In order to solve the unreasonable problem of coal mine safety investment structure and decision scheme，the safety investment evaluation system was established to comprehensively evaluate the decision scheme of a coal mine over the years. Firstly，based on the perspective of safety value，considering the relationship between safety function and safety output，eight evaluation indexes were selected to construct the safety investment evaluation system of coal enterprises. Secondly，entropy weight method and analytic hierarchy process (AHP) were used to determine the index weight comprehensively. Finally，the SPA-TOPSIS method was used to analyze and evaluate the 2012-2022 decision scheme of a coal mine，and the evaluation scheme was optimized and the improvement suggestions for practical problems were proposed. The results show that the coal mine enterprises should pay more attention to the investment in safety education and industrial health indicators. Coal mine enterprises should comprehensively consider the safety function needs and safety output benefits when making safety investment decisions and reasonably adjust the focus of future safety investment decision by referring to the optimal investment allocation.

In order to improve the safety and intelligence level of forklift truck，a forklift stability warning method based on multi-core parallel digital twin is proposed. First，the open-source high-precision inertial navigation sensor is used to evaluate the driver's operating habits and road smoothness，and then drive the digital twin operation. Secondly，the optimization algorithm is used to calculate the limit operating parameters that meet the stability conditions，such as the highest load and the fastest driving speed. Then，two acceleration strategies are proposed，which use the open source C language compiled solver and multi-core Central Processing Unit (CPU) in parallel，to shorten the optimization iteration time. Finally，taking a forklift truck as the test object，the accuracy of the measurement of the flight control system is verified，and the real-time performance of the digital twin stability early warning method is analyzed. The results show that the flight control system has high monitoring accuracy，the theoretical calculated values are basically consistent with the collected values，and the longitude and latitude deviation of global positioning system (GPS) is about 1 m. The digital twin program has a faster prediction speed. The digital twin compiled by the open source C language is 3 times faster than the Simulation X3.8 platform，and the parallel digital twin method is 20 times more efficient than the simulation platform.

In order to ensure the normal operation of wastewater treatment plants and prevent equipment failures，an improved FMEA risk assessment model was proposed. Firstly，the FMEA method was used to identify the failure modes of wastewater treatment plant equipment，and it was combined with PFS to portray the uncertainty assessment information. Secondly，the subjective and objective weights were calculated using the stepwise weight assessment ratio analysis (SWARA) method and the maximum deviation method，and the comprehensive weights of the three risk factors were calculated through the game theory combination weights. Thirdly，the multi-objective optimization on basis of ratio analysis (MOORA) method was used for the equipment failure mode risk ranking. Finally，taking Changchun City Z wastewater treatment plant equipment failure risk assessment as an example，the model proposed in this paper was compared with traditional FMEA，Pythagorean fuzzy technique for order preference by similarity to ideal solution (PF-TOPSIS)，and Pythagorean fuzzy VlseKriterijumska Optimizacija I Kompromisno Resenje (PF-VIKOR)，and the feasibility and effectiveness of the model were verified. The results show that the top 3 failure modes of wastewater plant equipment are that the grit extracted by the grit remover contains excessive organic matter，the diaphragm is dislodged or broken，and large foreign objects enter the pump.

To explore the influence of the lithology and cross-section shape on spalling failure properties of deep hard rock tunnels，indoor true triaxial tests on spalling failure were performed. Firstly，two types of rock samples (marble and granite) and two typical cross-section shapes (high side wall gate arch shape and horseshoe shape) samples in practical applications were selected. Then，the failure characteristics under the influence of different lithology and cross-section shapes were analyzed from the three aspects including spalling failure mode，spalling rock plate characteristics，and the characteristic stress during spalling. Finally，numerical simulation was conducted to explore the corresponding displacement and stress distribution characteristics during the development and propagation of the cracks. Furthermore，the spalling failure characteristics of deep hard rock tunnels were investigated. The results indicated that the slab peeling and opening failure phenomenon for the marble sample was more significant than the granite one in terms of spalling failure mode during the test process. Moreover，the cross-sectional contour range involved in spalling failure for the horseshoe shape sample was smaller than the high-side wall gate arch shape. Different lithologies presented different flaked rock slab shapes for different flaked rock slab characteristics. Compared with the high-side wall gate shape，the flaked rock slabs near the outer layer relevant to the curved wall arch sample were more slender. For the characteristic stress during spalling，the granite sample had a larger threshold at the beginning of the spalling and a faster rate for the evolution process of the spalling failure compared with the marble one. Furthermore，compared with the horseshoe shape sample，the characteristic stresses of the high-side wall gate arch sample were higher from the beginning of plate cracking to the occurrence of obvious plate cracking failure. The area with large displacement in the numerical simulation was mainly observed on the side wall of the hole. The farther away from the side wall，the smaller the displacement. Moreover，the major reason the spalling occurs can be attributed to the tangential stress concentration.

The aim of this study is to investigate the dispersion of aluminium powders with different SF in a 20 L spherical container. By establishing a numerical model describing the formation of a two-phase dispersion system of dust carried by a gas stream，including the equations of the gas flow and the trajectory of the dust particles，unsteady numerical simulations were carried out. The spatial distribution of dust，the turbulent kinetic energy and velocity at the center of the spherical chamber with time changes were analyzed under the conditions of SF of 0.2，0.4，0.6，0.8 and 1.0，respectively. The results show that the dispersion of airflow-carried dust inside the ball chamber can be divided into four stages，including powder intake，diffusion，stabilization and settling，and the dispersion uniformity and maximum velocity values are enhanced with the increase of SF. The bigger SF is，the closer the particle shape is to spherical，and the better the dispersion of aluminum dust is. The smaller SF is，the easier the dust will accumulate near the wall surface. When the nominal concentration is certain，SF ≤ 0.4，the peak concentration increases with the increase of SF，SF > 0.4，the peak concentration decreases with the increase of SF. The maximum value of the turbulent kinetic energy of the aluminum powder-air mixture decreases with increasing values of SF，the peak velocity of the aluminum powder particles increases with increasing values of SF.

To solve the problems of single prediction state and insufficient prediction accuracy of the traditional coal spontaneous combustion prediction model，a prediction model based on RBF neural network optimized by SSA was proposed. Firstly，the temperature programmed test was used to analyze the variation characteristics of the index gas of coal samples with temperature. The coal spontaneous combustion process was divided into slow oxidation stage (80≤t_i<120 ℃)，accelerated oxidation stage (120≤t_i<160 ℃) and intense oxidation stage (t_i≥160 ℃) with coal temperature as the node. At the same time，the grey correlation degree between the index gas and coal temperature in each stage of coal spontaneous combustion was analyzed. Secondly，the performance of Particle Swarm Optimization (PSO)，Grey Wolf Optimization (GWO) and SSA algorithm was tested by different dimension test functions. Finally，the superiority of the RBF neural network optimized by SSA algorithm to the coal spontaneous combustion prediction model was verified by using six mining area data. The results show that the grey correlation coefficients of CO/ΔO₂，CO and C₂H₄ with coal temperature are the largest in the slow oxidation stage. The grey correlation coefficient between C₂H₄/C₂H₆，CO/ΔO₂，CO₂/CO and coal temperature is the largest in the accelerated oxidation stage. The test results of three different dimensional functions show that SSA has better global search ability，stability and faster convergence speed compared with PSO and GWO. When the number of neurons is 5 and the number of iterations is 300，the prediction accuracy of the SSA-RBF neural network prediction model for the slow and accelerated oxidation stages reaches 99% and 93% respectively.

In order to prevent and control the explosion hazards of ethylene/polyethylene hybrid mixture，bicarbonate was selected as the explosion suppression powder，and the explosion suppression experiment was carried out in a 20 L spherical explosion device to explore the explosion inhibition effect and mechanism of different bicarbonate on ethylene/polyethylene hybrid mixture. The differences of explosion inhibition performance of different bicarbonate on the hybrid mixture were discussed. The results show that the hybrid mixture is more difficult to inhibit than the single-phase polyethylene. With the increase of ethylene concentration，the explosion inhibition of the hybrid mixture becomes more difficult. The bicarbonate has an inhibitory effect on the ethylene/polyethylene hybrid mixture with different concentrations，and the inhibition efficiency is affected by the concentration of ethylene and bicarbonate. Bicarbonate can inhibit the ethylene/polyethylene hybrid explosion through physicochemical reaction during the polyethylene explosion. The decomposition and endothermic properties of potassium bicarbonate and its retardation effect on polyethylene pyrolysis are better than those of sodium bicarbonate，so the inhibition effect of potassium bicarbonate on the explosion of ethylene/polyethylene hybrid mixture is better than that of sodium bicarbonate.

In order to more effectively and accurately judge the gas concentration field，temperature field，and flow field distribution in the goaf during the mining of extra thick coal seams，and thereby determine the self-ignition risk area for layered mining of extra thick coal seams，taking the 172307 working face of Lingquan mine as an example，numerical simulation technology was used to establish a mathematical model of coal spontaneous combustion in the goaf for layered mining of extra thick coal seams based on the coupling mechanism of multiple fields in the goaf. Combined with the distribution models of coal oxygen consumption rate，heat release intensity，critical oxygen concentration for spontaneous combustion，porosity and permeability，the evolution law of the spontaneous combustion risk zone for layered mining of extra thick coal seams in a stable state was obtained through the simultaneous solution. The results show that in the upper layered goaf，the high oxygen concentration area and the high-temperature area are mainly located near the stop mining line and in the upper part of the intake and return air tunnels，and the main air leakage area is located at the stop mining line. In the composite goaf，the high oxygen concentration area is mainly located on the inlet and return air sides. As it moves towards the deeper part of the goaf，the oxygen concentration shows a decreasing trend. And a local high-temperature zone resembling an ellipse appears at a certain distance from the coal mining face.

In order to solve the problem of insufficient research on the non-uniform mixed explosion characteristics of hydrogen leakage in the tunnel，the numerical simulation software Fluent was used to establish a tunnel model with the length，width and height of 60，6.46 and 5.5 m，respectively. The non-uniform mixed explosion characteristics of hydrogen at the ignition time of 75 and 100 s and at ignition positions above and behind the vehicle were studied. The results show that the hydrogen leakage volume fraction field is not uniformly distributed in the tunnel scenario. After the explosion，the pressure wave reflects from the tunnel wall and propagates to the exit at both ends of the tunnel. In the process，the intensity of the pressure wave decreases continuously. The propagation characteristics of the blast wave formed by different ignition positions are obviously different. The influence of the explosion location on explosion overpressure is greater than hydrogen volume fraction. At the same time，the overpressure of ignition behind the vehicle is generally greater than that of ignition above the vehicle. The peak pressure at the position 2 m behind the vehicle can reach about 100 kPa. The rear ignition position within 2 m will cause serious injury or even death to the human body，and personnel within 4 m of the rear ignition position will suffer different degrees of injury.

In order to prevent coal spontaneous combustion disasters under high-temperature environment and clarify the spontaneous combustion characteristics，coal samples from the 1306 working face of the VI coal seam in Barapukuria coal mine were selected. The coal samples were subjected to constant temperature treatment at 40，50，and 60 ℃ for 30 days，and pore structure analysis and thermogravimetry(TG) were performed on the raw coal samples and high-temperature pretreated coal samples to test the oxidation kinetic parameters. The results show that after high-temperature treatment，the proportion of small pores decreases while the proportion of medium pores and large pores increases. After treatment at 60 ℃，the specific surface area of the coal sample increases from 2.351 m²/g of raw coal to 3.285 m²/g，and the total pore volume increases from 0.007 88 mL/g of raw coal to 0.010 01 mL/g. In addition，compared with raw coal，the ignition temperature and burnout temperature of the coal sample significantly decreased after high-temperature treatment，and the maximum weight loss and the maximum weight loss rate increased by 6.1% and 23.3%，respectively. The calculation results of oxidation kinetics show that the activation energy and pre-exponential factor of the coal sample after high-temperature treatment are lower than those of the raw coal，indicating that the high-temperature environment significantly improves the oxidation reaction activity and increases the risk of spontaneous combustion of coal.