At present, pre-splitting blasting technology is not used in the construction of bench slope in an open-pit in Yunnan, which leads to unsatisfactory slope forming effect. In order to improve the forming quality and design coincidence rate of the bench slope with small-dip in the stope, the pre-splitting blasting test was carried out for the 55° gentle slope. Using the control variable method, the field control test was carried out with the pre-splitting hole spacing, line charge density and hole diameter as variables. The test results show that it is feasible to use the pre-splitting blasting method to realize the forming of the gentle bench slope with a small-dip of 55° in the blasting area. The quality of the slope is significantly improved after blasting, and the design coincidence rate is high. When the hole spacing is 1.3 m, the hole diameter is 115 mm, and the linear charge density is 0.8 kg/m, the test area achieves the best blasting effect, and the residual hole mark rate of the blast hole is about 80%.

In order to study the dynamic response and stability of goaf group under blasting stress disturbance, based on the structural characteristics of goaf group and its interaction with surrounding rock, the dynamic response model of goaf group was constructed, the dynamic response analysis method was created, the dynamic instability criterion was put forward, and its stability was judged. An underground limestone mine was selected as the object for calculation and analysis, which was compared with the results of numerical simulation and field monitoring. The influence of different blasting frequency, span-height ratio of goaf and height-width ratio of pillar on the dynamic response of goaf group was studied. The results show that under the disturbance of blasting stress, the calculation results of dynamic response analysis method are consistent with those of numerical simulation and field monitoring. The velocity and displacement response of the goaf group are mainly concentrated in the x and y directions. The blasting frequency significantly affects the velocity and displacement response of the goaf group, and the relationship curve between the two types of peak and frequency is " single peak ". The peak velocity increases first and then decreases with the increase of the span-height ratio of goaf, the inflection points of the peak velocity curves in the x and y directions are 0.8 and 0.6, respectively. The peak displacement increases linearly with the increase of the span-height ratio of goaf, and the linear change slopes in the x and y directions are 0.926 and 0.670, respectively. The peak values of velocity and displacement increase slowly with the increase of height-width ratio of pillar, which has a weak influence on the stability of goaf group. The research results can provide a new method for the dynamic response of goaf group.

In order to solve the problem of water inrush and instability of stope caused by a large amount of fissure water in the water-rich fault fracture zone, taking the stope in the northern area of Zhongguan Iron Mine as the background, the water pressure monitoring tests was carried out. The sensitivity of stope stability to water pressure change was explored by FLAC3D, and the water pressure gradient with obvious change was obtained. Then, a numerical model of "water pressure-waterproof layer thickness" was established to explore the control effect of different water pressure values and waterproof layer thicknesses on stope stability. The stability and variation rules were analyzed with the distribution of roof stress, displacement and plastic zone as indicators, and the relationship between water pressure and waterproof layer thickness was obtained. The results show that the ore body in the northern area of Zhongguan Iron Mine is a typical water-rich deposit, and the water pressure is between 0.1 MPa and 2.0 MPa. When the water pressure is greater than 1.0 MPa, the influence of water pressure on the roof stability is significant. Based on the comprehensive analysis of the variation trends of stress, displacement and plastic zone, the following conclusions are drawn: when the water pressure is 0.1 MPa, the the waterproof layer thickness should not be less than 1.8 m; when the water pressure is 0.5 MPa, the waterproof layer thickness should not be less than 3 m; when the water pressure is 1.0 MPa, the waterproof layer thickness should not be less than 4 m; when the water pressure is 1.5 MPa, the waterproof layer thickness should not be less than 5.6 m; when the water pressure is 2.0 MPa, the waterproof layer thickness should not be less than 7.1 m. The simulation results provide theoretical support for determining the waterproof layer thickness corresponding to different water pressure values in this ore body.

To investigate the roof fracture characteristics and mine pressure distribution patterns in ultra-long working faces (with a strike length ≥ 300 m), thereby effectively guiding roof control, the 132205 ultra-long fully mechanized working face in Xiaobaodang Coal Mine was taken as the research background. Combining theoretical analysis, numerical simulation, and field measurements, a zonal fracture mechanism of "central preferential fracture-migration toward both sides" which was formed under the coupling effect of advanced mining-induced fractures and primary fractures was revealed. The evolution process involves three stages, namely fracture in the central peak zone, stress migration in the non-peak zone, and instability in the side peak zones. Based on FLAC3D numerical simulation, the influence of working face length on mine pressure manifestation was elucidated as follows. When the length increases from 250 m to 450 m, roof subsidence grows several-fold, the initial pressure step distance decreases to 75 m, and the mine pressure distribution pattern shifts from an "arch-shaped" single peak to an "M-shaped" triple peak. Field-measured data from hydraulic supports validates the reliability of the simulation results. An innovative zonal coordinated rack-moving scheme of hydraulic support regulation was proposed, improving support resistance uniformity through differentiated strategies of grouped rack-moving mode in high-stress zones and stand-alone rack-moving mode in low-stress zones, holding significant engineering value for promoting large-scale development of shallow-buried coal seams in western China.

Landslide is an extremely destructive natural disaster. Accurate assessment of the ecological restoration effect in mine landslide treatment areas is of great significance for ensuring the safety and ecological stability of the surrounding areas. Airborne Light Detection and Ranging (LiDAR) data were used to construct Digital Elevation Model, Digital Surface Model, and normalized Digital Surface Model for terrain feature extraction. Combined with visible difference vegetation index and texture information features, the Pianqiaogou landslide treatment area in Du'erping Coal Mine was selected as the study area to perform ground object information extraction and classification using support vector machine optimized by particle swarm optimization algorithm. The results show that this method has a good classification performance, with the overall classification accuracy reaching 94.12%, the Kappa coefficient 84.19% and the F₁-score 93.52%. It is superior to the other two traditional classification methods. In addition, the Shannon Diversity Index of the treatment area reaches 0.958 4, which verifies the effectiveness of the mine landslide control measures, and provides ideas for the application of LiDAR in mine landslide treatment areas.

Aiming at the problems of water-induced cracking and insufficient durability of steel fiber reinforced concrete support in the roadway of a certain iron mine in Yunnan, based on the three-factor and three-level orthogonal test design, water absorption rate and sulfate erosion resistance tests were systematically carried out, and the influence laws of water-cement ratio (0.42, 0.45, 0.47), steel fiber content (2%, 3%, 4%) and waterproofing agent content (0.10, 0.12, 0.14) on water absorption rate and sulfate erosion resistance performance were quantitatively analyzed to optimize the water durability of the materials, and the optimal proportion was applied to the actual roadway support of the certain iron mine in Yunnan for construction verification. The results show that the water absorption rate of steel fiber reinforced concrete under various optimized proportions is relatively low, and the content of waterproofing agent has the most significant effect on water absorption rate (with a range of 1.73%). When the content of waterproofing agent is 0.14, the water absorption rate decreases to 4.69%. In the sulfate erosion resistance tests, the mass loss ratios of specimens are all negative (-0.35%--0.14%), the compressive strength increases with the increase in the number of cyclic erosion times, and the content of waterproofing agent has the most significant effect on compressive strength (with a range of 22.7 MPa). Proportion 2 (with a water-cement ratio of 0.42, 3% steel fiber content and 0.14 waterproofing agent content) exhibits the best comprehensive performance, with a water absorption rate of 4.54%. Its compressive strength increases from the initial 70.6 MPa to 83.1 MPa, with an increase of 17.6%. Field application results show that after support with Proportion 2, the displacement of two sides of the roadway stabilizes at 25 mm, with no significant leakage on the surface, which verifies the feasibility of the optimized proportion.

To accurately evaluate the roof water inrush risk of deep roadways and make up for the low credibility of traditional evaluation methods caused by index redundancy and subjective weighting, a comprehensive calculation method coupling with principal component analysis (PCA) and entropy method was proposed. PCA was used to reduce the dimension of multi-source indexes to eliminate information overlap. After key principal components were extracted, the weight of each principal component was quantified. The entropy method was introduced to achieve the objective calculation of comprehensive evaluation indexes. Combined with the sample input datasets of each index, the evaluation model of coal seam roof water inrush was constructed with the logical framework of "principal component extraction-comprehensive index calculation-model comparison and verification-dynamic prevention and control". The results show that the fault water conductivity coefficient is the main controlling factor affecting the roof water inrush of the working face, and the permeability coefficient is the second most important. Based on the high fitting characteristics of the comprehensive index calculated by the PCA-entropy method and the on-site water seepage data, five categories of water-rich risk levels have been divided. It is determined that the area 518-678 m away from the open-off cut of the 1315 working face is in the extremely high-risk area, and the area 0-425 m away is in the high-risk area. According to the characteristics of roof water inrush in different areas, the technical path of "partition-based prevention and control-three-dimensional interception-drainage optimization" was proposed. The research results improve the classification and identification system of roof water inrush risk levels, and provide a new method for the safe exploitation of deep resources.

During the mining process of underground ore bodies, the collapse of goaf can disrupt the stress balance of rock strata, leading to geological disasters and endangering surface facilities. In order to improve the accuracy of surface subsidence prediction in mines without actual monitoring data during the unmined stage, as well as to ensure personnel safety and mining production, a method combining neural networks and transfer learning for underground mining surface subsidence prediction was proposed. The method combines the advantages of long-short-term memory neural networks to accurately extract time series features and deep convolutional neural networks to extract local features of data, improving the accuracy of the prediction model. According to the mining design of Zhonggangou vanadium titanium magnetite, the prediction model was used to predict the surface subsidence under different mining schedules. The results show that with the increase of ore output, the mean square error of each segment is less than 0.4.The proposed model shows a high accuracy in surface subsidence prediction under different mining schedules. This method can provide a reference for surface subsidence prediction and safety monitoring of similar mines.

Aiming at the limitations of the current debris flow source detection algorithm, a YOLOv5s-GCE model was proposed. This model introduces CBAM attention mechanism, Ghost convolution and EIOU bounding box loss function to improve its identification accuracy and efficiency. In order to verify the detection effect of YOLOv5s-GCE model, it was compared with YOLOv4 and YOLOv5s models. The results show that the average accuracy of the YOLOv5s-GCE model is 95.4%, which is 2.5 and 8.6 percentage points higher than that of the YOLOv4 and YOLOv5s models, respectively. The detection accuracy of YOLOv5s-GCE model for debris flow source is as high as 96%, and the detection effect is better. The particle flow numerical simulation method was used to study the migration law of debris flow. The simulation results show that the front end of the source body is destroyed and migrated in the initial stage, and the infiltration of water particles leads to the increase of porosity and structural instability of the source body. The mid-section of the source body is subjected to compression from the rear end and restraint from the front end, leading to a significant reduction in porosity, structural densification and the occurrence of localized bulging. In the later stage of migration, a large number of material sources accumulated at the gully mouth. The threat of debris flow to downstream construction facilities is significant, and the soil on the left side of the mid-section of the source area is the most threatening in extreme weather. The research results are of great significance to the prevention and control of slag-type debris flow.

To investigate the effect of chemical solution corrosion on the dynamic impact compression mechanical properties of sandstone, red sandstone accelerated by distilled water and HCl solution with pH of 5 and 3 were used as the research objects. Dynamic compression tests were conducted under five different impact pressures to explore the influence of chemical solution corrosion on the dynamic mechanical parameters, crushing energy consumption, and failure mode of sandstone. The corrosion process and degradation mechanism of sandstone by chemical solutions were revealed using XRD and SEM, and the variation of micro fractal dimension before and after chemical solution corrosion was quantitatively characterized by box-counting method. The results indicate that in acidic environments, muscovite and plagioclase in sandstone will transform into quartz and soft kaolinite, and the cement will be dissolved. The contact mode among particles will change, resulting in an increase in the fractal dimension and damage rate of sandstone microstructure with the increase of solution acidity. Under the action of acidic solution, the stiffness of mineral particles decreases, the structure is loose, and the mechanical properties deteriorate. Taking the strain rate of 58.06 s^-1 as an example, as the acidity of the solution increases, the peak dynamic stress decreases by 17.27%, 39.83% and 49.63%, respectively, and the dynamic peak strain increases by 13.04%, 31.30% and 38.26%, respectively. After corrosion, the macroscopic fragmentation of sandstone intensifies, the energy consumption ratio decreases, the fractal dimension increases, and the failure mode changes from tension to shear. This research system reveals the mechanism of the influence of chemical corrosion on the dynamic mechanical behavior of sandstone, providing a reference for the stability assessment of rock engineering in acidic environments.