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The occurrence of linear discontinuous deformations, primarily manifesting as ground steps, is becoming increasingly prevalent in mining and post-mining areas. These deformations present a significant hazard to structures, as there are no effective protective measures currently available. An important aspect of these deformations is that they can occur several decades after mining operations have ceased, making it crucial to understand their causes and conditions of formation. This paper presents a detailed case study of ground step formation that resulted in substantial damage to storage halls. Through comprehensive analyses of geological and mining conditions, combined with rigorous calculations, the study identifies the most likely factors that triggered the deformation. Notably, these factors differ from those commonly cited in the existing literature, providing a novel contribution to the research on this issue. The findings underscore the necessity for continuous monitoring and reevaluation of post-mining areas to mitigate potential risks and develop more effective protective strategies.

Large rocky landslides induced by underground mining are the primary type of geological disaster in the karst mountains of southwestern China. In this study, by integrating field surface surveys, interferometric synthetic aperture radar (InSAR) monitoring, and discrete element simulations, we analyzed the deformation evolution of steep cliffs with karst structural planes under mining disturbance. Based on the stress transfer, deformation response, and instability precursors, a landslide instability model was developed. The results revealed that the instability boundaries and the instability mode were controlled by the large structural plane at the top of the mountain. Underground mining accelerated the uneven subsidence of the overlying strata, which led to expansion and penetration of the karst fissure structural planes and fracturing of the rock base, which are the main reason for the instability of the mountain. Underground mining caused internal stress fluctuation of the overlying strata, and the mountain experienced four stages during this process, i.e., development of karst fissure structural planes, fissures expansion and rock base fracturing, further fissures expansion and rock base crashing, and fissures penetration and shear failure. The mining-induced failure of mountain with large karst structural planes can be described as tensile shear-fracturing crashing failure. The InSAR monitoring results revealed that accelerated deformation occurred in the source area starting 20 days before the Baiyan landslide. In addition, 25 potential deformation landslides were identified in Zhijin County, Guizhou Province. Hence, InSAR technology can be used for early-stage detection and warning of similar landslides.

Crown pillars provide regional and local support by isolating the ground surface from underground mine workings. Topography above the underground mine may be a relatively flat ground surface or an open-pit structure. Depending on what lies above and design of the underground mine, the crown pillar behaviour will differ. In transitioning setups (open pit to underground), large open pit collapses have taken place as a result of crown pillars located at the transition zone. Hence, this paper focuses on crown pillars between open pit and underground to better understand their behaviour. Taking the Zuuntsagaan Fluorite mine as an example where open pit will transform to underground mining, a remnant ore is to be left as a crown pillar to separate the two mining sections. Through numerical simulation in FLAC3D 7.0, stress distribution and failure mechanisms acting around the crown pillar were monitored as underground mining progresses. Effect of crown pillar geometrical parameters was evaluated, thus crown pillar thickness, span and dip. Further, the open pit geometry influence was also considered on the overall behaviour of the crown pillar. It was found out that in transition from open pit to underground, slope and stope walls closing in on the crown pillar induce stresses that act as loading from the pillar sides, which in turn influence the failure process.

Visible light communication (VLC) is considered an enabling technology for future 6G wireless systems. Among the many applications in which VLC systems are used, one of them is harsh environments such as Underground Mining (UM) tunnels. However, these environments are subject to degrading environmental and intrinsic challenges for optical links. Therefore, current research should focus on solutions to mitigate these problems and improve the performance of Underground Mining Visible Light Communication (UM-VLC) systems. In this context, this article presents a novel solution that involves an improvement to the Angle Diversity Receivers (ADRs) based on the adaptive orientation of the Photo-Diodes (PDs) in terms of the Received Signal Strength Ratio (RSSR) scheme. Specifically, this methodology is implemented in a hemidodecahedral ADR and evaluated in a simulated UM-VLC scenario. The performance of the proposed design is evaluated using metrics such as received power, user data rate, and bit error rate (BER). Furthermore, our approach is compared with state-of-the-art ADRs implemented with fixed PDs and with the Time of Arrival (ToA) reception method. An improvement of at least 60% in terms of the analyzed metrics compared to state-of-the-art solutions is obtained. Therefore, the numerical results demonstrate that the hemidodecahedral ADR, with adaptive orientation PDs, enhances the received optical signal. Furthermore, the proposed scheme improves the performance of the UM-VLC system due to its optimum adaptive angular positioning, which is completed according to the strongest optical received signal power. By improving the performance of the UM-VLC system, this novel method contributes to further consideration of VLC systems as potential and enabling technologies for future 6G deployments.

For this study, as part of the underground operations, the underground mining sequence was explored for suitability in the Zuuntsagaan mine. Two mining sequences are considered; bottom-up (B-U) and top-bottom (T-B), and the instability of stopes and open pit slopes is evaluated in response to each sequence. For the present rock mass conditions and stress state, with reference to the underground section, the results revealed that T-B sequence has lower ground movements. On the open pit section, the effect of the two sequences is relatively the same while the difference is mainly observed in the underground section.

Understanding the changes in a land use/land cover (LULC) is important for environmental assessment and land management. However, tracking the dynamic of LULC has proved difficult, especially in large-scale underground mining areas with extensive LULC heterogeneity and a history of multiple disturbances. Additional research related to the methods in this field is still needed. In this study, we tracked the LULC change in the Nanjiao mining area, Shanxi Province, China between 1987 and 2017 via random forest classifier and continuous Landsat imagery, where years of underground mining and reforestation projects have occurred. We applied a Savitzky–Golay filter and a normalized difference vegetation index (NDVI)-based approach to detect the temporal and spatial change, respectively. The accuracy assessment shows that the random forest classifier has a good performance in this heterogeneous area, with an accuracy ranging from 81.92% to 86.6%, which is also higher than that via support vector machine (SVM), neural network (NN), and maximum likelihood (ML) algorithm. LULC classification results reveal that cultivated forest in the mining area increased significantly after 2004, while the spatial extent of natural forest, buildings, and farmland decreased significantly after 2007. The areas where vegetation was significantly reduced were mainly because of the transformation from natural forest and shrubs into grasslands and bare lands, respectively, whereas the areas with an obvious increase in NDVI were mainly because of the conversion from grasslands and buildings into cultivated forest, especially when villages were abandoned after mining subsidence. A partial correlation analysis demonstrated that the extent of LULC change was significantly related to coal production and reforestation, which indicated the effects of underground mining and reforestation projects on LULC changes. This study suggests that continuous Landsat classification via random forest classifier could be effective in monitoring the long-term dynamics of LULC changes, and provide crucial information and data for the understanding of the driving forces of LULC change, environmental impact assessment, and ecological protection planning in large-scale mining areas.

The illegal mining events could be found in coal-rich regions around the world, which could not only seriously damage mineral resources and ecological environment, but also cause mine disasters and great economic loss, as well as threatening safety production and social stability. Due to wide distribution of mines and strong concealment of underground illegal mining activities, it is hard to find out these behaviors promptly and accurately depending only on mine law-enforcing departments whose investigations will be time–energy–finance-consuming. Therefore, it is an urgent problem to quickly and accurately identify illegal mining events. To solve the problem, this paper uses the new mining subsidence monitoring by D-InSAR to accurately get the surface deformation and establishes a space–time relationship model of surface deformation and underground mining characterized by subsidence. On the basis of this, the integration of D-InSAR and GIS technology is used to develop a quick, efficient, and accurate way to identify illegal underground mining areas. Then, a case study is conducted in the district of Yangquan, Shanxi Province, China. The identification results have been compared with the data about illegal mining by local law-enforcing departments during the same period. The research results indicate that the identification results are basically the same as the actual illegal mining events. Therefore, the proposed method based on integration of D-InSAR and GIS technology could be utilized for real-time and dynamic monitoring of illegal mining events. The results could also provide important technical support in guiding mine law-enforcing departments to timely crack down and remove illegal underground mining events, maintain mining orders, and protect the ecological environment.

This study investigates the impact of wall roughness on the performance of the Non-Line-of-Sight (NLOS) component in Visible Light Communication (VLC) systems designed for underground mining environments, adhering to safety and communication standards such as IEC 60079-28(intrinsic safety in explosive atmospheres) and IEEE 802.15.7 (VLC parameters). Using probabilistic models aligned with the ITU-R P.1238 propagation guidelines, the research evaluates how wall materials (e.g., coal, shale, limestone) and their irregular geometries, characterized by surface roughness profiles compliant with ISO 8503-2,influence reflection coefficients (0.05–0.85 range), incidence angles (0°–90°), and irradiance angles (5°–180°), which are critical for signal propagation. Simulation scenarios, parameterized with material reflectivity data from ASTM E423, explore the effects of statistical distributions (uniform, normal with μ = 0.3, σ = 0.2; exponential λ = 2; gamma α = 0.5, β = 0.2) on power distribution, channel impulse response, and reflection coefficients. The results indicate variations in maximum received power: a decrease of 80% for uniform distribution, an increase of 150% for exponential distribution, and a 100% increase for gamma distribution in reflection conditions. Under incidence and irradiance conditions, uniform distribution exhibited a 158.62% increase, whereas exponential distribution and gamma distribution experienced reductions of 72.22% and 7.04%, respectively. These variations align with IEC 62973-1 EMI limits and emphasize the role of roughness (Ra = 0.8–12.5 μm per ASME B46.1).

Fault activation caused by construction, earthquakes, or mining can produce disastrous water-inrush episodes in underground mines. Fault activation is generally caused by stress concentration at the fault tip, so in this study, a computational model of a typical underground stope with a hidden fault was established to quantitatively assess the magnitude of the stress concentration of the stress fields of the fault-tip. Numerical simulation was performed using the extended finite element method and fracture mechanics. Stress intensity factors, which represent the magnitude of the stress concentration, were obtained using the interaction integral method to quantitatively evaluate the tip fields and assess the possibility of fault activation. The mining depth, fluid pressure, fault dip, and fault length were analyzed and the advance of a working face was simulated to determine whether underground mining would cause fault activation.

In recent years, landslides induced by underground mining have attracted much attention as they cause great harm and early warning signals are difficult to detect. The key work of the early warning of a mining landslide is to clarify its initiation mechanism and evolution process. Due to the complexity of the deformation and failure of the goaf overburden and the lack of monitoring of the slope evolution process, the deformation and failure law and evolution characteristics of mining landslides have always been difficult to analyze. In this paper, a typical mining landslide, the Madaling landslide, was selected as the study object. The soft-hard interlayer structure of the slope was generalized and explored by centrifuge model tests and a 3D discrete element model. The results showed that the evolution of the Madaling landslide are divided into four stages: (I) the bending and collapse of the goaf overburden, the slope settlement and the formation of tensile cracks at the trailing edge; (II) the upwards extension of the subsidence cracks of the rock mass; (III) the occurrence of shear cracks in the rock mass, with gradual slope deformation as a whole; and (IV) the connection of shear cracks, with the initiation of landslides. The long-term gravity creep of soft rock and the extension of trailing edge tensile cracks cause the internal rock mass of the slope to become the key block controlling slope stability. The slope surface displacement (S)-time (t) curve of mining landslides is divided into the settlement stage, rock mass crack development stage and landslide evolution stage. The formation time of shear cracks in the rock mass crack development stage is a sign of the transformation of subsidence into a landslide. The relationship between the horizontal displacement and the depth of the rock mass effectively reflects the development stage of shear cracks. The horizontal and vertical displacement of the deep rock mass can serve as the early warning criterion for mining landslides.