing method, and neural network time series forecasting are used in this research to analyze fatal accidents and forecast future accident incidents. By analyzing various parameters of the applied models, the neural network model was found to be the most appropriate model for the collected data to forecast Indian coal mine accidents as it provides the least root mean squared error (RMSE) (17.62), and mean absolute error (MAE) (13.33) among all models. According to this study, the Neural Network model is the most suitable one to predict Indian coal mine fatality.

The ignition of hard coal grades DG, G, Zh, and K under the action of laser pulses (1064 nm, 120 µs, 1.3 J) was studied for the fractions of microparticles with a narrow size distribution in the range of 0.25-44 µm. The kinetic characteristics of the glow of samples from the entire size range were measured for each coal rank. Three stages of ignition are distinguished for each fraction. The duration of the first stage coincides with the duration of the laser pulse. The duration of the second takes a time interval of 10-15 ms (DG, G and Zh coal ranks) and 3-5 ms (K coal rank). The duration of the third stage is 60-80 ms (DG, G, and G coals) and 20 ms (K coal rank). It has been established that the threshold ignition energy densities (ignition thresholds) at all three stages depend non-monotonically on coal particle sizes. The minimum values of ignition thresholds at all three stages are achieved at particle sizes equal to 2.2 (for DG rank coal), 4.0 (for G rank coal), 0.7 (for Zh rank coal) and 2.0 µm (for K rank coal). Using the results of the proximate analysis of coals, the observed dependences of critical energy densities on the size of coal particles are interpreted.