Original Research Paper
Rock Mechanics
P GANESAN; Ritesh D Lokhande; Siddhartha Roy; Hemant Agrawal
Abstract
Subsidence associated with underground coal mining is a significant geotechnical concern in many coal-producing regions. The extraction of coal over large areas from underground often leads to the collapse of overlying strata into the goaf, subsequently causing surface subsidence. The extent of this ...
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Subsidence associated with underground coal mining is a significant geotechnical concern in many coal-producing regions. The extraction of coal over large areas from underground often leads to the collapse of overlying strata into the goaf, subsequently causing surface subsidence. The extent of this subsidence varies widely across mines, depending on several factors, including mine geometry, geological discontinuities, physico-mechanical properties of the overlying strata, extraction method, seam thickness, and depth of working. Among these, the angle of draw (AoD) plays a critical role in delineating the subsidence-affected zone, particularly in underground coal mining. Accurate prediction of AoD is essential for safe mine planning and the mitigation of subsidence-related hazards. In the present study, a comprehensive field investigation was conducted to collect mine operational parameters from various underground coal mines. Using this dataset, Genetic Programming (GP) was employed to model the relationship between AoD and key mining and geological parameters. The developed GP model demonstrated a strong correlation between predicted and measured AoD values, with a coefficient of determination (R) = 0.7921, highlighting the model’s predictive capability. Additionally, a sensitivity analysis (SA) was performed to identify the most influential input parameters affecting AoD. The analysis indicated that, while all five input variables significantly impact AoD, the compressive strength of overlying strata exhibited the highest influence (sensitivity score = 0.98). The findings of this study provide a data-driven approach to predict the angle of draw in underground coal mines, offering valuable insights for improved mine design, extraction strategies, and surface infrastructure protection.
Original Research Paper
Exploration
Marco Antonio Cotrina Teatino; Jairo Jhonatan Marquina-Araujo; Jose Nestor Mamani-Quispe; Solio Marino Arango-Retamozo; Joe Alexis Gonzalez-Vasquez; Kevin Daniel Rondo-Jalca
Abstract
The classification of mineral resources significantly impacts mine planning, economic feasibility, and regulatory compliance. Despite its importance, such classification frequently depends on the subjective judgment of the Qualified Person (QP), owing to the absence of internationally standardized technical ...
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The classification of mineral resources significantly impacts mine planning, economic feasibility, and regulatory compliance. Despite its importance, such classification frequently depends on the subjective judgment of the Qualified Person (QP), owing to the absence of internationally standardized technical criteria for delineating resource categories. To mitigate this limitation, an innovative methodology integrating clustering based on Riemannian geometry with machine learning techniques was developed for mineral resource classification. A database of 5,654 composited samples from 185 diamond drill holes in a copper deposit in central Peru was utilized to classify 318,443 blocks. Copper grades were estimated through Ordinary Kriging (RMSE = 0.102; MAE = 0.069), generating geostatistical variables kriging variance, average distance to samples, and number of samples that served as input features for the classification. Clustering was performed using both classical KMeans and Riemannian KMeans, followed by spatial smoothing via XGBoost and Random Forest algorithms. Absolute coordinates were incorporated to address spatial discontinuities in classification outputs. The combination of the Riemannian model with Random Forest produced the highest classification performance, with a Silhouette index of 0.26 and a Davies-Bouldin index of 0.72. The resulting metal content was estimated at 4.24 Mt of copper at 0.44% grade (measured), 6.49 Mt at 0.34% Cu (indicated), and 7.68 Mt at 0.32% Cu (inferred), demonstrating close alignment with QP estimates while exhibiting improved spatial coherence. In summary, the Riemannian-based approach outperformed classical KMeans and conventional classification methods, providing a more robust, objective, and globally consistent alternative.
Original Research Paper
Exploration
Abdelhamid Bajadi; Driss El Azzab; Anas Driouch; Mohammed ouchchen; Mohammed Jalal TAZI
Abstract
The Bou Azzer–El Graara inlier, located in Morocco’s central Anti-Atlas, is well known for its significant cobalt mineralization, genetically associated with a Pan-African serpentinized ultrabasic ophiolitic massif. In this context, a structural study was conducted in the Aït Ahmane ...
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The Bou Azzer–El Graara inlier, located in Morocco’s central Anti-Atlas, is well known for its significant cobalt mineralization, genetically associated with a Pan-African serpentinized ultrabasic ophiolitic massif. In this context, a structural study was conducted in the Aït Ahmane area, situated at the eastern end of the Bou Azzer mining district, with the aim of analyzing structural lineaments, which constitute a fundamental tool in geological mapping and mineral exploration. The methodological approach is based on the interpretation of multispectral remote sensing data to map surface lineaments and compare them with structures observed underground. The processing applied to the Landsat 8 OLI imagery includes radiometric and atmospheric corrections, followed by principal component analysis (PCA), which enhances the discrimination of linear structures and allows the production of reliable lineament maps. In parallel, underground geological mapping was carried out in the F53 vein deposit, at two lower exploitation levels, to characterize mineralized structures at depth. The integration of surface and subsurface datasets highlights two main structural families. The first, trending N–S to NE–SW, is associated with cobalt-bearing structures hosted within diorites. The second, oriented NW–SE to WNW–ESE, corresponds to cobalt-mineralized tectono-lithological contacts between serpentinites, basic rocks, and diorites. The correlation between surface-mapped lineaments and deep-seated structures is significant, emphasizing the structural continuity between the surface and subsurface domains.
Original Research Paper
Environment
Tingze Li; Yu Wang; Genyuan Tan
Abstract
Effective gas drainage in coal mines necessitates the precise optimization of borehole parameters to reduce gas pressure and prevent gas outbursts. However, current drilling designs predominantly rely on field experience rather than site-specific quantitative analysis of geological conditions, leading ...
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Effective gas drainage in coal mines necessitates the precise optimization of borehole parameters to reduce gas pressure and prevent gas outbursts. However, current drilling designs predominantly rely on field experience rather than site-specific quantitative analysis of geological conditions, leading to limitations in adaptability. This study establishes a COMSOL-based multiphysics coupling model that integrates stress-permeability interactions, gas adsorption-desorption kinetics, and fracture-induced permeability evolution to evaluate the gas drainage performance of cross-measure boreholes in floor strata. Simulation results indicate that directional borehole spacing is the most influential factor: reducing the spacing from 25 m to 20 m significantly increases gas drainage efficiency by 31.4%, while extending the drainage duration from 90 days to 270 days expands the influence radius by more than 35%. In contrast, variations in borehole diameter (75-115 mm) and negative pressure (10-90 kPa) exert a negligible impact on gas pressure (with a variation of less than 5%), reflecting limited sensitivity. The optimal borehole location is determined to be at the lower boundary of the mining-induced fracture zone. A gradient layer analysis further confirms that the perforation depth should match the range of the plastic deformation zone (15-25 m). The proposed parametric optimization strategy provides a quantitative framework for directional drilling design, enabling the matching of borehole layout with the scale of fracture development. These findings contribute to enhancing the accuracy of gas control and the engineering adaptability of gas drainage systems under complex geological conditions.
Original Research Paper
Mineral Processing
Chourouk MENIAI; Mohamed BOUNOUALA; Raouf CHAABIA; CHAHRA SIFI; Rim AMATA
Abstract
Phosphate mining at Djebel Onk (Tébessa, Algeria) generates large volumes of solid wastes that occupy land, release dust, and contaminate surrounding environments. This study aims to characterize and valorize two types of dry tailings, namely +15 mm screening rejects and fines from pneumatic separation ...
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Phosphate mining at Djebel Onk (Tébessa, Algeria) generates large volumes of solid wastes that occupy land, release dust, and contaminate surrounding environments. This study aims to characterize and valorize two types of dry tailings, namely +15 mm screening rejects and fines from pneumatic separation (TSV), in order to reduce their environmental impact and recover residual phosphate. Samples were analyzed using particle size distribution, atomic absorption spectrometry (AAS), X-ray diffraction (XRD), and scanning electron microscopy coupled with energy-dispersive spectroscopy (SEM/EDS). Treatment tests included calcination (laboratory furnace, 700–1000 °C, 15–30 min) and direct flotation (Denver-type cell, with oleic acid and phosphoric acid as reagents).The results show that the +15 mm rejects and TSV fines contain 21.42 % and 23 % P₂O₅, respectively, while the richest fraction (-0.5 + 0.25 mm) reaches 28.99 % P₂O₅ with 1.01 % MgO. Calcination at 1000 °C for 30 minutes produced concentrates with 33.51 % P₂O₅ and near-complete CO₂ removal, whereas direct flotation yielded concentrates of ≈ 30 % P₂O₅ with MgO < 1 %. The novelty of this work lies in the combined application of calcination and flotation, which demonstrates their complementarity for efficient recovery of phosphate from dry tailings. These results confirm the potential for phosphate valorization while reducing environmental impacts and supporting more sustainable mining practices.Keywords: Phosphate, mining wastes, calcination, flotation, environmental management, Djebel Onk
Original Research Paper
Environment
Snežana Brajević; Aleksandar Simić; Vera Karličić; Nikola Milanović; Monika Stojanova; Blažo Lalević; Željko Dželetović
Abstract
Permanent mining generates substantial amounts of flotation tailings with highly unfavourable physical and chemical properties, often devoid of vegetation. Their stabilization relies on phytoremediation, particularly through the establishment of grass cover. Successful revegetation requires sufficient ...
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Permanent mining generates substantial amounts of flotation tailings with highly unfavourable physical and chemical properties, often devoid of vegetation. Their stabilization relies on phytoremediation, particularly through the establishment of grass cover. Successful revegetation requires sufficient nutrient availability and the activity of soil microorganisms that transform nutrients into plant-accessible forms. However, the interactions between plants, nutrients, and microflora during this process remain poorly understood. This study aimed to investigate the temporal dynamics and interrelationships within the plant–nutrient–microorganism system during the revegetation of flotation waste using four grass species—tall fescue, red fescue, meadow fescue, and perennial ryegrass. Plants were grown under controlled conditions on flotation tailings with different fertilizer treatments: organic (NPK 4:4:4) and mineral (NPK 20:20:20) fertilizers at varying concentrations (1% and 2% O; 0.25% and 0.5% M) and irrigation levels (50% and 75% of field water capacity). Microbial diversity (culturable bacteria, ammonifiers, fungi, and actinomycetes) was used as an indicator of remediation efficiency. Organic fertilization had the most pronounced effect, improving plant height, biomass yield, and microbial activity, particularly in tall fescue. Bacteria and ammonifiers responded positively to mineral fertilization under higher irrigation in red fescue and to organo-mineral treatment under lower irrigation in perennial ryegrass. The highest abundance of actinomycetes occurred under reduced irrigation in red fescue and perennial ryegrass. Overall, perennial ryegrass demonstrated the strongest correlation between cultivation conditions, microbial activity, and phytoremediation potential, highlighting its suitability for the ecological rehabilitation of flotation tailings.
Original Research Paper
Mineral Processing
Ayman M. Ibrahim; Han Wang; Dianwen Liu; Peilun Shen; Hassan A. Osman; Muhannad Alhaj; Mohamed A. Ibrahim; Misbah Khalil
Abstract
In this study, Pb²⁺ and STG were used as effective co-activation reagents before sodium sulfide treatment to assess their effect on smithsonite floatability. The flotation test results showed that sodium sulfide nonahydrate (SSN) and sodium diethyl dithiocarbamate (DDTC) concentrations significantly ...
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In this study, Pb²⁺ and STG were used as effective co-activation reagents before sodium sulfide treatment to assess their effect on smithsonite floatability. The flotation test results showed that sodium sulfide nonahydrate (SSN) and sodium diethyl dithiocarbamate (DDTC) concentrations significantly impacted floatability, achieving maximum recoveries of 89.32% and 93.19%, respectively. XPS analysis confirmed that Na₂S treatment introduced sulfur species onto the smithsonite surface, enhancing collector attachment and facilitating the formation of PbS and ZnS. FTIR analysis further substantiated that co-activation enhances DDTC adsorption via C=S vibrations, thereby increasing the number of active sites available for interaction with the collector relative to direct sulfidation. FESEM-EDS and AFM analysis at pH 9 confirmed that co-activation resulted in the formation of denser, cloud-like layers of PbS and ZnS on the surface. These layers improved flotation efficiency, increased hydrophobicity, and strengthened DDTC interaction, thus promoting flotation. Additionally, ToF-SIMS and EPMA analyses indicated higher Pb⁺ and S⁻ intensities in the co-activation system, confirming enhanced surface reactivity and substantiating the increased activity and diversity of sulfidation products. This study offers an effective approach to enhancing smithsonite flotation recovery by optimizing surface chemistry and collector attachment.
Original Research Paper
Exploitation
Shambhavi sinha; Anup Tripathi; Akhil Avchar; Mritunjay kumar
Abstract
Accurate assessment of rock mass quality in marble quarries remains challenging because conventional empirical classification systems are largely strength-dominated and insufficiently sensitive to discontinuity-controlled block instability. This study proposes a quarry-specific empirical framework, termed ...
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Accurate assessment of rock mass quality in marble quarries remains challenging because conventional empirical classification systems are largely strength-dominated and insufficiently sensitive to discontinuity-controlled block instability. This study proposes a quarry-specific empirical framework, termed the Marble Rock System (MRS), designed to explicitly capture structural, hydro-mechanical, and alteration-driven controls governing bench-scale stability in dimension stone marble quarries. The primary objective was to develop and validate an empirically grounded classification system using machine learning as an independent diagnostic tool rather than as a black-box predictor.A comprehensive geomechanical database comprising 85 quarry-scale records was developed from three active marble quarries in southern Rajasthan, India. Six physically interpretable parameters intact strength, weathering or serpentinization, joint frequency, joint surface condition, groundwater influence, and block stability were incorporated into the MRS framework. Supervised machine learning models, including artificial neural networks, support vector machines, and linear regression, were trained to predict independently derived factors of safety for validation. Model performance was evaluated using coefficient of determination, root mean square error, cross-validation, and classification metrics.Results show that MRS-based models achieved consistently higher predictive accuracy, improved class separability, and more stable generalization than models trained using conventional Rock Mass Rating inputs. Sensitivity analysis revealed that block stability and joint characteristics dominate stability prediction, while intact strength plays a secondary role. These findings confirm that marble quarry slope behaviour is primarily discontinuity-controlled. The proposed MRS provides a physically interpretable, empirically validated framework for quarry-scale stability assessment and offers a robust alternative to conventional classification systems for operational decision-making.
