In the process of hot dry rock mining in enhanced geothermal system, high temperature and cyclic cooling will lead to damage the thermal reservoir rock mass, change its physical and mechanical properties as well as microstructure, and affect the permeability of rock mass and mining efficiency. The granite samples after high temperature treatment at 400 ℃ were subjected to cyclic cooling treatment by different cooling methods. The shear permeability tests were carried out under different normal stresses. The shear fracture surface of granite was analyzed by three-dimensional morphology and scanning electron microscopy. The results show that the shear strength and shear displacement of granite increase with the increase of normal stress. The shear strength decreases with the increase of cyclic cooling times, and the shear strength of water-cooled samples decreases more obviously. The cohesive force decreases with the increase of cyclic cooling times, and the internal friction angle does not change significantly. The initial permeability decreases with the increase of normal stress, and the initial permeability of water-cooled samples is 1-2 orders of magnitude higher than that of natural cooling samples. The shear displacement corresponding to the minimum permeability increases firstly and then decreases with the increase of cyclic cooling times, and increases with the increase of normal stress. With the increase of cyclic cooling times, the intergranular cracks of the natural cooling sample increase, the width of the transgranular cracks increases. The secondary cracks of the water-cooled sample increase and crystal fracture occurs. The research results can provide theoretical basis and technical support for hot dry rock mining.

In order to investigate the crushing properties and energy conversion law of magnetite ore under impact load, taking magnetite ore with different iron-silicon ratios as the research object, the impact crushing test on magnetite ore with different iron-silicon ratios was carried out using split Hopkinson pressure bar to analyze the destructive deformation characteristics, compressive strength and energy conversion law of magnetite ore under different incident stresses, and to reveal the macro-micro crushing mechanism by combining with scanning electron microscope technology. The results show that under the impact load, the stress-strain curves of magnetite ore with different iron-silicon ratios do not have a compression-density phase, and the elasticity modulus, peak stress, and dynamic compressive strength all decrease with the increase of the iron-silicon ratio, and the dissipation energies of the three iron-silicon ratios of magnetite ore increase with the increase of the iron-silicon ratio and the incident energy. With the increase of incident stress, the diameter of the ore fragments is decreasing, the intergranular cracks and transgranular cracks in magnetite ore are increasing, and the width and length of cracks increase with the increase of iron-silicon ratio. When the incident stress is the same, the ore fragments with a large iron-silicon ratio are smaller than those with a small iron-silicon ratio. Therefore, in the actual production of mines, magnetic iron with different iron-silicon ratio can be crushed in batches, which can improve the energy utilisation to a certain extent.

To effectively ensure the long-term stability of the extension section of the auxiliary inclined shaft in a mine of northern Shaanxi, ABAQUS software was used to analyze the influence of parameters such as thread spacing, anchorage length and borehole diameter on the bearing performance of the bolt, and reasonable anchorage parameters were selected. FLAC3D software was used to simulate the bolt support schemes of three kinds of spacing, and the optimal bolt spacing was determined by the displacement and plastic zone distribution. On this basis, field tests and surrounding rock deformation monitoring were carried out. The results show that the maximum tensile force of the bolt under 10 mm thread spacing is only 7.9 kN different from that under 8 mm thread spacing. Considering the production cost, the thread spacing of the bolt is determined to be 10 mm. The maximum anchorage force of the bolt increases with the increase of the anchorage length and the borehole diameter. After exceeding the critical value, the anchorage length and the borehole diameter have little effect on the anchorage force. Finally, the reasonable anchorage length is 800 mm and the borehole diameter is 28 mm. The control effect of surrounding rock with bolt support spacing of 1 200 mm and 1 000 mm is not much different. In order to improve the construction efficiency, the bolt spacing is determined to be 1 200 mm. The field practice shows that after using the optimized anchorage and support parameters, the average anchorage force of the bolt is greater than 150 kN, and the surface deformation of the surrounding rock is less than 25 mm, which can ensure the stability of the roadway and verify the rationality of the anchorage and support parameters.

To explore the acid corrosion resistance of zinc-infiltrated anchor bolt, the corrosion characteristics and mechanical properties of zinc-infiltrated anchor bolt in acidic environment were studied. Firstly, the immersion corrosion tests on ordinary anchor bolts and zinc-infiltrated anchor bolts were carried out, the corrosion kinetic model of zinc-infiltrated anchor bolt was constructed, and the deterioration law of mechanical properties and corrosion failure mechanism of zinc-infiltrated anchor bolt were analyzed. Secondly, the influence of anchor bolt corrosion degradation on the stability of roadway surrounding rocks was analyzed by Abaqus numerical simulation. Finally, the acid corrosion resistance of the zinc-infiltrated anchor bolt was tested by engineering application. The results show that under the same corrosion conditions, the acid corrosion resistance of zinc-infiltrated anchor bolt is significantly better than that of ordinary anchor bolt, and the stability of roadway surrounding rocks supported by zinc-infiltrated anchor bolt is significantly higher than that of ordinary anchor bolt supporting roadway. In the acidic environment, the ordinary anchor bolt is characterized by accelerated corrosion, and the zinc-infiltrated anchor bolt is characterized by uniform corrosion. After corrosion for 100 days, the yield strength, tensile strength and elongation rate of ordinary anchor bolt decrease by 6.50%, 6.37% and 15.85% respectively, and the tensile fracture form changes from ductile fracture to ductile-brittle mixed fracture. The yield strength, tensile strength and elongation rate of the zinc-infiltrated anchor bolt are decreased by 2.85%, 1.45% and 7.97% respectively, and the tensile fracture form is still ductile fracture. After the occurrence of corrosion, the displacement of the roof and two sides of the roadway supported by ordinary anchor bolts is increased by 50.07% and 52.50% respectively, and the stress is increased by 36.85% and 27.41% respectively. The displacement of roof and two sides of roadway supported by zinc-infiltration anchor bolts is increased by 21.07% and 22.06% respectively, and the stress is increased by 16.37% and 20.54% respectively. The results of engineering application show that the use of zinc-infiltration anchor bolt for roadway support can effectively prolong the life of anchorage support and ensure the safety of roadway support.

Through relevant calculation, the effectiveness of the design measures of a tailings pond was verified. Based on the GEO-SLOPE numerical simulation, the seepage and stability of the tailings pond under different working conditions were comprehensively evaluated. The results show that under the flood control standard of once in five hundred years, the discharge capacity of the flood interception ditch on east and west sides of the tailings pond and the discharge capacity of the spillway in the tailings pond area can meet the requirements. Through seepage calculation and analysis, the effectiveness of seepage control measures of tailings pond is verified. HDPE geomembrane and drainage system have good anti-seepage effect. Under the calculation of three working conditions, the anti-sliding stability of the downstream slope of the tailings pond can meet the design standards. The suggestion of arranging manual monitoring and on-line monitoring facilities is put forward to realize the real-time monitoring of dam of tailings pond and flood discharge situation. The research results can provide a technical reference for the design, construction and management of tailings pond.

The Tianjingshan mining area is a limestone quarrying region for construction purposes in the typical arid areas of northwest China. Due to severe environmental damage in this mining area, natural revegetation is no longer possible, and there is an urgent need for restoration and management. In light of this, from the overall perspective of the mine's eco-geological environmental system, research was conducted on the eco-geological environment of the mining area using the analytic hierarchy process (AHP) and fuzzy comprehensive evaluation (FCE) methods. 20 evaluation factors were selected from both ecological and geological aspects. An eco-geological environmental evaluation system was constructed that is consistent with the characteristics of typical arid areas and oriented towards mine ecology restoration. This system aims to quantitatively and accurately determine the quality levels of the eco-geological environment of the mining area and match appropriate restoration and management models for corresponding levels. Based on the evaluation result that the eco-geological environment quality level of this mining area was poor (Level Ⅲ), targeted restoration and management mode of the mining area were carried out using combined methods of geological disaster risk elimination, soil reconstruction, vegetation reconstruction, and manual maintenance. Secondary revegetation of the mine relic site was ultimately achieved. The results show that the evaluation system can provide a relatively objective evaluation of the eco-geological environment of limestone mines in arid areas and the proposed restoration and management modes have good restoration and management effects, which can be replicated and promoted for application in local and similar arid and semi-arid areas for the restoration and management of mine relic sites.

Mining activities will cause contamination to the mining area and the surrounding soil. Reasonable layout of sampling points is very important for mastering the soil environmental conditions and using remote sensing to invert the spatial pattern of soil contamination. Taking an iron mine area in Luanzhou and the surrounding area affected by mining activities as the sampling area, according to the principle of zoning control, the study area was divided into mining activities directly affected area and mining activities indirectly affected area. The classical statistical analysis method was used to calculate the reasonable sampling number and layout the sampling grid. Based on landscape diversity index and weighted average method, the layout scheme of soil heavy metal monitoring sampling points was designed. The results show that 215 sampling points are calculated by reasonable sampling number in different precision partitions. Among them, 34 grids are selected by landscape diversity index in mining activities directly affected area, and a total of 196 sampling points are allocated. The mining activities indirectly affected area uses the weighted average method to allocate 19 sampling points through the area of land-use type. After different precision, different methods to determine the distribution of forest land sampling number 39, farmland sampling number 95, bare land sampling number 20, river beach sampling number 16, tailings and mining area stope sampling number 45. The sampling scheme is based on remote sensing images, combined with the geographical location of the study area and the distribution characteristics of land-use types, taking into account the actual situation of sampling costs, which helps to reduce the sampling workload. There may be uncertain factors such as mining activities, topography and hydrology in the actual sampling work, so the sampling scheme needs to be adjusted in combination with the on-site situation.

Due to factors such as high pressure, water depth, and complex geological formations, the difficulty and complexity of ocean exploration are much higher than those on land, which puts high demands on the quality and performance of drill bits, and even requires customized production according to special needs. In order to provide customized drill bits in time, 3D printing technology has been innovatively applied to the production process of ocean exploration drill bits. Using spherical tungsten carbide (WC), cobalt (Co) powder, and diamond particles as raw materials, a method of selective laser melting (SLM) printing the working layer of drill bits has been proposed. By testing the density and hardness of printed samples, the printing parameters were optimized. The results show that the bulk density of printed WC-20Co-diamond stone can reach up to 13.45 g/cm³, and the hardness can reach 1 455 HV. Under the conditions of laser power of 220 W and scanning speed of 400 mm/s, high-quality molding can be achieved. The final prepared tungsten carbide cobalt based diamond drill bit sample has a good bonding between the hard alloy and the steel matrix interface. The production mode of drill bits based on 3D printing can significantly shorten the manufacturing time, produce drill bits that are suitable for various extreme environments and complex rock formations on the seabed, and timely meet the needs of printing drill bits on ocean drilling ships.

In order to improve the accuracy of slope stability prediction, a slope stability prediction model based on multi strategy improved cuckoo search algorithm (ICS) optimized Elman neural network was proposed. Firstly, the population was initialized using Sinusoidal chaos, and strategies such as dynamic step size control and 1% step discretization of discovery probability were introduced to improve the slow convergence speed and poor accuracy of the cuckoo search algorithm. Simulation results on 7 benchmark functions show that compared with the CS algorithm, the optimization ability and convergence speed of the ICS algorithm are significantly improved. Then, the ICS algorithm was used to optimize the weights and thresholds of the Elman neural network, and the optimal slope stability prediction model was constructed. The results show that the relative error range of the ICS-Elman model for predicting the safety factor of slope stability is –2.81%−6.98%, with root mean square error and mean absolute error of 0.275 0 and 0.342 2, respectively. Compared with the Elman and CS-Elman models, the ICS-Elman model has better stability and accuracy. Compared with the CPSO-BP neural network, the ICS-Elman neural network has a relative error range of –1.57%−1.25% in predicting values, indicating better prediction accuracy.

In mine production, the roof fall accident of working face is directly related to the hydraulic support. According to this theory, a prediction model based on multi-source data fusion was proposed to predict the load of hydraulic support. By studying the theory of pressure deformation characteristics of coal seam roof, the composition and working principle of hydraulic support, the bearing theory and the influence of working condition on hydraulic support, the influencing factors of load change were analyzed, and the data of key stress components were collected. The K-means clustering algorithm was used to cluster the characteristics of the data, and the load was classified and predicted. The whale optimization algorithm (WOA) was used to optimize the long short-term memory network (LSTM) and the deep belief neural network (DBN) respectively, and the WOA-LSTM series prediction model and the WOA-DBN series prediction model were established. The results are as follows. Firstly, the mean absolute error is reduced by 0.228 7, 0.206 4 and 0.067 7 respectively in the prediction of the front column load of 20^# hydraulic support by WOA-DBN model. The root mean square error is reduced by 0.212 9, 0.195 3 and 0.072 5, respectively. Secondly, in the prediction of the rear column load of 20^# hydraulic support by WOA-DBN model, the mean absolute error is reduced by 0.303 1, 0.244 6 and 0.205 4 respectively. The root mean square error is reduced by 0.291 9, 0.246 4 and 0.238 9, respectively. It can be seen that the WOA-DBN series prediction model is more suitable for load prediction and has higher accuracy.