Longwall Coal Mining Research Articles

Three-Dimensional Physical Test Study on the Overburden Breaking Behavior of Non-Penetrating Pre-Splitting in Small-Coal-Pillar Roadway Roofs

In longwall coal mining, significant deformation of small-pillar roadways presents challenges for the safe and efficient retreat of mining panels. Non-penetrating directional pre-splitting alters the roof structure of these roadways and effectively manages their stability under high stress during mining operations. In this study, a three-dimensional experimental model for the non-penetrating pre-splitting of small-coal-pillar roadway roofs was established, the apparent resistivity change in the rock layer during mining of the working face was determined, the propagation law of high-frequency electromagnetic waves in the overlying rock was studied, and the stress distribution law of the surrounding rock was investigated. After non-penetrating pre-splitting in the roof, the apparent resistivity change rate of the overlying rock increased and the electromagnetic waveform exhibited scattering and diffraction, forming a short cantilever beam. After mining, the stress in the adjacent mining panel gateway reduced, resulting in a pressure relief effect on the surrounding rock. These findings were further validated through field application, where the overall deformation of the roadway was reduced by 57%. The research results shed light on the management of roof control in small-coal-pillar roadways and the rational determination of non-penetrating pre-splitting parameters.

The Detectability of Post-Seismic Ground Displacement Using DInSAR and SBAS in Longwall Coal Mining: A Case Study in the Upper Silesian Coal Basin, Poland

The Upper Silesian coal basin (USCB) in Poland faces significant ground deformation issues resulting from mining activities conducted without backfill, which can persist for years. These activities can cause damage to surface structures and phenomena such as induced seismicity. Ground deformations can be monitored using differential synthetic aperture radar interferometry (DInSAR). However, various DInSAR approaches have their own advantages and limitations, particularly regarding accuracy and atmospheric filtering. This is especially important for high-frequency displacement signals associated with seismic activity, which can be filtered out. Therefore, this study aims to assess the detectability of mining-induced seismic events using interferometric techniques, focusing on the USCB area. In this experiment, we tested two InSAR approaches: conventional DInSAR without atmospheric filtering and the small baseline subset (SBAS) approach, where the atmospheric phase screen was estimated and removed using high-pass and low-pass filtering. The results indicate that, in most cases, post-seismic ground displacement is not detectable using both methods. This suggests that mining-related seismic events typically do not cause significant post-seismic ground displacement. Out of the 17 selected seismic events, only two were clearly visible in the DInSAR estimated deformation, while for four other events, some displacement signals could neither be definitively confirmed nor negated. Conversely, only one seismic event was clearly detectable in the SBAS displacement time series, with no evidence of induced tremors found for the other events. DInSAR proved to be more effective in capturing displacement signals compared to SBAS. This could be attributed to the small magnitude of the tremors and, consequently, the small size of the seismic sources. Throughout the investigated period, all registered events had magnitudes less than 4.0. This highlights the challenge of identifying any significant influence of low-magnitude tremors on ground deformation, necessitating further investigations. Moreover, SBAS techniques tend to underestimate mining displacement rates, leading to smoothed deformation estimates, which may render post-seismic effects invisible for events with low magnitudes. However, after an in-depth analysis of the 17 seismic events in the USCB, DInSAR was found to be more effective in capturing displacement signals compared to SBAS. This indicates the need for significant caution when applying atmospheric filtering to high-frequency displacement signals.

Study on the Influence of Grouting Treatment on the Movement and Deformation of Surface in Longwall Coal Mining Goaf Areas

Study on the Influence of Grouting Treatment on the Movement and Deformation of Surface in Longwall Coal Mining Goaf Areas

Study on Failure Behaviors of Roofs with Varying Thicknesses in Longwall Coal Mining Working Face

Study on Failure Behaviors of Roofs with Varying Thicknesses in Longwall Coal Mining Working Face

Development of a Dynamic Prediction Model for Underground Coal-Mining-Induced Ground Subsidence Based on the Hook Function

Underground coal-mining-induced ground subsidence deformation is a common geological disaster impacting buildings, transportation and water supplies. Models predicting ground subsidence dynamically with high precision are important for the prevention of damage derived from ground subsidence. In this paper, the Hook function is utilized to develop a model describing the velocity of ground subsidence due to underground coal mining. Based on the subsidence velocity model, a dynamic subsidence model is established by taking an integral of the velocity model. Coefficients of the model, which depend on maximum subsidence, maximum subsidence velocity and the time corresponding to the maximum subsidence velocity, are related to the geological and mining conditions of the coal seam being investigated. A Levenberg–Marquardt-algorithm-based method is also proposed to calculate the optimal model coefficients based on subsidence velocity observations. Four continuously operating Global Navigation Satellite System (GNSS) stations were constructed above a typical longwall coal mining working face in the Jining mining area, China. These GNSS stations collected subsidence observations over two years, which were used to validate the developed prediction model. The results show that the root-mean-square (RMS) of the model-predicted ground subsidence error is 56.1 mm, and the maximum relative error is 2.5% for all four GNSS stations, when the ground subsidence is less than 6000 mm.

A novel numerical modeling method for studying the failure mechanism of the main roof with different thicknesses in longwall coal seam mining

A novel numerical modeling method for studying the failure mechanism of the main roof with different thicknesses in longwall coal seam mining

Major Issues Related to Underground Longwall Coal Mining Automation

Major Issues Related to Underground Longwall Coal Mining Automation

Straightness Measurement Based on FOG-IMU and Shearer Motion Constraints for Longwall Coal Mining

Straightness measurements of fully mechanized coal faces are a core requirement for intelligent, comprehensive coal mining. In coal mining, using an inertial measurement unit (IMU) assisted by an odometer for straightness measurement is vital for automating longwall mining. IMUs are less vulnerable to dim and harsh underground mining conditions. However, IMU divergence cannot be controlled solely by the forward velocity obtained from the odometer. To address this problem without external sensors, this paper proposes a straightness measurement method based on a fiber optic gyroscope-IMU/odometer and shearer motion constraints. The motion of the shearer is constrained to correct the pitch and roll attitude angle errors in strapdown inertial navigation solution (SINS) attitude solutions. An extended Kalman filter was established to combine the SINS and dead reckoning using the output from the odometer. Finally, the position estimation obtained by Kalman filter fusion was converted into straightness. An experiment based on a custom-built test rail demonstrated that the proposed algorithm effectively improved the accuracy of straightness measurements in multiple cutting cycles. The error of the results in the horizontal plane was reduced by 45% compared to the traditional IMU/odometer method. This study is important in promoting the unmanned and intelligent development of China’s coal industry.

An exploration of improving the stability of mining roadways constructed in soft rock by roof cutting and stress transfer: A case study

In the confinement of traditional supports, reinforced supports are often used to control the deformation of roadways constructed in soft rock. Due to the failure to weaken the factors that induce deformation at the source, the roadway remains damaged after the restoration period. To this end, taking inspiration from roof cutting and pressure relief concepts, the protection mechanism of stress transfer in mining roadways constructed in soft rock of longwall remaining coal pillars was studied in the context of a typical coal mine. Unlike the technical scheme of gob-side entry retaining, no components are added in this study. The roof cutting and coal mining progress are consistent to ensure the integrity of the roadway in front of the longwall coal mining face (LCMF). The effect of the roof-cutting parameter on the roadway is studied via numerical simulations, and the optimal parameters are subsequently applied to similar material simulation experiments. It was found that roof cutting relieved the mechanical connection between the gob roof and the roadway roof, and the high-stress area was transferred from the roadway roof to the front of the LCMF. Roof cutting diminished the abutment stress in the surrounding rock in the area of intense dynamic pressure in front of the LCMF (average reduction of 12.57 %), which effectively improved the stability of the roadway. The roof cutting impaired the traction effect of the roadway roof deformation behind the LCMF on the strata ahead and effectively reduced the roadway deformation (27.3 % reduction) and coal pillar deformation (15.7 % reduction). On-site practice has demonstrated the effectiveness of this research, and the results of this research provide a new idea for preventing the destruction of roadways constructed in soft rock.

Using CO2 Fracturing to Weaken Roofs During the Initial Phase of Longwall Coal Mining

Using CO2 Fracturing to Weaken Roofs During the Initial Phase of Longwall Coal Mining

Mechanism and control of deformation in gob-side entry with thick and hard roof strata

Deformation of gob-side entries has always been a critical concern for ensuring stability in longwall coal mines. This paper addresses the significant deformation and support challenges that arise in thick and hard roof longwall faces (THRLF) due to dynamic pressure. The study aims to elucidate the characteristics and mechanisms of deformation during the retreat of the longwall face. The research findings indicated that the primary cause of deformation was the combination of advanced abutment stress resulting from longwall face mining and the movement of the lateral roof over the chain pillar. To mitigate this issue, we propose a deformation control method known as cutting off the lateral roof (COLR) over the chain pillar. Simulation results demonstrate a significant reduction in roof stress and deformation of the gob-side entry after implementing the lateral roof-cutting technique. These findings provide valuable guidance for effectively managing deformation in gob-side entries, particularly when dealing with thick and hard roof strata.

Fractal Characteristics of Overburden Rock Fractures and Their Impact on Ground Fissures in Longwall Coal Mining

Ground fissures are generated during the coal mining process due to overlying strata migration, which provides gas and water seepage channels and usually contributes to coal mining accidents in shallow buried coal seams with larger mining height working faces. Thus, the evolution features of ground fissures in large mining height working faces and shallow buried coal seams were explored by considering field observation data, similar simulation, and numerical simulations. The results show that the weathered rock layer above the thin bedrock inhibits fracture growth caused by coal mining. Overlying strata fracture expansion can be quantitatively divided into three stages based on fractal dimension: the overburden fracture formation stage, the overburden deformation fracture expansion stage, and the overburden fracture stable development stage. The movement deformation region of the ground fissure can be described by three characteristic zones: the boundary tension zone, the central compression zone, and the central dynamic tension and compression zone. Central dynamic fissures usually have 3–5 fissure counts with 2–5 m intervals between each group of fissures; central fissures develop twice from open to closed widths; the time period for two central fissures to reach their with maximum widths is 11–20 days; and border fissures expand rapidly with maximum values in a time period of 5–6 days.

The Process of Developing Model Research for the Technology of Obtaining Energy Resources

The current problems associated with the maintenance of hard coal longwall mining depend on the application or use of extraction technologies. In order to make the best use of these technologies, a new approach based on simulation studies is necessary. This paper aims to develop a mathematical model for the powered roof support’s operation. The three groups of professionals involved in the testing of the roof support were involved in the work on changing the hydraulic system of the powered roof support stand. These professionals were powered roof support’s designers, researchers and users. The research subject was the development of a mathematical model as a starting point for conducting simulations. The model is based on d’Alembert’s principle and the equation of the balance of flow rates. Based on the developed model, it is possible to determine the pressure in the space under the piston of the hydraulic prop. The results obtained in the simulations are the basic assumptions for the development of a prototype that would solve the current problems in the hydraulic systems of powered roof supports. The adopted research methodology assumed the development of a mathematical model, simulation in the MATLAB environment and verification of the model on a test stand. The obtained results of simulation tests based on the developed mathematical model were confirmed in bench tests. Simulation and bench tests determined the correctness of the assumptions made for the development of the prototype model. Based on the analysis of the results, the nature of the work of the future prototype has been predetermined. The next stage will be the testing of the prototype, which is to be included in the hydraulic system of the prop of powered roof support in the future. The model mentioned before is the baseline model, and it will be modified depending on the application of the future design in real conditions. Simulation studies of powered roof support will allow the structure that is used currently to be optimised, so as to adapt it to increasingly difficult working conditions.

Multifactorial analysis of a gateroad stability at goaf interface during longwall coal mining – A case study

Purpose. Creating a generalized algorithm to account for factors (coal seam thickness, enclosed rock mechanical properties, the dimension and bearing capacity of artificial support patterns) causing a gateroad state under the effect of longwall face and goaf. Methods. The assessment of the gateroad stability is based on numerical simulation of the rock stress-strain state (SSS). The finite element method is used to find out the changes in the SSS of surrounding rocks at various stages of longwall mining. The elastic-plastic constitutive model and Hoek-Brown failure criterion implemented in codes RS2 and RS3 (Rocscience) are applied to determine rock displacements dependently on the coal seam thickness, enclosed rock strength, width and strength of artificial support (a packwall comprised of hardening mixture “BI-lining”). To specify the mechanical properties of the packwall material a series of experimental tests were conducted. A computational experiment dealing with 81 combinations of affecting factors was carried out to estimate the roof slag and floor heaving in the gateroad behind the longwall face. A group method of data handling (GMDH ) is employed to generalize the relationships between rock displacements and affecting factors. Findings. The roof-to-floor closure in the gateroad has been determined at the intersection with the longwall face and goaf dependently on the coal seam thickness, enclosed rock strength, width of the packwall, and strength of hardening material. It is revealed that the support material gains the strength value of 30 MPa on the 3rd day from its beginning to use which is fully corresponding to the requirements of protective element bearing capacity. The possibility of using untreated mine water to liquefy the mixture is proved, that allows simplifying and optimizing the solute mixing and pumping technology. Originality. This study contributes to improving the understanding of the factors that influence the stability of underground mining operations and highlights the importance of utilizing numerical simulations in optimizing mining designs. The impact of each factor on the resulting variable (decrease in cross-section of gate road by height) based on the combinatorial algorithm of structural identification of the model is estimated as follows: the packwall width is 48%, the thickness of coal seam is 25%, the strength of enclosing rocks is 23%, and the strength of the packwall material is 4%. Practical implications. The findings provide stakeholders with a technique to determine reasonable parameters for support and protective systems, and the predictive model developed can be used to mitigate potential instability issues in longwall mining excavations. The results have implications under similar geological settings and can be valuable for mine design and optimization in other regions.

Effects of Ni-based composite coatings on failure mechanism and wear resistance of cutting picks on coal shearer machine

The performability and wear resistance of the cutting picks play an important role in the extraction operation of mining machinery especially drum shearers in longwall coal mines. Tungsten carbide tip fracture and removal, and severe wear of the pick body are the major failures that affect the performance of these picks. The coating could be a proper solution for strengthening the coal-cutting tools and extension of their useful life. In this paper, a Ni-based ultrafine coating, NiBSiFeWC, deposited by laser-cladding technique, has been applied to improve the wear resistance and mechanical properties of the coal-cutting picks. All cutting tests were carried out on a drum shearer machine and on a real-scale operation, which makes the study much more realistic and effectively applicable for advanced tools’ developments in mechanized longwall mines. The archived results show that NiBSiFeWC coating reduced the tool wear rate by about 50%.

Estimation of in-situ rock strength from borehole geophysical logs in Australian coal mine sites

This study aims to improve the conventional empirical rock strength estimation method that is widely adopted in the Australian coal mining industry and provide more accurate rock uniaxial compression strength (UCS) predictions based on artificial neural network (ANN) models. 274 laboratory-measured UCS data (sample dimension: 60 mm (diameter) × 150 mm (height)) were collected from two longwall coal mines in Australia, along with the four geophysical logs (sonic, gamma, neutron, and porosity logs) and rock density of the tested core specimens. A two-layer ANN model was developed from these data based on the Levenberg–Marquardt algorithm as a base model. As compared to conventional sonic-UCS fitting equations, the mean percentage error, root mean squared error and maximum absolute error of the proposed ANN model were reduced from 34.27%, 15.23 MPa and 70.66 MPa to 20.67%, 11.02 MPa and 47.66 MPa, respectively. Further investigations were conducted by splitting the dataset based on rock lithology and mine locations, and separate ANN models were developed based on the divided subsets. Both lithology-specific and site-specific models exhibited improved estimation accuracy in comparison to the base model, indicating lithology and local geological conditions could considerably affect the estimation accuracy. Among the three types of models, the lithology-specific models yielded the most accurate predictions over the 274 data (MPE: 17.55%; RMSE: 8.84 MPa), followed by the site-specific models and the base model in descending order. Overall, all three models significantly outperformed the current empirical methods adopted in the studied mine sites. The outcomes of this study could provide more accurate UCS predictions for further geotechnical analysis in underground constructions, such as tunnel stability analysis and estimating in-situ stresses based on borehole breakout.

Overlying Strata Dynamic Movement Law and Prediction Method Caused by Longwall Coal-Mining: A Case Study

The surface subsidence caused by underground mining is a spatiotemporal process. The impact of mining on surface structures (houses, highways, railways, dikes, etc.) and structures in rock strata (shafts, roadways, chambers, etc.) is a dynamic process. It is necessary to study the dynamic movement law of the surface and overlying strata in the mining process of the working face to predict the extent of the impact of mining on the aforementioned structures. It provides a reference for pre-reinforcement and post-mining treatment. This paper studies the variation of surface dynamic movement based on the survey line above the working face of Peigou Coal Mine. The numerical simulation model of the overlying strata dynamic movement is established to study the dynamic movement law of rock strata with different depths, and the fitting function of surface and overlying strata dynamic movement is determined. Finally, the subsidence velocity prediction function of the major section of the surface and overlying strata in the Peigou Coal Mine is established. The accuracy of this prediction function is demonstrated by contrasting the subsidence and subsidence velocity curves of the surface subsidence basin survey line with the numerical model. In this paper, a numerical simulation method for the dynamic movement of the surface and overlying strata and a function for predicting the subsidence velocity on the strike major section are established, which provides an important theoretical reference for the dynamic protection of the structures on the surface and in the overlying strata.

Multisensor Data-Fusion-Based Gas Hazard Prediction Using DSET and 1DCNN for Underground Longwall Coal Mine

The combustible and noxious gases are among the prominent issues affecting the life and the mining operations of underground coal mines (UCMs). Commonly adopted hazard monitoring methodologies in UCM are fuzzy, rule-based systems, statistical methods, and other expert systems, but these models are not reliable for highly complex and nonlinear systems. The neural network’s ability to learn and create nonlinear relationships is beneficial to making hazard prediction models. Especially, convolutional neural networks (CNNs) auto feature extraction capabilities to make it more suitable for the task. But, UCM’s harsh and crucial environment may result in sensor malfunctioning and faults, giving rise to data uncertainty. Like other data-driven models, data uncertainty significantly affects CNN’s performance. This study involves designing an effective and reliable gas hazard monitoring system using a hybrid of Dempster–Shafer evidence theory (DSET)-based filter and one-dimensional CNN (1DCNN) classifier. The novelty of this study is the integration of DSET and 1DCNN to predict the UCM hazard more reliably, even in malfunctioning node scenarios. Inherent usage limitations on traditional communication techniques restrict the application of cloud-based machine learning (ML) methods and this study use novel edge implementation of the filter and the classifier using edge ML (EML) technology. The proposed model’s hazard classification accuracy is 99.6%, even in the faulty node scenarios, where the traditional approaches fail.

Quantitative assessment of the spatio-temporal correlations of seismic events induced by longwall coal mining

Rock failure process as a natural response to mining activities is associated with seismic events, which can pose a potential hazard to mine operators, equipment and infrastructures. Mining-induced seismicity has been found to be internally correlated in both time and space domains as a result of rock fracturing during progressive mining activities. Understanding the spatio-temporal (ST) correlation of mining-induced seismic events is an essential step to use seismic data for further analysis, such as rockburst prediction and caving assessment. However, there are no established methods to perform this critical task. Input parameters used for the prediction of seismic hazards, such as the time window of past data and effective prediction distance, are determined based on site-specific experience without statistical or physical reasons to support. Therefore, the accuracy of current seismic prediction methods is largely constrained, which can only be addressed by quantitively assessing the ST correlations of mining-induced seismicity. In this research, the ST correlation of seismic event energy collected from a study mine is quantitatively analysed using various statistical methods, including autocorrelation function (ACF), semivariogram and Moran's I analysis. In addition, based on the integrated ST correlation assessment, seismic events are further classified into seven clusters, so as to assess the correlations within individual clusters. The correlation of seismic events is found to be quantitatively assessable, and their correlations may vary throughout the mineral extraction process.

Prediction of mining-induced subsidence at Barapukuria longwall coal mine, Bangladesh

It is essential to predict the mining-induced subsidence for sustainable mine management. The maximum observed subsidence having a noticeable areal extent due to Northern Upper Panels (NUP) and Southern Lower Panels (SLP) at the Barapukuria longwall coal mine is 5.8 m and 4.2 m, respectively, after the extraction of a 10 m thick coal seam. The mining-induced subsidence was simulated by the Displacement Discontinuity Method. The numerical model considered the effects of the ground surface, mining panels, faults, and the dyke. The predicted and the observed subsidence due to the mining of NUP and SLP were compared by varying Young's modulus, and the 0.10 GPa Young's modulus was found to be the best match in the geo-environmental condition. The effects of the faults and the dyke in the calculation were negligible. Future subsidence was predicted by considering 30 m extraction of the thick coal seam as 15.7–17.5 m in NUP and 8.7–10.5 m in SLP. The vulnerable areas demarcated considering the tilt angle and extensile strain might extend up to the coal mine office area and some villages.