Coal Mine Construction Research Articles

Influence of land use change on habitat quality: a case study of coal mining subsidence areas.

Revealing the spatiotemporal evolution characteristics and key driving processes behind the habitat quality is of great significance for the scientific management of production, living, and ecological spaces in resource-based cities, as well as for the efficient allocation of resources. Focusing on the largest coal-mining subsidence area in Jiangsu Province of China, this study examines the spatiotemporal evolution of land use intensity, morphology, and functionality across different time periods. It evaluates the habitat quality characteristics of the Pan'an Lake area by utilizing the InVEST model, spatial autocorrelation, and hotspot analysis techniques. Subsequently, by employing the GTWR model, it quantifies the influence of key factors, unveiling the spatially varying characteristics of their impact on habitat quality. The findings reveal a notable surge in construction activity within the Pan'an Lake area, indicative of pronounced human intervention. Concurrently, habitat degradation intensifies, alongside an expanding spatial heterogeneity in degradation levels. The worst habitat quality occurs during the periods of coal mining and large-scale urban construction. The escalation in land use intensity emerges as the primary catalyst for habitat quality decline in the Pan'an Lake area, with other factors exhibiting spatial variability in their effects and intensities across different stages.

Goaf Site Stability Detection in the Overlap Area of Coal Mining Subsidence and Urban Construction

The contradiction between coal mining and urban construction in coal resource-based cities is prominent, which greatly limits the sustainable development of these cities. Pan’an New City is a key mining-induced subsidence area in Xuzhou City, which presents significant challenges to the construction of the new city. Therefore, in order to ensure the safe construction of Pan’an New City, the residual deformation and stability of the goaf sites must be monitored and evaluated. Under such background, based on the measured leveling data of the mining-induced surface deformation in a coal mine near Pan’an New City, this paper first analyzed the accuracy of InSAR monitoring of surface deformation in coal mining subsidence area by SBAS-InSAR technology. Then, the SBAS-InSAR technology was used to monitor the surface subsidence rate and cumulative subsidence in the coal mining subsidence area of Pan’an New City, based on the 29 scene SAR data during Dec. 2020 and Jan. 2022. The results showed that the goaf site in the north and northwest of Pan’an New City is unstable, while the other areas are stable. Finally, according to the monitoring results, the suggestions have been put forward for the construction of Pan’an New Town on the goaf site. The research results have important theoretical and practical significance for the reuse of goaf sites in Pan’an New City and similar areas in Xuzhou.

Evaluation of risk factors affecting the safety of coal mine construction projects using an integrated DEMATEL-ISM approach

Purpose The purpose is to identify and evaluate the safety risk factors in the coal mine construction process.Design/methodology/approach The text mining technique was applied in the stage of safety risk factor identification. The association rules method was used to obtain associations with safety risk factors. Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Interpretative Structural Modeling (ISM) were utilized to evaluate safety risk factors.Findings The results show that 18 safety risk factors are divided into 6 levels. There are 12 risk transmission paths in total. Meanwhile, unsafe behavior and equipment malfunction failure are the direct causes of accidents, and inadequate management system is the basic factor that determines the safety risk status.Research limitations/implications Due to the limitation of the computational matrix workload, this article only categorizes numerous lexical items into 18 factors. Then, the workshop relied on a limited number of experts; thus, the findings may be potentially biased. Next, the accident report lacks a universal standard for compilation, and the use of text mining technique may be further optimized. Finally, since the data are all from China, subsequent cross-country studies should be considered.Social implications The results can help China coal mine project managers to have a clear understanding of safety risks, efficiently carry out risk hazard identification work and take timely measures to cut off the path of transmission with risks identified in this study. This helps reduce the economic losses of coal mining enterprises, thus improving the safety standards of the entire coal mining industry and the national standards for coal mine safety policy formulation.Originality/value Coal mine construction projects are characterized by complexity and difficulties in construction. Current research on the identification and assessment of safety risk factors in coal mine construction is insufficient. This study combines objective and systematic research approaches. The findings contribute to the safety risk management of China coal mine construction projects by providing a basis for the development of safety measures.

Performance prediction of roadheaders used in coal mines from the needle penetration index and the schmidt hammer value

Coal mine galleries and construction tunnels are commonly excavated using roadheaders. Estimating the performance of roadheaders is crucial for planning and cost estimation when planning tunnel or tunnel projects. The aim of this study is to derive generalized performance prediction models including Schmidt hammer value, needle penetration index, and volumetric joint count for roadheaders used in coal mines. The performance measurements of axial and transverse type roadheaders were carried out in six different coal mines. Schmidt hammer tests, needle penetration index tests, and of volumetric joint count measurements were also performed at the locations where the performance measurements were conducted. The extensive data were evaluated using multiple linear and nonlinear regression analysis. The developed formulas were evaluated using statistical tests. The Equations that include the Schmidt hammer value or needle penetration index value in addition to cutter head power have been shown to be unreliable. However, the equations that include Schmidt hammer value or needle penetration index value in addition to cutterhead power and volumetric joint count have been shown to be reliable. This study concludes that the developed reliable equations can be used for the performance assessment of roadheaders used in coal mines.

Spatio-temporal evolutionary analysis of surface ecological quality in Pingshuo open-cast mine area, China.

The open-pit mining area is highly affected by human activities, which aggravate soil erosion and disturb surface ecology, bringing many problems and challenges to its environmental management and restoration, which has received widespread attention. The establishment of an objective, timely and quantitative remote sensing monitoring, and evaluation system for the spatio-temporal evolution of the surface ecological environment in the open-pit mining area is of great significance for its environmental protection, management decisions, and sustainable social development. Based on the Google Earth Engine (GEE) platform, this paper uses Landsat images to construct and calculate the remote sensing ecological index (RSEI) of the Pingshuo open-cast mine area (POMA) from 1990 to 2020 and monitor and evaluate its surface ecological environment. Combined with the Theil-Sen median, Mann-Kendall test, and Hurst index, the spatio-temporal process was analyzed. The results showed that the ecological environmental quality of the mining area first decreased and then increased from 1990 to 2020. 1990-2000 was a period of serious ecological degradation, followed by improvement. The overall improvement area reached 87.03%, and the degradation was concentrated in the coal mining area. Between 1990 and 2020, the Hurst index of the mining area was 0.452, indicating that the region has a fragile ecological environment and has difficult maintaining its stability. The global Moran's I mean value of the RSEI of the study area is 0.92, which combined with Moran's scatter plot to indicate that there is a strong positive spatial correlation rather than a random distribution of its ecological environment. During the study period, the impact on the climate of the ecological environmental change of POMA was weak, and human factors such as coal mining, land reclamation, and social construction were the main driving forces for the change in ecological quality. The results of this study reveal the changing trend of surface ecology in the mining area over the past 30 years, which is helpful for understanding its impact mechanism on ecological quality and provides support for the management of the region.

Entity recognition in the field of coal mine construction safety based on a pre-training language model

PurposeSafety management plays an important part in coal mine construction. Due to complex data, the implementation of the construction safety knowledge scattered in standards poses a challenge. This paper aims to develop a knowledge extraction model to automatically and efficiently extract domain knowledge from unstructured texts.Design/methodology/approachBidirectional encoder representations from transformers (BERT)-bidirectional long short-term memory (BiLSTM)-conditional random field (CRF) method based on a pre-training language model was applied to carry out knowledge entity recognition in the field of coal mine construction safety in this paper. Firstly, 80 safety standards for coal mine construction were collected, sorted out and marked as a descriptive corpus. Then, the BERT pre-training language model was used to obtain dynamic word vectors. Finally, the BiLSTM-CRF model concluded the entity’s optimal tag sequence.FindingsAccordingly, 11,933 entities and 2,051 relationships in the standard specifications texts of this paper were identified and a language model suitable for coal mine construction safety management was proposed. The experiments showed that F1 values were all above 60% in nine types of entities such as security management. F1 value of this model was more than 60% for entity extraction. The model identified and extracted entities more accurately than conventional methods.Originality/valueThis work completed the domain knowledge query and built a Q&A platform via entities and relationships identified by the standard specifications suitable for coal mines. This paper proposed a systematic framework for texts in coal mine construction safety to improve efficiency and accuracy of domain-specific entity extraction. In addition, the pretraining language model was also introduced into the coal mine construction safety to realize dynamic entity recognition, which provides technical support and theoretical reference for the optimization of safety management platforms.

Application and characterization of new polymer dust suppression foam in coal mine and tunnel construction space

Severe dust pollution is common in tunnel, coal mine, and other construction sites. Dust suppression foam is a feasible method for dust suppression, but its single function makes it difficult to adapt to complex construction sites. Driving by reconstructing the molecular structure of ecological raw materials and strengthening the network function, a new method of SPI based gel foam dust suppression was proposed in this study. This method was realized through improving the performance of soy protein isolate (SPI) gel by glycosylation and further enhancing the fluidity and foaming performance of SPI by enzymatic hydrolysis. Afterwards, its reaction mechanism and dust suppression mechanism were analyzed. It was found that after the glycosylation of 0.4% SPI with 0.2% xanthan gum (XG) and the subsequent addition of 0.15% transglutaminase (TGase), a relatively stable double reinforcement network structure was generated. This structure was confirmed by Fourier transform infrared spectroscopy and other experiments; to be specific, its viscosity was reduced to 28.3mPa·s, and the foaming multiple was improved by 16.8% than SPI. The particle size of foam was observed to reduce to 20-60μm through a three-dimensional microscope, which is more conducive to wetting and capturing coal dust. Then, the prepared solution was compounded with 1.0% dodecyl dimethyl Amine oxide (OA-12) to develop a dust suppression gel foam and it was sprayed on the coal dust. Through experiments on the mine airflow-dust environment simulation platform, the dust suppression gel foam reached a PM10 suppression efficiency of 98.42%, and remained a total dust suppression efficiency of above 98% after 75 days. Moreover, the validity of the molecular model was confirmed by X-ray photoelectron spectroscopy. The molecular dynamics simulation showed that coal molecules with negative potential attract positively charged OA-12 molecules, and the tail group of OA-12 contacts the hydrophobic sites of the coal at an inclined angle, allowing water molecules to fully contact the coal molecules and improving the wettability; while gel molecules are adsorbed on the surface of coal molecules to play the role of bonding and filling. This research provides a theoretical support for the application of SPI based gel in the field of dust suppression, and develops an environmentally friendly and efficient feasible scheme for dust control in the construction site.

Analysis of Eco-Environmental Quality and Driving Forces in Opencast Coal Mining Area Based on GWANN Model: A Case Study in Shengli Coalfield, China

Opencast coal mine production and construction activities have a certain impact on the ecological environment, while the development and utilization of large coal bases distributed in semi-arid steppe regions may have a more direct and significant impact on the eco-environment. Therefore, in-depth studies of the ecological impacts of human activities and natural environmental elements in opencast coal mines in typical semi-arid steppe regions and analyses of their driving forces are of great significance for protecting and restoring regional fragile steppe ecosystems. In this paper, the mining area southwest of the Shengli coalfield, a typical ore concentration area in eastern Inner Mongolia, was selected as the research object. Its remote sensing ecological index (RSEI) was calculated using the Google Earth Engine (GEE) platform to analyze the eco-environmental quality in the mining area and its surrounding 2 km from 2005 to 2021. The geographically weighted artificial neural network model (GWANN) was combined with the actual situation of mining activity and ecological restoration to discuss the driving factors of eco-environmental quality change in the study area. The results showed that: (1) the proportion of the study area with excellent and good eco-environmental quality increased from 20.96% to 23.93% from 2005 to 2021, and the proportions of areas with other quality grades fluctuated strongly. (2) The change in eco-environmental quality in the interior of the mining area was closely related to the reclamation of dump sites and migration of the mining area. (3) The maximum contribution rate of the mining activity factor to the external eco-environmental quality of the mining area reached 43.33%, with an annual average contribution rate of 34.48%; as the distance from the mining area increased, its contribution gradually decreased. This quantitative analysis of the driving forces of RSEI change in the mining area will complement future work in ecological evaluations of mining areas while also improving the practicality of ecological evaluation at the mining scale, thereby further helping the ecological management of mining areas.

Adaptive Modification of TBM Tunneling in Coal Mine Roadway and Disaster Control Technology for Complex Geological Conditions

Many mines have introduced the tunnel boring machine (TBM) to improve the efficiency of rock tunneling because of its high propulsion capacity, safe working space, and intelligent equipment. In contrast, the operating environment of coal mines is often under complex geological conditions such as high ground stress, large depth of burial, high temperature, water damage, and large construction angles, making it difficult to apply traditional TBMs in coal mines. Taking the TBM of Gaojiapu Coal Mine of Zhengtong Coal Industry as an example, this paper introduces the coal mine adaptability transformation and construction technology optimization of the equipment, optimizes the design of the roadheader department of the equipment, increases the support operation space and reduces the empty roof distance, shortens the length of the whole machine and transforms the walking structure to enhance its maneuverability and convenience, and applies the monorail crane to the auxiliary transportation system of TBM. This paper proposes the theory of TBM tunneling disaster control in complex geology, research and discussion on TBM jamming, impact pressure, cooling prevention and control, and water damage in complex geological conditions. The results obtained were applied at the Zhengtong Coal Industry in engineering practice, resulting in an average monthly progress of more than 200 m, which is more than three times more efficient than full rock heaving, and also reduces the work intensity of tunneling personnel and promotes the development of coal mining. The final part of the article looks at the future application of TBMs in coal mining.

An Impacting Factors Analysis of Unsafe Acts in Coal Mine Gas Explosion Accidents Based on HFACS-ISM-BN

With the development of intelligent coal mine construction, China’s coal production safety has been greatly improved, but coal mine gas explosion accidents still cannot be completely avoided and the unsafe acts of miners are an important cause of the accidents. Therefore, this study firstly collected 100 coal mine gas explosion cases in China, improved the framework of human factors analysis and classification system (HFACS) and used it to identify the causes of miners’ unsafe acts in detail. A hierarchy of the impacting factors is established. Then, combining with the interpretive structural model (ISM), the correlation between the impacting factors among different levels, especially among non-adjacent levels, is qualitatively analyzed through expert judgment. Then, the correlation among the contributing factors was quantitatively tested by chi-square test and odds ratio (OR) analysis. On this basis, a Bayesian network (BN) is constructed for the impacting factors of miners’ unsafe acts. The results show that the probability of coal mine gas explosion accident is 20% and 52%, respectively. Among the leading factors, the government’s insufficient crackdown on illegal activities had the greatest impact on miners’ violations, with a sensitive value of 13.2%. This study can provide reference for evaluating the unsafe acts of miners in coal mine gas explosion accidents by the probabilistic method.

A novel probability integral method segmental modified model for subsidence prediction applicable to thick loose layer mining areas.

In response to the problem that the actual extent of coal mining impacts on the surface in thick loose layer mines significantly exceeds the theoretical predictions, based on the literature study, the form of influence of thick loose layer on the predicted parameters of the probability integral method is summarized and analyzed; taking into account the influence of the subsidence coefficient, the sine modification formula of the major influence radius and the logistic modification formula of the subsidence coefficient are established, respectively, and based on the characteristics of the major influence radius, a new subsidence basin demarcation point is proposed and a novel probability integral method segmental parameter modified prediction model is constructed. The simulated experiment and real data experiment results prove that the constructed probability integral method segmented parameter modified model can both reduce the convergence of surface subsidence basin edge better and take into account the predicted accuracy inside the subsidence basin. The research achievements provide scientific data support for disaster warning, pollution management, ecological restoration, and coordination between coal mining and surface city construction in thick loose layer mining areas.

Game Analysis of the Influence of the Miner under Carbon Emotion on the Intelligent Development Strategies of the SMEE in Coal Mines

The intelligent development of coal mines is a crucial way to achieve the safe, efficient, green, and low-carbon transformation of the coal industry and to reach the “double carbon” target, which is related to the life and health of miners, the stable development of enterprises and the national energy reform. As directly affected subjects, the cooperative attitudes of miners in different emotional states have a significant impact on the smooth implementation of intelligent coal mine renovation projects. Hence, we combined the RDEU theory and game theory, constructed a three-party evolutionary game model of the small and medium-sized energy enterprises (SMEE), the government, and the miner, considered the influence of the strategies made by the miner on the equilibrium strategy choices of other game subjects in the intelligent coal mine construction under the rational and irrational emotional states of the miner, and finally used MATLAB 2021 to simulate and analyze the impact of the evolution of the gaming system from 3 key elements: initial participation rate, construction costs, and government support. The study found the following: (1) The government will insist on actively promoting intelligent coal mine construction regardless of the miner’s emotional state. (2) Both moderate pessimism and optimism will, to a certain extent, give a positive impetus to the development of intelligent coal mine construction. (3) The miner’s emotions have a greater impact on SMEE than on the government’s strategic behavior. (4) Excessive construction costs or low government support will make SMEE may reduce the enthusiasm of SMEE to carry out an intelligent construction of coal mines. Accordingly, corresponding suggestions and countermeasures are put forward, aiming to provide targeted and practical ideas for the efficient construction of intelligent coal mines in China, thereby accelerating the green and low-carbon transformation of energy.

Evaluation Model Research of Coal Mine Intelligent Construction Based on FDEMATEL-ANP

To improve intelligent construction standard systems in coal mines, we must promote the high-quality development of the coal mining industry. The current intelligent construction of coal mines is inefficient. Considering the complexity and diversity of coal mine intelligent construction index factors, this paper proposes an intelligent coal mine construction evaluation model that integrates the fuzzy decision-making trial and evaluation laboratory (FDEMATEL) and the analytical network process (ANP). Firstly, the evaluation index system is established based on the intelligent construction of coal mines. Secondly, the FDEMATEL is applied to deal with the fuzziness in the evaluation process and determine the influence relationship between the evaluation indexes of coal mine intelligent construction to draw the ANP network structure diagram. Finally, super decision software is used to calculate the weight of coal mine intelligent construction evaluation indexes, and then obtain the combination weight and correlation degree of each evaluation index. By applying the evaluation model to conduct a comprehensive evaluation of coal mine intelligent construction, the results show that there is a significant correlation between the indexes affecting the intelligent construction of coal mines. Basic platform intelligence and safety monitoring intelligence are the two most important aspects of intelligent coal mine construction. Database construction, mobile internet construction, big data support, and model algorithm support are the key indexes affecting the intelligent construction of coal mines.

Research on Coal Mine Building Compliance Inspection System Based on Accident Causation and BIM in China

Coal mine construction projects have high risks, and non-compliant designs generated in the design stage will have adverse effects on subsequent construction and production stages. Therefore, it is of great importance to conduct effective preconstruction compliance inspections on coal mine construction designs. To make the compliance check of coal mine building design more rapid and effective, and to reduce the risks arising from the design phase, this study built a compliance inspection system for coal mine building design from the causes of coal mine accidents, using the Word2Vec word similarity calculation method and BIM platform secondary development technology. The system was tested and was found to be able to detect a 92.82% non-compliant component rate where the correct inspection rate was 97.68%. In addition, the inspection time for a single component was only 0.23 s. The construction of the compliance inspection system based on accident causes has changed the extensive inspection mode in the traditional manual model inspection, and the inspection no longer depends on the experience of inspectors, thus improving the efficiency and accuracy of coal mine building model inspection. The inspection focuses on the building elements with high risks, which achieves the purpose of risk control in the design stage.

Analysis of Vegetation Coverage Evolution and Degradation under Coal Mine Construction in Permafrost Region

The ecological environment in permafrost regions is very sensitive to climate change and human activities. The effects of coal mining on the vegetation in permafrost regions have been poorly studied. Herein, on the basis of a field survey in the Juhugen mining area of Qilian Mountain, China, we investigated and quantified the influence of open-pit coal mining on vegetation coverage degradation in permafrost areas. According to the NDVI and field survey, the vegetation coverage was divided into five levels from low to high in the Arc GIS platform. Compared with the area not affected by coal mining, vegetation degradation was significant in the coal-mining-affected area, especially in the high-vegetation-coverage area. The vegetation coverage in Level 5 decreased from 51.99% to 21.35%. According to the conversion matrix, the transfer-out area in high coverage was larger, while the transfer-in area in low vegetation coverage was larger. The transfer-out area of five levels was significant in levels 2–5, accounting for 36.1% to 62.8% of the total area. The transfer-in area of five levels was significant in levels 1–4, accounting for 55.2% to 75.0% of the total area. Moreover, the ground surface temperature and water change were monitored in the vegetation degradation area. The results showed that the above degradation was related to an increase in the ground surface temperature and a decrease in the ground surface moisture.

Mine Intelligent Receiver: MIMO-OFDM Intelligent Receiver for Mine Information Recovery

With the advancement of an intellectual and numerical society, the coal mining industry has also begun to change to intelligence. As an important aspect of intelligent coal mine construction, coal mine communication has put forward more stringent standards for communication quality. For the complex communication environment in mines, the transmission of communication signals is always damaged by various noises and interferences, resulting in serious distortion of the communication signals received at the receiving end. Therefore, the use of traditional receivers for information recovery has the problem of high bit error rate (BER), which cannot meet the standard of intelligent coal mine construction. Based on this, the aim of this research is to combine convolutional neural networks (CNN) and multi-input multi-output orthogonal frequency division multiplexing (MIMO-OFDM) communication systems to design an intelligent receiver model for complex mine communication systems. At the receiver side, CNNs are used to take the place of all the information processing processes. First, features are extracted from the received IQ signal by the convolutional neural network, and then the original information bit is recovered using a multi-label classifier to finally realize end-to-end information restoration. The experimental results show that the intelligent receiver model designed in this research has more accurate information recovery capability in the complex mine channel environment compared with the traditional receiver. In addition, they also verify that the intelligent receiver can still recover information effectively when the traditional receiver cannot recover information properly in the case of partial loss of received data.

Safety Technology Risks and Countermeasures in the Intelligent Construction of Coal Mines

At present, China’s intelligent coal mine construction is still in the primary development stage. The integrated development of a new generation of information and communication technology and the coal industry is accelerating, and this industry’s intelligent green transformation and upgrading is being promoted. With the continuous acceleration of China’s intelligent coal mine construction and the continuous improvement in the degree of coal mine intelligence, system compatibility, information acquisition, and intelligent research have raised awareness of new mining safety risks. Based on the analysis of the process of China’s intelligent construction, this paper describes the safety management and control risks and the technical challenges faced by China’s intelligent coal mine construction in terms of norms and standards, data acquisition, subsystem and terminal sensors, multisystem integration, safety risk management, and control ability. It is important to make full use of the collaborative advantages of intelligent scientific and technological coal mine resources. Technological innovation and intelligent equipment safety access verification need to be supported, so as to promote the intelligent and high-quality development of coal mines.

Macro-Micro Study on Mechanical Properties of Frozen Fine Sandstone Based on DEM Mathematical Model

The study of freezing rock mechanical properties is getting more and more urgent because of coal mine construction in western China. Particle discrete element method (DEM) can describe discontinuous medium problem mathematically. In order to reveal the mechanical failure mechanism of frozen fine sandstone, the uniaxial compressive strength test of frozen fine sandstone was carried out, and then, DEM was used to simulate the uniaxial test of frozen fine sandstone. Furthermore, the nuclear magnetic resonance (NMR) technology was used to obtain pore distribution of the freezing sandstone. Finally, the results of NMR test and discrete element simulation were combined to reveal the microscopic mechanism of mechanical change in freezing fine sandstone. The DEM results show that the strength of frozen fine sandstone increases with the decrease of temperature. With the decrease of temperatures, strain softening occurs in frozen sandstone, which indicates that the discrete element simulation results are in good agreement with the uniaxial test results. Therefore, DEM can be used to simulate the mechanical behavior of frozen fine sandstone. At the same time, the DEM results also indicate that the formation and development of the shear band are the precursor of the failure of the sample. Furthermore, the NMR test confirms that temperature has a great impact on the pore distribution of sandstone. With the decrease of temperature, the pore ice content increases greatly, which induces a great decrease in NMR porosity and a vast decrease in the proportion of large and medium pores in all pores. Meanwhile, with the growth of the cohesion induced by increasing ice content, the uniaxial compressive strength increases macroscopically.

Risk Assessment of Water Inrush in Coal Mine through Fault Based on Forchheimer and Non-Darcy Flows

Abstract Fault water inrush accident in coal mine construction is a serious hydrogeological disaster, which seriously endangers the safe operation of underground engineering. In the process of mining coal resources in Western China, a large number of serious mine water inrush accidents have occurred. Based on the investigation of geological conditions of fault in the Pingdingshan coal mine, the coupling model of the Darcy laminar flow and Brinkman flow is used to analyze the water inrush mechanism of a fault. On this basis, considering the higher permeability and water inrush rate, the Brinkman flow may not be used to simulate the nonlinear flow mechanism at the fault. Two improved models, the Brinkman equation and Forchheimer equation are used to analyze the mechanism of water inrush. Based on the two-dimensional finite element method, the process of water inrush into the water inrush zone is analyzed. The pressure and velocity nephogram under different conditions and the evolution characteristics of non-Darcy effect influence coefficient of fault water inrush are analyzed through parameter study. Based on the different permeability variation coefficients ξ (the ratio of fault permeability kF to aquifer constant permeability kA) and different fluid flow field changes, the Fletcher number and flow rate are compared with the theoretical data.

Research on risk management and prevention and control system of major disasters in coal mine based on fish-bone diagram and STAMP/STPA model

Fishbone diagram and STAMP/STPA model is a problem of control safety from the perspective of system theory, caused by the lack of sufficient control and safety-related constraints. There is a certain relationship between the model and coal mine construction projects. Based on the introduction of the basic concepts of the fishbone diagram and the STAMP /STPA model, this paper combines the construction of coal mine projects in China with frequent accidents, and based on the fishbone diagram model, establishes a coal mine stamping accident cause model. At the same time, the empirical analysis of typical rock burst accidents is carried out, and the starting point of the analysis is the theoretical point of view caused by system accidents. According to the fishbone diagram and STAMP /STPA model, the accident process is analyzed, the cause of the accident is analyzed, the accident disaster is described, and the safety constraints and fault behaviors are identified. Finally, the basic causes of the accident are analyzed and compared. The results show that the fishbone diagram and the STAMP /STPA model can be well used in the risk management of major disasters in coal mines. Through the safety control structure of the risk control model, the constraints and failure behaviors of each control level can be effectively identified. According to the interaction and feedback at all levels, the cause of the accident can be analyzed and obtained, which is of great significance for preventing and controlling major disasters in coal mines. <br/>