Physical Model Experimental Study on the Coalface Overburden Movement Law on the End-slope of an Open-pit Mine

Due to technology and safety limitations, the amount of coal resources overlying slopes in open pit coal mines is immense. In recent years, this problem has gradually attracted the attention of researchers. How to realize the efficient recovery of the side overburden resources with the premise of ensuring the stability and safety of the slope has become an important topic for the development of opencast mining technology in China. To study the yield failure characteristics of coal pillars and the rock mass migration law of the end slope mining field under the mining condition of the end slope shearer, 2D/3D, integrated, simulation experimental equipment is developed based on similarity theory and efficient region theory. This equipment overcomes the technical problem that the internal failure of the rock mass is invisible and that deformation data are not easily obtained during the simulation of end slope coal mining on an existing experimental platform. Based on the engineering geological conditions of the Ordos mining area in China, a typical engineering geological model of the slope near the horizontal condition is constructed to simulate the process “formation of mining cave group -failure of support coal pillars - instability of slope rock mass”. Based on laser positioning technology and multiangle, oblique photography technology, a panoramic phase 3D laser scanner, high-resolution digital camera and deep space micromonitoring system are comprehensively employed to carry out the whole process tracking monitoring and analysis of the deformation and failure of the supporting coal pillars and slope rock mass. The experiment is verified by numerical simulation. The results show that under the experimental conditions, with an increase in mining cave depth, the vertical stress of the supporting coal pillar increases linearly. At a certain distance before reaching the end of the mining cave, the peak value is reached. At this time, the depth continues to increase, and the stress value decreases sharply. The vertical stress gradually decreases to the original rock stress after a certain distance beyond the end of the mining cave. A certain length of supporting coal pillar from the end of the mining cave will never collapse, which is approximately 2.5~3 times the width of the mining cave. The triggering condition of slope deformation and failure is under the combined action of dynamic and static loads. The actual stress of the supporting coal pillar in the deep part of the geometric centre along the slope of the mining cave group is greater than the ultimate stress, and then large discontinuous deformation of multiple adjacent coal pillars around the central coal pillar is caused by compressive shear failure. The boundary of the final collapse plane range of the roadway group is approximately a closed curve formed by two paraboloids, which are axisymmetric with the No. Ⅳ coal pillar and open opposite. The parabola opening in the shallow part of the slope area is small, and the parabola opening in the deep part of the slope area is large. There is a significant space-time correspondence between the failure of supporting coal pillars and the deformation of the slope surface. According to the failure process of the rock mass structure and the movement and deformation characteristics of the slope surface, the slope after failure can be divided into three areas, and the upper part of the slope is the key area of deformation and instability of the overlying rock mass in the end-slope mining field. The research results provide a theoretical basis for scientific monitoring and stability control of slope deformation coal mining conditions in open-pit mines.

Remote-Sensing Evaluation and Temporal and Spatial Change Detection of Ecological Environment Quality in Coal-Mining Areas

The large-scale development and utilization of coal resources have brought great challenges to the ecological environment of coal-mining areas. Therefore, this paper has used scientific and effective methods to monitor and evaluate whether changes in ecological environment quality in coal-mining areas are helpful to alleviate the contradiction between human and nature and realize the sustainable development of such coal-mining areas. Firstly, in order to quantify the degree of coal dust pollution in coal-mining areas, an index-based coal dust index (ICDI) is proposed. Secondly, based on the pressure-state-response (PSR) framework, a new coal-mine ecological index (CMEI) was established by using the principal component analysis (PCA) method. Finally, the coal-mine ecological index (CMEI) was used to evaluate and detect the temporal and spatial changes of the ecological environment quality of the Ningwu Coalfield from 1987 to 2021. The research shows that ICDI has a strong ability to extract coal dust with an overall accuracy of over 96% and a Kappa coefficient of over 0.9. As a normalized difference index, ICDI can better quantify the pollution degree of coal dust. The effectiveness of CMEI was evaluated by four methods: sample image-based, classification-based, correlation-based, and distance-based. From 1987 to 2021, the ecological environment quality of Ningwu Coalfield was improved, and the mean of CMEI increased by 0.1189. The percentages of improvement and degradation of ecological environment quality were 71.85% and 27.01%, respectively. The areas with obvious degradation were mainly concentrated in coal-mining areas and built-up areas. The ecological environment quality of Pingshuo Coal Mine, Shuonan Coal Mine, Xuangang Coal Mine, and Lanxian Coal Mine also showed improvement. The results of Moran’s Index show that CMEI has a strong positive spatial correlation, and its spatial distribution is clustered rather than random. Coal-mining areas and built-up areas showed low–low clustering (LL), while other areas showed high–high clustering (HH). The utilization and popularization of CMEI provides an important reference for decision makers to formulate ecological protection policies and implement regional coordinated development strategies.

Contemporary Biological Methods of Mine Reclamation in the Kemerovo Region – Kuzbass

Introduction. Coal mining is the main source of anthropogenic impact on the landscapes of the Kemerovo Region – Kuzbass. The current mine reclamation rate lags far behind the annual increase in disturbed lands. A reclamation fund can be a perfect solution to this relevant issue. The present research objective was to analyze and structure the available data on the anthropogenic impact of coal mining in Kuzbass. The article reviews new effic ient methods of reclamation and resoiling. Study objects and methods. The study featured ten years of research publications that were registered in the PubMed database of the National Center for Biotechnology Information (USA), Elsevier (Scopus, ScienceDirect), the Web of Science, and the Russian Electronic Library (eLibrary.ru). Results and discussion. The research revealed the following Kuzbass districts that experience the greatest mining impact: Novokuznetsk, Prokopyevsk, Kemerovo, Belovo, and Leninsk-Kuznetskiy. The authors also identified the most common pollutants associated with coal mining. Polycyclic aromatic hydrocarbons (PAHs) appeared to be the most dangerous pollutants: as waste coal burns, these substances cover considerable distances with the wind. Biodegradation seems to be the optimal solution because PAHs are known to be carcinogenic, and most mine tips are located near settlements. The article also features mine reclamation laws and introduces a list of plants with a high absorption capacity recommended for biological reclamation, as well as microorganisms and their consortia used for bioremediation. Conclusion. The authors identified the most promising methods of mine reclamation in the Kemerovo region, i.e. bioremediation with pollutant-binding microbial consortia and plants.

Model Altman Untuk Menilai Kinerja Perusahaan Subsektor Pertambangan Batubara Periode 2015-2019

This study aims to determine the degree of accuracy of the Altman Z-score method in predicting the bankruptcy of a company. This study uses quantitative research with a descriptive approach through accuracy and error type tests. Where the samples used are companies that are members of the coal mining sub-sector during the 2015-2019 period. Purposive sampling method was used in sampling with a total sample of 19 companies. The Altman Z-score method has an accuracy rate and type error of 11% and 42%, which indicate that the method is not good for use in companies that are members of the coal mining sub-sector.