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Coal is the principal energy of China, and the coal industry is an important basic industry related to the energy security. For a long time, the underground coal resources mining in China has always been based on the longwall 121 mining method. This mining system has many problems such as waste of coal resources, high rate of entry excavation and concentrated stress of coal pillars. In order to solve the three bottlenecks and prominent problems of “safety, mining cost and coal recovery rate” existing in the current mining system, we established a mining engineering model based on the mining damage invariant equation, analyzed the mechanical principle of automagical entry formation without coal pillars. On this basis, the key technologies of 110 and N00 mining method, such as directional presplitting and pressure relief of roof, NPR bolt/cable support are developed. The technical objective of “being able to control the roof, cut off the roof, make the roof easy to collapse and protect the entry rib” has been achieved. The 110 mining method of automagical entry formation without coal pillars and the N00 mining method at different development stages have been formed. The 110 mining method unifies the two sets of processes of coal mining and excavation initially, so that each coal mining face can dig one less mining entry, and no pillar mining is realized. The N00 mining method is based on the 110 mining method, which completely unifies the two processes of coal mining and excavation. The mining pressure is used to automatically form the roadway, thus eliminating the excavation of roadways and thoroughly eliminating the long-standing problem of strained relations of mining and excavation. The field practice shows that the 110 mining method cuts off the stress transmission between the roof of the goaf and the roof of the entry. The mine pressure and self balance of the surrounding rock of the retained entry is realized by using the crushing and swelling property of the collapsed gangue. The N00 mining method innovates the original mining technology, changes the layout of the traditional mining system, and realizes no entry digging and automatic entry formation in the whole mining area.

Gob‐side entry formation by roof cutting is a new technology for no pillar coal mining, which can maximize coal resources and reduce roadway drivage ratio. However, the mechanical behavior of the formed entry is complex while it is crucial to ensure the stability of the entry for mining safety. This paper proposed a machine learning‐based method for predicting the stability of the formed entry, which combined artificial neural network (ANN) with particle swarm optimization (PSO) algorithm or genetic optimization (GO) algorithm. The data set from 75 coal mining faces from 2009 to 2022 was employed to train and test the models. A descriptive variable of dynamic unstable distance was introduced to evaluate the stability state of the formed entry and six other parameters were chosen as influence parameters. The two intelligent models were compared with each other to have a comprehensive assessment. Model assessment indices such as R2, mean absolute error, mean absolute percentage error, and root mean square error were used to evaluate the accuracy of the models. The results of both developed models are promising, and the predictive accuracy of the PSO‐ANN model is higher than that of the GO‐ANN model. Through sensitivity analyses, it has been found that the coal seam thickness and roof rock hardness are the most important parameters for influencing entry stability. The developed method provides a practical tool for the prediction of entry stability and the optimization of entry design. [ABSTRACT FROM AUTHOR]

Coal-mining areas are widely distributed in Northern China, but are under threat from confined water in the mining operation, resulting in a series of floor water- inrush hazards. Therefore, it is significant to effectively evaluate the floor water inrush to ensure safe and efficient coal mining. The 182602 working face of the Wutongzhuang coal mine served as the background for our research. The concept of "pre-mining microseisms" was proposed, and based on this, microseismic monitoring equipment was arranged on site. The correlation between microseismic events and the water abundance of an aquifer was analyzed, and a floor water inrush evaluation method was constructed based on the three elements of an aquifer and pre-mining microseisms. The main results are as follows: first, the microseismic events were excited by artificial disturbances before the mining of the working face including slurry diffusion and neighboring mining, which had the characteristics of sporadicity, clustering, and periodicity. Second, the regional distribution of water abundance was determined by taking the water inflow, water pressure, and grouting volume as the outward performance characteristics of water abundance in the Shanvuqing aquifer. Furthermore, the correlation coefficient between the pre-mining microseisms and the three elements of the aquifer (water inflow, water pressure, and grouting volume) was larger than 0.7. On this basis, an evaluation method associated with the water inrush risk along the strike of the working face was established based on pre-mining microseisms, dividing the working face into dangerous zones, suspected dangerous zones, and safe zones. Furthermore, pre-mining microseisms, water abundance, and structures were introduced as risk-evaluation indices, and the complete weight was calculated using an analytic hierarchy process and entropy-weight technique, before a vulnerability index model of floor water inrush was built. Finally, targeted treatment procedures were efficiently implemented to ensure the safe mining of working face 182602 due to the successful prediction of potential water risk zones. The research results provide scientific and technological support for pre-mining microseisms combined with water abundance as a technical method to prevent floor water inrush. [ABSTRACT FROM AUTHOR]