Exploration
Reza Moezzi nasab; Alireza Arab Amiri; Abolghasem Kamkar-Rouhani; Meysam Davoodabadi Farahani
Abstract
Mineral prospectivity modeling in structurally complex and vertically heterogeneous geological systems requires analytical frameworks capable of capturing nonlinear feature interactions and depth-dependent variability. This study evaluates the predictive performance of a deep self-attention neural network ...
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Mineral prospectivity modeling in structurally complex and vertically heterogeneous geological systems requires analytical frameworks capable of capturing nonlinear feature interactions and depth-dependent variability. This study evaluates the predictive performance of a deep self-attention neural network within a fully 3D mineral prospectivity modeling framework applied to the Chah-Mousa copper deposit, Iran. The modeling domain was discretized into twenty-one independent elevation levels to assess depth-consistent predictive behavior. Model performance was evaluated using ROC–AUC analysis, confusion-matrix-derived metrics, and success-rate curve assessment. The deep self-attention model achieved a mean ROC–AUC of approximately 0.83, indicating strong discriminative capability between mineralized and non-mineralized domains. Averaged across elevation slices, classification performance remained stable (Accuracy ≈ 0.83, Precision ≈ 0.69, Recall ≈ 0.75, F1-score ≈ 0.72), demonstrating vertical generalization and resistance to shallow overfitting. Success-rate analysis revealed that more than 50% of known mineralized occurrences are concentrated within the top 10% of predicted prospectivity areas, confirming strong ranking efficiency for exploration prioritization. The probabilistic outputs exhibit spatial coherence aligned with structural corridors and alteration zones, indicating that the attention mechanism effectively captures nonlinear geological relationships. The results demonstrate that deep self-attention architectures provide statistically robust, depth-consistent, and operationally meaningful predictions for 3D mineral exploration targeting in structurally controlled copper systems.
Rock Mechanics
Mohammad-Taghi Hamzaban; Alireza Chehreghan; Roozbeh Geraili Mikola
Abstract
Back analysis of tunnel excavation plays a fundamental role in calibrating geomechanical parameters using field monitoring data. However, conventional direct back analysis procedures remain computationally demanding and highly dependent on operator supervision. This study presents an integrated Finite ...
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Back analysis of tunnel excavation plays a fundamental role in calibrating geomechanical parameters using field monitoring data. However, conventional direct back analysis procedures remain computationally demanding and highly dependent on operator supervision. This study presents an integrated Finite Difference Method–Genetic Algorithm (FDM–GA) framework for automated tunnel back analysis, implemented entirely within the FLAC environment using the embedded FISH programming language. The proposed approach eliminates the need for external optimization software and data transfer between numerical and artificial intelligence platforms. A simplified genetic algorithm is coupled directly with finite difference simulations to iteratively minimize the discrepancy between measured and computed tunnel convergences. The framework incorporates constrained parameter optimization, automated handling of non-convergent models, and a robust convergence-based stopping criterion that avoids predefined error thresholds. Verification is performed using two synthetic plane-strain tunnel models representing stiff cohesive soil and dense granular material. Six unknown parameters (ρ, E, ν, c, φ, and K0) are back-calculated using only three convergence measurements. Results from multiple independent runs demonstrate stable convergence toward very small error values (on the order of 10-6–10-5) and consistent reproduction of synthetic monitoring data. The method successfully narrows broad initial parameter ranges and produces multiple acceptable parameter sets, explicitly acknowledging the non-uniqueness inherent in back analysis problems. The developed FDM–GA framework provides an efficient, self-contained, and adaptable tool for practical tunnel back analysis applications.
Exploitation
Hassan Bakhshandeh Amnieh; Ebrahim Arefmand; Abbas Majdi
Abstract
The Power deck blasting technique is widely used in open-pit and underground mines to optimize explosive energy for effective rock fragmentation while minimizing adverse effects. This study examines the influence of primer location and air column length on ground vibration and limestone rock mass damage ...
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The Power deck blasting technique is widely used in open-pit and underground mines to optimize explosive energy for effective rock fragmentation while minimizing adverse effects. This study examines the influence of primer location and air column length on ground vibration and limestone rock mass damage through field tests and numerical simulations at the Nardaghi limestone mine. A two-hole blast using the Power deck method was performed, with vibrations recorded by a three-axis seismograph. The maximum particle velocity reached 70.22 mm/s at 11 meters from the blast. Field inspections indicated that damage was limited to areas around the blast hole openings. Numerical results show that placing the primer at the bottom of the explosive column reduces ground vibration by 37% compared to middle or top positions, whereas the top primer location causes greater surface damage. Damage at the blast hole bottom was comparable across all primer locations. Fixing the primer at the bottom, the effect of air column length (0.4 to 2 meters) on vibration and damage was studied. Increasing the air column length up to 1.4 meters increased vibration, but longer lengths led to significant vibration reduction. Maximum rock mass damage occurred at an air column length of 0.6 meters, indicating optimal energy transfer. The results highlight the critical effects of primer position and air column length on blasting outcomes. The best primer placement is at the bottom of the explosive column, and the optimal air column length is 0.6 meters to balance vibration control and fragmentation efficiency.
Mineral Processing
Faraz Soltani; Hadi Naghavi; Hossna Darabi; Arsalan Parvaneh; Mobin Chagh Siah
Abstract
The main objective of the present study is to evaluate the feasibility of using gravity separation methods, including heavy bromoform liquid, spiral, and shaking table, for the primary concentration of gold from low-grade Siah Jangal ore (Sistan and Baluchistan Province, Iran). Characterization studies ...
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The main objective of the present study is to evaluate the feasibility of using gravity separation methods, including heavy bromoform liquid, spiral, and shaking table, for the primary concentration of gold from low-grade Siah Jangal ore (Sistan and Baluchistan Province, Iran). Characterization studies indicated that gold is mainly present as inclusions or within the lattice of pyrite and siderite minerals. For this reason, the potential of gravity separation methods using bromoform heavy liquid with a density of 2.89 g/cm³ was initially investigated in three size fractions: +1180, -1180+500, and -500 µm, where the maximum grade of 2.78 g/t with a recovery of 76.7% was obtained. The results showed that in coarser size ranges, both the grade and recovery of gold decreased. In spiral tests, the highest grade and recovery of gold were 2.33 g/t and 62.58%, respectively. The results of the shaking table experiments showed that, given a concentrate-to-feed weight ratio of 12%, a grade of 2.54 g/t could be achieved with a recovery of 73.81%, which, by eliminating a significant amount of tailings (about 88% of the feed), significantly reduces the operating expenses of subsequent processes (including flotation, oxidation, and leaching). It can be concluded that gravity methods, especially the shaking table, can serve as low-risk, low-cost, and environmentally friendly approaches for concentrating low-grade gold ores.
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.
Rock Mechanics
Ebrahim Ebrahimnezhad Sadigh; Kazem Badv
Abstract
Understanding the rheological behavior of soft marine and lacustrine sediments is crucial for the success of geotechnical and civil engineering projects. Coastal and offshore structures such as artificial islands, lake causeways, piers, and oil platforms directly interact with these sediments. Their ...
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Understanding the rheological behavior of soft marine and lacustrine sediments is crucial for the success of geotechnical and civil engineering projects. Coastal and offshore structures such as artificial islands, lake causeways, piers, and oil platforms directly interact with these sediments. Their safe and stable performance depends on accurate characterization of sediment behavior under complex loading conditions. This study investigates the rheological properties of soft sediments from Lake Urmia, Iran, through a combined experimental and numerical approach. Two key tests were performed: extrusion tests and unconfined compression tests. The extrusion tests were conducted on both undisturbed and remolded samples under various conditions, including different loading rates, moisture contents, and discharge orifice sizes. For the numerical simulation, the Bonded Particle Discrete Element Method (BPDEM) was employed, with the model's micro-parameters calibrated using experimental extrusion test data. The numerical results showed excellent agreement with experimental data: the force-displacement curve was replicated with less than 2% error. The calibrated model also successfully simulated the unconfined compression test, reproducing the stress-strain curve with less than 2% deviation from laboratory results. These findings demonstrate the accuracy of BPDEM in modeling soft sediment behavior. The results indicate that integrating laboratory methods with BPDEM modeling provides a powerful tool for analyzing soft sediments. This approach is particularly effective for Holocene and Late Pleistocene soft to ultra-soft sediments, offering reliable predictions of rheological and mechanical behavior in geotechnical applications.
Exploitation
Abbas Khajouei Sirjani; Farhang Sereshki; Mohammad Ataei; Mohammad Amiri Hossaini
Abstract
Rock fragmentation induced by blasting plays a critical role in the productivity and cost efficiency of open-pit mining operations. Among blast design strategies, air-deck blasting has been proposed as a technique to improve energy utilization by modifying the pressure–time characteristics within ...
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Rock fragmentation induced by blasting plays a critical role in the productivity and cost efficiency of open-pit mining operations. Among blast design strategies, air-deck blasting has been proposed as a technique to improve energy utilization by modifying the pressure–time characteristics within the blasthole. However, its performance under production-scale conditions and the reliability of numerical predictions remain insufficiently validated. This study presents an integrated field–numerical investigation of air-deck blasting at the Gol-e-Gohar Iron Ore Mine No. 1, Iran. Fragmentation characteristics were quantified using image-based particle size distribution (PSD) analysis of muck piles processed with Split-Desktop software. Characteristic fragmentation indices (D20, D50, and D80) were extracted to evaluate blast performance. Three-dimensional numerical simulations were performed using the LS-DYNA explicit finite element code to model stress-wave propagation, damage evolution, and fragmentation development for both conventional blasting and air-deck blasting configurations. Numerical models were calibrated using site-specific blasting geometry, explosive properties, and rock mass parameters derived from field measurements. The results show strong agreement between numerical predictions and field observations, with coefficients of determination exceeding 0.95 and RMSE values below 10%. Compared with conventional blasting, air-deck blasting produced finer and more uniform fragmentation, reducing D50 by approximately 10–15% and D80 by up to 18%. The improvement is primarily attributed to stress-wave reflection at the air gap and enhanced tensile crack propagation. The proposed field-validated numerical framework provides a practical tool for blast design optimization and demonstrates the potential of air-deck blasting to improve fragmentation efficiency in large-scale open-pit mining operations.
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.
