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Estimating average vertical pillar stresses is a critical step in designing room-and-pillar mines. Several analytical methods can be used to estimate the vertical stresses acting on the pillars. However, the present analytical methods fail to adequately account for the influence of abutments on the distribution of vertical stresses, especially when applied to narrow panel widths and pillar layouts comprising evenly spaced barriers. In this study, a multi-layer perceptron neural network (MLPNN) was applied to predict the vertical loads of regular pillars more accurately. Hundreds of room-and-pillar mine layouts were modeled using a displacement discontinuity method (DDM), and a database of 2355 sampled pillar cases was compiled. The MLPNN was trained based on this database, and its prediction capabilities were further validated using simulations by a finite difference code (i.e., FLAC3D). The model predictions and the FLAC3D simulations reasonably agreed with a regression coefficient of 0.99. The model was also adapted for mine cases with evenly spaced barrier pillars, and its application to a real case study mine has shown to provide accurate pillar stress estimations; hence, this model is suitable for practical use at mines. Even though the MLPNN model cannot be applied universally to all mine situations, it seems as a significant improvement over existing analytical techniques in terms of accounting for the influence of abutments on pillar stresses.

The wide pillars are generally popular due to the high productivity and efficiency in Northwest China. The distribution of lateral abutment pressure in coal pillars is important for mining safety. To reveal the effect of the first mining on the lateral abutment pressure distribution and evolution in wide pillars, an in-situ experiment, theoretical analysis and numerical simulation were performed. First, the field monitoring of lateral abutment pressure was conducted from the perspective of time and space in the Chahasu Coal Mine, Huangling No. 2 Coal Mine and Lingdong Coal Mine during the first mining. Based on the field monitoring stress, a theoretical model was proposed to reveal the lateral abutment pressure distribution. The methodology was demonstrated through a case study. Aiming at the distribution mechanism, a numerical experiment was conducted through the finite-discrete element method (FDEM). Last, field observations of borehole fractures were performed to further study the damage distribution. In addition, two types of lateral abutment pressure evolution with mining advance were discussed. Suggestions on the stress monitoring layout were proposed as well. The results could provide foundations for strata control and disaster prevention in wide pillars in underground coal mines.

Pillar stability is an important condition for safe work in room-and-pillar mines. The instability of pillars will lead to large-scale collapse hazards, and the accurate estimation of induced stresses at different positions in the pillar is helpful for pillar design and guaranteeing pillar stability. There are many modeling methods to design pillars and evaluate their stability, including empirical and numerical method. However, empirical methods are difficult to be applied to places other than the original environmental characteristics, and numerical methods often simplify the boundary conditions and material properties, which cannot guarantee the stability of the design. Currently, machine learning (ML) algorithms have been successfully applied to pillar stability assessment with higher accuracy. Thus, the study adopted a back-propagation neural network (BPNN) and five elements including the sparrow search algorithm (SSA), gray wolf optimizer (GWO), butterfly optimization algorithm (BOA), tunicate swarm algorithm (TSA), and multi-verse optimizer (MVO). Combining metaheuristic algorithms, five hybrid models were developed to predict the induced stress within the pillar. The weight and threshold of the BPNN model are optimized by metaheuristic algorithms, in which the mean absolute error (MAE) is utilized as the fitness function. A database containing 149 data samples was established, where the input variables were the angle of goafline (A), depth of the working coal seam (H), specific gravity (G), distance of the point from the center of the pillar (C), and distance of the point from goafline (D), and the output variable was the induced stress. Furthermore, the predictive performance of the proposed model is evaluated by five metrics, namely coefficient of determination (R2), root mean squared error (RMSE), variance accounted for (VAF), mean absolute error (MAE), and mean absolute percentage error (MAPE). The results showed that the five hybrid models developed have good prediction performance, especially the GWO-BPNN model performed the best (Training set: R2 = 0.9991, RMSE = 0.1535, VAF = 99.91, MAE = 0.0884, MAPE = 0.6107; Test set: R2 = 0.9983, RMSE = 0.1783, VAF = 99.83, MAE = 0.1230, MAPE = 0.9253).

The hard roof of coal mines has the characteristics of high hardness, good integrity, and large layer thickness, which leads to many ground control problems. To reveal the influence of a hard roof structure on the stress performance and coal pillar stability during mining operations, the 8,104 and 8,105 working faces in the Tongxin coal mine were considered as the research object to analyze the stress behavior during the working face advance. Numerical simulation software FLAC3D was used to establish the numerical model of the longwall face under hard roof conditions. The stress distribution laws and coal pillar stability under different roof strengths were analyzed so as to explain the impacts of the hard roof on the stress distribution at the working face. The results show that during the second face proceeding, the influence zone of the front abutment pressure under hard roof conditions is 6 m wider than that under soft roof conditions, and the bearing stress at the working face is 10.4 MPa higher. At the mining position, the plastic zone of the pillar under hard roof conditions is 11 m wider than that under soft roof conditions, and the peak vertical stress is 5.13 MPa higher than that under soft roof conditions. At 25 m ahead of the working face, the plastic zone of the pillar under hard roof conditions is 6 m wider than that under soft roof conditions, and the peak vertical stress is 24.84 MPa higher than that under soft roof conditions. Additional overburden pressure produced by the uncaved hard roof increased pillar stress and plastic zones. Therefore, the hard roof is the main cause of strong ground pressure behavior in the Tongxin coal mine. Aiming at the strong mine pressure behavior, it is suggested to adopt the pre-splitting technology to reduce the influence of the hard roof on mine pressure.

Coal is a nonrenewable resource. Hence, it is important to improve the coal recovery ratio and ensure the stability of coal mines for sustainable development of mining cities. Partial extraction techniques, such as strip pillar mining or room-and-pillar mining, are efficient methods to extract coal. Pillar stress is a critical property for pillar design and for the assessment of mine stability after partial extraction. Current pillar stress calculation methods can sometimes overestimate the pillar stress and unnecessarily large coal pillars may be left underground, which leads to a waste of coal resources. In this paper, the size effects of mining activity on the maximum vertical pillar stress were investigated using numerical simulations. Both strip pillar mining and room-and-pillar mining were considered as possible mining scenarios at different mining depths. The results show that the maximum pillar stress of a mine is primarily controlled by four factors: the mine size to mining depth ratio, the mining width to pillar width ratio, the overburden elastic modulus, and the mining depth. The maximum pillar stress of a mine gradually increases to an ultimate value as the mine size increases. Simplified formulas and methodology have been derived for stress calculations under consideration of mine size effects and, therefore, can reduce the waste of coal resources from the overestimation of pillar stress. [ABSTRACT FROM AUTHOR]

Generally the settlement of spherical tank’s foundation is difficult to ensure complete uniformity. Especially the foundation has been used for years. There is always a certain differential settlement. Pillar stress of the tank will be uneven under differential settlement. The stress of a LPG spherical tank on use with multiple differential settlements is analyzed by elasticity model of finite element method. According to the analysis results under hydraulic testing pillar stress exceeds the yield strength of the material. Then elastoplastic model is established to analyze the impact of material nonlinearity of pillar. Through finite element analysis and experimental testing,whether the tank can be used is evaluated. Based on the analysis results the tank is recommended to use under low load and strong inspection.

This paper investigates various multiseam mining related parameters using mine site specific data and numerical simulations. Two important mining effects-subsidence and stress-are analysed for different possible mining layouts. A geological mine dataset has been used to generate a numerical model. The predicted surface subsidence magnitude and surface profile have been compared under different scenarios to assess potential options in multiseam mining strategies. The effects that seam separation distances, mining offset, panel layout and panel orientation each have on surface subsidence and chain pillar stress magnitude have been investigated. The numerical simulation shows that ascending or descending mining directions have little impact on controlling the surface subsidence in multiseam mining and predicted an almost identical maximum stress development at the chain pillars. Numerical simulations infer that the orientation of the top panels control the subsidence profile. [ABSTRACT FROM AUTHOR]

An investigation is made of the characteristic strata movement and mechanism underlying fault-pillar induced rock bursts (FPIRBs) in order to mitigate rock burst damage in fault areas. A mechanical analysis of the fault-pillar model is established and roof rotation criteria is obtained. A formula is derived for the average static stress in the pillar through theoretical analysis, physical simulations, and engineering practice. The results show that when a coalface approaches a fault area, two or more roof strata simultaneously fracture in the fault area, leading to an increase in the dynamic and static stresses in the pillar. The most important factors affecting FPIRB are the static stress in the pillar and the dynamic stress induced by fault slides. The roof block rotates more easily when the pillar width is smaller, the roof thickness larger, and the roof subsidence smaller. The average static stress in the pillar increases with decreasing pillar width and/or increasing roof fracture length. The stress is greater if there is a voussoir beam structure, in which case the stress is directly proportional to the squared length of the fractured roof, and inversely proportional to the squared width of the pillar just before rotation occurs. After rotation, it is directly proportional to the roof fracture length and inversely proportional to the pillar width. Based on the FPIRB mechanism and analysis of the mechanical model, six methods of FPIRB prevention are proposed. Also, we find that FPIRB occurrence can be effectively reduced by the use of de-stress blasting and large diameter drilling. [ABSTRACT FROM AUTHOR]