Search Results (82)

To address the critical challenges of geological hazards, such as water and mud inrush, encountered during the construction of deep-buried tunnels in China, this study investigates the hydraulic properties of remolded mud-infill materials. A multi-scale approach, integrating indoor variable-head permeability tests with scanning electron microscopy (SEM), was employed to characterize the evolutionary patterns of the permeability coefficient (k). Specifically, the research evaluates the independent influences of moisture content, dry density, and confining pressure, alongside the synergistic coupling between dry density and hydration state. The results demonstrate the following: Under independent variable conditions, k exhibits a monotonic decline with increasing dry density and confining pressure while showing a positive correlation with moisture content, with the sensitivity varying significantly across different parameter regimes; under coupled effects, the permeability in both low- and high-moisture ranges manifests a distinct “increase–decrease–increase” fluctuation as dry density rises, reaching a local peak at 2.20 g/cm³. Notably, a relative minimum k (6.12 × 10⁻⁷ cm/s) is achieved at the optimum moisture content (5.8%); micro-mechanistic analysis reveals that low-moisture samples are characterized by randomized angular particles and well-developed interconnected macropore networks, facilitating higher k values. Conversely, high-moisture samples exhibit preferential plate-like stacking dominated by occluded micropores, resulting in a substantial reduction in hydraulic conductivity. This study elucidates the multi-factor coupling mechanism governing the seepage behavior of remolded mud, providing essential theoretical benchmarks for the prediction and mitigation of water–mud outburst disasters in deep underground engineering, thereby ensuring the structural stability and operational safety of tunnel projects. Full article

Water accumulation in goafs in Chinese coal mines is a major hidden hazard that can trigger water inrush accidents and may also affect aquifer integrity and regional water security. Reliable delineation of goaf water distribution and identification of water-source types are therefore essential for mine water-hazard control and groundwater protection. This paper reviews the main technical routes for goaf groundwater investigation, including geophysical prospecting, hydrogeochemical and isotopic identification, direct inspection tools, and data-driven intelligent workflows. For geophysical detection, the mechanisms, engineering applicability, and key constraints of the Transient Electromagnetic Method (TEM), Surface Nuclear Magnetic Resonance (NMR), the High-Density Resistivity Method (HDRM), and the Coherent Frequency Component (CFC) electromagnetic wave reflection coherence method are synthesized, with emphasis on interpretation boundaries and uncertainty sources under complex geological conditions. For source identification, conventional hydrochemistry, stable isotopes, and laser-induced fluorescence are summarized, and intelligent recognition models such as neural networks and support vector machines are discussed in terms of workflow positioning and practical performance limits. A unified evaluation rationale is established and a semi-quantitative method–metric matrix is constructed to compare techniques in terms of reliability, deployability, cost level, environmental adaptability, and information value, thereby clarifying their functional roles and complementarities within staged engineering workflows. The synthesis indicates that major bottlenecks include limited deep capability under strong interference, pronounced interpretational non-uniqueness caused by complex geology and irregular goaf geometries, and constrained timeliness and generalization for mixed-source identification. Future directions are summarized as multi-method integration with fusion-driven interpretation, intelligent and quantitative decision support with quality control, and sensor–platform advances enabling more practical three-dimensional investigation, aiming to improve the reliability and engineering usability of goaf groundwater hazard assessment. Full article

Rapid and accurate identification of water inrush sources is essential for the prevention and control of coal mine water hazards. Fisher discriminant analysis and random forest are widely applied, but their performance comparison and applicability under single-mine and multi-mine scenarios remain to be investigated. This study takes the Tunlan Mine in Shanxi Province, China, as an example and evaluates both models using accuracy, precision, recall, F1-score, and confusion matrix. A joint discrimination scheme is used to explore their generalization ability. In the single-mine scenario, the improved Fisher algorithm achieves an overall accuracy of 93% and the random forest model achieves 87%, indicating that the former has greater advantages when data distribution is relatively linear. In the multi-mine joint discrimination scenario, the random forest model yields accuracies of 77–98%, far exceeding those of the Fisher algorithm and demonstrating clear superiority in handling complex nonlinear data. The results show that model performance depends primarily on data quality and feature distribution rather than solely on sample size. This study provides a scientific basis for selecting water source identification algorithms in different scenarios and has practical value for improving coal mine water hazard prevention and control. Full article

The structural integrity of isolation dams in deep coal mines is critical to preventing underground disasters, particularly those involving water and waste-mixture inrushes. This study presents a forensic root-cause analysis, using reverse-engineering techniques, of a specific isolation-dam rupture to determine the failure mechanism under complex stress conditions and limited data availability. A hybrid investigative methodology was employed, combining sequential post-failure documentation analysis with physical-scale modelling and numerical simulations to reconstruct a deadly disaster for criminal investigation purposes. A 1:5 scale physical model of the excavation and dam was constructed using original construction materials to test the structure’s resistance to hydrostatic pressure. The experimental results demonstrated that the dam maintained integrity under static hydraulic loads representative of real-world conditions, with only minor seepage (“sweating”) and no structural failure over a 7-day monitoring period. To investigate external geomechanical factors, Finite Element Method (FEM) simulations were conducted using ANSYS software. The numerical analysis evaluated the effects of rock mass pressure and convergence on the dam’s stability. The results indicate that while the dam was designed to withstand significant hydraulic head, the failure was precipitated by excessive rock mass pressure at a depth of around 600 m, which induced critical stress concentrations exceeding the masonry’s load-bearing capacity. This study confirms that the dynamic rupture was driven by unforeseen geomechanical forces rather than hydrostatic overload alone, highlighting the necessity of considering rock mass–structure interaction in the safety assessment of underground isolation barriers. This approach enables mutual verification of the results obtained and reduces the ambiguity of interpretation that often accompanies the analysis of accident events in underground mining. It also confirms the application of tested methodology for mining disaster reconstruction as proof at the stage of investigation and in the Court. Full article

Regional curtain grouting for water interception serves as a critical technique for achieving safe and efficient mining under complex hydrogeological conditions in deep mine deposits. This study focuses on the Cuihongshan Iron-Polymetallic Mine, where repeated incidents of water inrush and sand outbursts have occurred due to complex hydrogeological conditions. By identifying the water-conducting pathways and characterizing the spatial distribution of relative aquitards within the mining area, a precise hydrogeological model was established. On this basis, the engineering application and performance evaluation of horizontal curtain grouting were systematically investigated. Through field monitoring and multi-method joint analysis, the water-blocking effectiveness of the grouting technique was comprehensively assessed. The results demonstrate a significant sequential reduction in grout take per meter for primary, secondary, and tertiary grouting holes, indicating a clear cumulative grouting effect. The grout effectively filled karst fractures, forming a continuous and stable water-resisting curtain. The project successfully severed the hydraulic connection between the highly water-rich Quaternary aquifer and the mine workings, substantially reducing mine water inflow. This study provides important theoretical support and practical reference for water hazard control in similar deep metal mines. Full article

The roof aquifer of the Jurassic coal seam is the primary source of water inrush in the Nalinhe Mining Area. It poses a severe threat to safe mining operations. Accurate prediction of its water richness is crucial for production safety. This study focuses on the Nalinhe No. 2 Coal Mine. Seven key controlling factors were selected as evaluation indicators, including aquifer thickness, burial depth, core recovery rate, the thickness ratio of brittle to plastic rock, fault scale density, fault fractal dimension, and the density of fault endpoints and intersections. A hybrid weighting strategy was applied in this study. This strategy integrates the Analytic Hierarchy Process (AHP) and the Entropy Weight Method (EWM) to assign scientific weights to the evaluation indices. A water richness evaluation model was subsequently developed based on matter-element extension theory. The model calculates the comprehensive correlation degree for each grid node and determines the corresponding water richness level. Zoning results were validated with unit inflow data from pumping test boreholes, mine inflow observations, and ground transient electromagnetic survey findings. The predicted water richness zones closely matched the measured hydrogeological data. These results demonstrate the scientific rigor and reliability of the matter-element extension model. The proposed model provides a novel approach for assessing water richness in coal seam roof aquifers. Full article

Accurate prediction of aquifer water abundance is critical for coal mine safety, yet traditional static models often fail to capture the spatial heterogeneity and non-stationarity of hydrogeological conditions. This study proposes a dynamic evaluation methodology integrating Grey Relational Analysis, the Analytic Hierarchy Process, and a Time-Varying Parameter Cubature Kalman Filter (TVP-CKF). By reconceptualizing spatial borehole data as a dynamic time-series process, the model recursively updates the contribution weights of six controlling factors based on monitoring data from 2012 to 2020. Analysis reveals a structural shift in the groundwater system: the influence of hydrochemical factors (TDS) has diminished, while hydraulic conductivity has become the dominant control over time. The TVP-CKF model significantly outperformed static regression and recursive least squares baselines, demonstrating superior convergence stability and precisely capturing transient inflow fluctuations. Furthermore, its uncertainty quantification effectively bounded extreme low-flow events within 95% confidence intervals. This approach validates the necessity of adaptive modeling in evolving geological environments, providing a robust, risk-quantified tool for precise water inrush prevention. Full article

Roof water inrush is a major hazard threatening coal mine safety. This paper addresses the risk of roof water inrush during mining in the shallow-buried Jurassic coalfield of Northern Shaanxi, taking the Guojiawan Coal Mine as a case study. A systematic framework of “identification of main controlling factors–coupling of subjective and objective weighting–GIS-based spatial evaluation” is proposed. An integrated weighting system combining the Fuzzy Analytic Hierarchy Process (FAHP) and the Coefficient of Variation (CV) method is innovatively adopted. Four weight optimization models, including Linear Weighted Method, Multiplicative Synthesis Normalization Method, Minimum Information Entropy Method, and Game Theory Method, are introduced to evaluate 10 main controlling factors, including the fault strength index and sand–mud ratio. The results indicate that the GIS-based vulnerability evaluation model using the Multiplicative Synthesis Normalization Method achieves the highest accuracy, with a Spearman correlation coefficient of 0.9961. This model effectively enables five-level risk zoning and accurately identifies high-risk areas. The evaluation system and zoning results developed in this paper can provide a direct scientific basis for the design of water prevention engineering and precise countermeasures in the Guojiawan Coal Mine and other mining areas with similar geological conditions. Full article

Coal-free zones, particularly scouring zones, reduce recoverable reserves and increase water inrush risk in coal mining. Existing sedimentological, geophysical, and geostatistical methods are often constrained by coring conditions, lithological interpretation accuracy, and geological complexity. Given that well log signals provide the most continuous carriers of geological information, this study integrates Singular Spectrum Analysis (SSA), Maximum Entropy Spectral Analysis (MESA), and Integrated Prediction Error Filter Analysis (INPEFA) to establish a multi-curve framework for analyzing the genesis and logging responses of coal-free zones. A two-stage SSA workflow was applied for noise reduction, and a Trend–Fluctuation Composite (TFC) curve was constructed to enhance depositional rhythm detection. The minimum singular value order (N), naturally derived from SSA-decomposed INPEFA curves, emerged as a quantitative indicator of mine water inrush risk. The results indicate that coal-free zones resulted from inhibited peat-swamp development followed by fluvial scouring and are characterized by dense inflection points and frequent cyclic fluctuations in TFC curves, together with the absence of low anomalies in natural gamma-ray logs. By integrating multi-curve logs, core data, and in-mine three-dimensional direct-current resistivity surveys, the genetic mechanisms and boundaries of coal-free zones were effectively delineated. The proposed framework enhances logging-based stratigraphic interpretation and provides practical support for working face layout and mine water hazard prevention. Full article

Mining above confined aquifers fundamentally depends on understanding the evolution of floor permeability for water hazard control and water conservation mining. A mechanical model was developed to characterize the coordinated deformation of floor aquiclude strata, accounting for non-uniform distributions of stress and water pressure. The competing mechanisms whereby neutral plane strain and flexural deflection dominantly control permeability at different dip angles were elucidated, and the influence of dip angle on the stability of the water-resistant key strata was quantified. On this basis, a quantitative method for assessing the feasibility of in situ water conservation mining above confined aquifers was developed and its effectiveness was verified through field application. The main findings are as follows: The deflection of the floor aquiclude increases with water pressure, advance distance, and panel length. Larger coal seam dip angles correspond to smaller aquiclude deflection, with a strong dependence on the water pressure treatment method. The equivalent permeability of the floor increases with water pressure, panel length, and advance distance, and its variation is most pronounced with water pressure. As the dip angle increases, the equivalent permeability exhibits a trend of first rising and then decreasing; the transition between deflection-dominated and neutral plane strain-dominated control occurs at a dip angle of 35°. Lithological assemblage is found to govern the position of the neutral plane and the bending stiffness matrix, while a soft–hard interbedded floor is effective in suppressing deformation and mitigating the increase in the equivalent permeability. For inclined aquiclude key strata, the ranking of zones most prone to failure and water inrush is as follows: lower end > upper end > coal wall position > behind the goaf. A quadratic multi-parameter response model for the mining-induced equivalent permeability at the Fenyuan Coal Mine is established, yielding the sensitivity ranking under single factor and interaction effects as follows: water pressure > panel length > advance distance > water pressure (quadratic) > water pressure × panel length interaction. The higher the water pressure, the stronger the influence of dip angle on the equivalent permeability. Groundwater ion evolution is dominated by dissolution/leaching, with sulfate (SO₄²⁻) serving as a diagnostic ion for source identification. The stepwise criteria and grouting-reinforcement parameters for in situ protection of confined aquifers are proposed. Using water quality and quantity as evaluation metrics, Working Face 5-103 at the Fenyuan Coal Mine, which is a large-inclination-angle and high-pressure working face, has achieved in situ protection of the floor water. Full article

In recent years, with the continuous increase in coal mining depth and intensity, hydrogeological conditions in coal mines have become increasingly complex, and the risk of floor water inrush has risen significantly. To address the limitations of the global weighting pattern in traditional floor water inrush risk evaluation systems, this study, taking a coal mine in Shaanxi Province as a case, develops a local water inrush risk evaluation method based on the Monte Carlo Analytic Hierarchy Process (MAHP) combined with a circular moving window, and compares it with the water inrush coefficient method and the global evaluation method. The results demonstrate that the proposed local evaluation model achieves higher accuracy, provides a more refined delineation of high-risk zones, and shows stronger consistency with actual mining conditions. Further comparison of window radii of 100 m, 500 m, and 900 m indicates that the 500 m radius performs best in terms of spatial morphology, area proportion, and water inrush point identification rate (89.3%). Moreover, its application in Yangcheng Coal Mine further confirms that this method can accurately identify high-risk zones, thereby offering reliable scientific support for the prevention and control of coal seam floor water inrush. Full article

To reduce the risk of coal mine water inrush, a dynamic escape path optimization model based on the spatio-temporal evolution of the water inrush is studied. The actual coal mine is simplified into roadway nodes and segments to meet the real-time simulation of the coal mine water inrush, where the computational cost is reduced significantly while the accuracy is acceptable. To solve the control equations of the open channel flow and full channel flow efficiently, the lattice Boltzmann method is adopted to simulate the spatio-temporal evolution of the water inrush. Different from the previous studies, the spatio-temporal evolution of the water inrush is taken into account, which is closer to the actual case. The escape speed is not static, which is affected by the water depth dynamically; meanwhile, the effect of the physical energy reduction is considered. To validate the dynamic escape path optimization model based on the spatio-temporal evolution of the coal mine water inrush, three case studies are conducted. In the first case, there is one water inrush point and one person, while in the second case, there are two water inrush points and four persons; the third case is an actual coal mine with multiple water inrush points. We defined two indicators to evaluate the risk of the escape path quantitatively; they are the window escape time and rescue priority. By conducting the dynamic programming of the escape path, the optimal escape path is selected, where the effectiveness of the dynamic escape path optimization model is validated. The present work is helpful in reducing the risk of coal mine water inrush and improving the safety of the early warning system. Full article

Water inrush disasters pose a serious threat during tunnel construction. Accurately evaluating their evolution process is essential for timely prevention and risk mitigation. Given the staged nature of seepage-instability-induced inrushes and the sensitivity of borehole resistivity imaging to water-bearing anomalies, this study explores the use of borehole resistivity methods to monitor the evolution of such events. A four-stage geoelectrical evolution model is developed based on the characteristics of inclined fault-related water inrushes. A time-lapse evaluation method combining least squares inversion and resistivity ratio analysis is proposed to assess the inrush process. Numerical simulations show that this method achieves a localization error below 2 m for inclined water-conducting channels. Across the four stages, the resistivity ratio of the channel ranges from 0.65 to 1.40, capturing the three-dimensional expansion of the inrush pathway. These findings confirm that borehole resistivity imaging effectively characterizes the evolution of water inrush disasters and supports early warning and mitigation strategies. Full article

Frequent water and mud inrush accidents during karst tunnel construction severely impact tunnel construction safety, environmental sustainability, and the long-term use of infrastructure. Therefore, conducting practical risk assessment for karst tunnel water and mud inrush is crucial for promoting sustainable practices in tunnel engineering, as it can mitigate catastrophic events that lead to resource waste, ecological damage, and economic loss. This paper establishes an improved weighted cloud model for karst tunnel water and mud inrush risk to evaluate the associated risk factors. The calculation of subjective weight for risk metrics adopts the ordinal relationship method (G1 method), which is a subjective weighting method improved from the analytic hierarchy process. The calculation of objective weight employs the improved entropy weight method, which is superior to the traditional entropy weight method by effectively preventing calculation distortion. Game theory is applied to calculate the optimal weight combination coefficient for two computational methods, and cloud model theory is finally introduced to reduce the fuzziness of the membership interval during the assessment process. This study applied the established risk assessment model to five sections of the Furong Tunnel and Cushishan Tunnel in Southwest China. The final risk ratings for these sections were determined as “High Risk,” “High Risk,” “Medium Risk,” “High Risk,” and “Moderate Risk”, respectively. These results align with the findings from field investigations, validating the effectiveness and reliability of the cloud model-based mud and water outburst risk assessment using combined weighting. Compared to traditional methods such as fuzzy comprehensive evaluation and entropy weighting, the evaluation results from this study’s model demonstrate higher similarity and reliability. This provides a foundation for assessing mud and water outburst hazards and other tunnel disasters. Full article

Mine water inrush is a significant environmental catastrophe during the coal mining process, and the timely discrimination of the source of water inrush is the key to ensuring safe production in coal mines. This work suggests a mine water inrush—belief rule base (MWI-BRB) source discrimination model to overcome the interpretability and performance issues with conventional models. MWI-BRB firstly automatically constructs the reference values of prerequisite attributes using the Sum of Squared Errors—K-means++ algorithm, which effectively combines expert knowledge and data-driven methods, and solves the limitation of the traditional belief rule base model relying on specialist knowledge. Secondly, the hierarchical incremental structure solves the rule explosion problem caused by complex features while using XGBoost to select features. Finally, in the inference process, the model adopts an evidential reasoning algorithm to realize transparent causal inference, guaranteeing the model’s interpretability and transparency. The Penalized Covariance Matrix Adaptation Evolution Strategy algorithm optimizes the model parameters to increase the discriminative accuracy of the model even more. Experimental results on a real coal mine dataset (a total of 67 samples from Hebei, China, covering four water inrush sources) demonstrate that the proposed MWI-BRB achieves 95.23% accuracy, 95.23% recall, and 95.36% F1-score under a 7:3 training–testing split with parameter tuning performed via leave-one-out cross-validation. The near-identical values across accuracy, recall, and F1-score reflect the balanced nature of the dataset and the robustness of the model across different evaluation metrics. Compared with baseline models, MWI-BRB’s accuracy and recall are 4.78% higher than BPNN and 9.52% higher than KNN, RF, and XGBoost; its F1-score is 4.85% higher than BPNN, 10.64% higher than KNN, 10.19% higher than RF, and 9.65% higher than XGBoost. Moreover, the model maintains high interpretability. In conclusion, the MWI-BRB model can realize efficient and accurate water inrush source discrimination in complex environments, which provides a feasible technical solution for the prevention and control of mine water damage. Full article