Environment
H. Mahdiyanfar
Abstract
Detection of deep and hidden mineralization using the surface geochemical data is a challenging subject in the mineral exploration. In this work, a novel scenario based on the spectrum–area fractal analysis (SAFA) and the principal component analysis (PCA) has been applied to distinguish and delineate ...
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Detection of deep and hidden mineralization using the surface geochemical data is a challenging subject in the mineral exploration. In this work, a novel scenario based on the spectrum–area fractal analysis (SAFA) and the principal component analysis (PCA) has been applied to distinguish and delineate the blind and deep Mo anomaly in the Dalli Cu–Au porphyry mineralization area. The Dalli mineral deposit is located on the volcanic–plutonic belt of Sahand–Bazman in the central part of Iran. The geochemical data was transformed to the frequency domain using the Fourier transformation, and SAFA was applied for classification of geochemical frequencies and detection of geochemical populations. The very low-frequency signals in the fractal method were separated using the low-pass filter function and were interpreted using PCA. This scenario demonstrates that the Mo element has an important role in the mineralization phase in the very low-frequency signals that are related to the deep mineralization; it is an important innovation in this work. Then the Mo geochemical anomaly has been mapped using the inverse Fourier transformation. This research work shows that the high-power spectrum values in SAFA are related to the background elements and the deep mineralization. Two exploratory boreholes drilled inside and outside the deep Mo anomaly area properly confirm the results of the proposed approach.
A. Nouri Qarahasanlou; M. Ataei; R. Shakoor Shahabi
Abstract
Whether directly in the form of expenses or indirectly, the objective of maintenance in the mining industry is self-evident in time losses and loss of production. In this paper, the reliability-based maintenance is examined with a different insight than before. The system goes back to the Good As New ...
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Whether directly in the form of expenses or indirectly, the objective of maintenance in the mining industry is self-evident in time losses and loss of production. In this paper, the reliability-based maintenance is examined with a different insight than before. The system goes back to the Good As New (GAN) state or too Bad As Old (BAO) maintenance state; why so, the maintenance of the system shifts to the midrange state. On the other hand, the implementation of repairs is strongly influenced by the environmental factors that are known as the “risk factors”. Therefore, an analysis requires a model that integrates two basic elements: (1) incompleteness of the maintenance effect and (2) risk factors. Thus, an extensive proportional hazard ratio model (EPHM) is used as a combination of the Proportional Hazard Model (PHM) and the Hybrid Imperfect Preventive Maintenance model (HIPM) in order to analyze these elements. In this regards, four different preventive maintenance strategies are proposed. All four strategies are time-based including constant interval or periodic (the first and second strategies) and cyclic interval (the third and fourth strategies). The proposed method is applied for a Komatsu HD785-5 dump-truck in the Songun copper mine as a case study. The PM intervals with a mean value of risk factors for the four activities to reach the 80% reliability for the first and second strategies are about 5 and 48 hours. These intervals for the third strategy are calculated as 48.36, 11.58, 10.25, and 9.035, and for the fourth strategy are 5.06, 4.078, 3.459, and 1.92.
Ajay Kumar; Aditya Gupta; Yadvendra Pratap Singh; Monu Bhagat
Abstract
Land use (LU) is one of the most imperative pieces of cartographic information used for monitoring the mining environment. The extraction of land use data sets from remotely sensed satellite images has garnered significant interest in the mining region community. However, classification of LUs from satellite ...
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Land use (LU) is one of the most imperative pieces of cartographic information used for monitoring the mining environment. The extraction of land use data sets from remotely sensed satellite images has garnered significant interest in the mining region community. However, classification of LUs from satellite images remains a tedious task due to the lack of availability of efficient coal mining related datasets. Deep learning methods provide great leverage to extract meaningful information from high-resolution satellite images. Moreover, the performance of a deep learning classification approach significantly depends on the quality of the datasets. The present work attempts to demonstrate the generation of satellite-based datasets for the performance analysis of different deep neural network (DNN)-based learning algorithms in the LU classifications of mining regions. The mining regions are broadly classified into distinct regions based on visual inspection, namely barren land, built-up areas, waterbody, vegetation, and active coal mines. In our experimental work, a patch of 100 spatial samples for each of the five features is generated on three scales, as [1 × 1 × 3], [5 × 5 × 3], and [10 × 10 × 3]. Moreover, the effects of different scalabilities of the dataset on classification performances are also analyzed. Furthermore, this case study is implemented for the large-scale benchmark of satellite image datasets for mining regions. In the future, this work can be used to classify LU in the relevant study regions in real time.
M. Ansari; M. Hosseini; A. R. Taleb Beydokhti
Abstract
Rock abrasivity, as one of the most important parameters affecting the rock drillability, significantly influences the drilling rate in mines. Therefore, rock abrasivity should be carefully evaluated prior to selecting and employing drilling machines. Since the tests for a rock abrasivity assessment ...
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Rock abrasivity, as one of the most important parameters affecting the rock drillability, significantly influences the drilling rate in mines. Therefore, rock abrasivity should be carefully evaluated prior to selecting and employing drilling machines. Since the tests for a rock abrasivity assessment require sophisticated laboratory equipment, empirical models can be used to predict rock abrasivity. Several indices based on five known methods have been introduced for assessing rock abrasivity including rock abrasivity index (RAI), Cerchar abrasivity index (CAI), Schimazek’s abrasivity factor (F-abrasivity), bit wear index (BWI), and LCPC abrasivity coefficient (LAC). In this work, 12 rock types with different origins were investigated using the uniaxial compressive strength (UCS), Brazilian test for tensile strength, and longitudinal wave velocity and LCPC tests, and microscopic observations were made to obtain a correlation for estimating the LCPC abrasivity coefficient by conducting the conventional rock mechanics tests. Using the equivalent quartz content, velocity of longitudinal waves, and rock brittleness index, a linear correlation was obtained with a coefficient of determination (R2) of 93.3% using SPSS in order to estimate LAC.
Environment
Sehla Altaf; Kanwarpreet Singh; Abhishek Sharma
Abstract
The expansion and contraction properties of black cotton soil make it a challenging task to construct structures on it. Hence, modifying its expansion and contraction behavior is imperative to make black cotton soil appropriate for construction purposes. This study aims to assess the geo-technical properties ...
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The expansion and contraction properties of black cotton soil make it a challenging task to construct structures on it. Hence, modifying its expansion and contraction behavior is imperative to make black cotton soil appropriate for construction purposes. This study aims to assess the geo-technical properties of black cotton soil through laboratory testing, incorporating waste foundry sand (WFS) and sodium chloride (NaCl) to utilize the combination as sub-grade material. Differential free swell, consistency limits, the standard Proctor test, and California bearing ratio (CBR) tests are conducted with varying amounts of both materials. The laboratory testing reveals that the addition of the appropriate amount of waste foundry sand, sodium chloride, or both, improve the geo-technical properties of black cotton soil (BCS). Furthermore, using the CBR values obtained, the thickness of flexible pavement is designed with the IITPAVE software and evaluated against the IRC: 37-2018 recommendations. The software analysis demonstrates a reduction in pavement thickness for varying levels of commercial vehicles per day such as 1000, 2000, and 5000 CVPD across all combinations. This mixture not only addresses the issues related to black cotton soil but also provides an economical solution for soil stabilization and proves to be sustainable as it involves the utilization of waste materials such as waste foundry sand.
B. Shokouh Saljoughi; A. Hezarkhani; E. Farahbakhsh
Abstract
The study area, located in the southern section of the Central Iranian volcano–sedimentary complex, contains a large number of mineral deposits and occurrences which is currently facing a shortage of resources. Therefore, the prospecting potential areas in the deeper and peripheral spaces has become ...
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The study area, located in the southern section of the Central Iranian volcano–sedimentary complex, contains a large number of mineral deposits and occurrences which is currently facing a shortage of resources. Therefore, the prospecting potential areas in the deeper and peripheral spaces has become a high priority in this region. Different direct and indirect methods try to predict promising areas for future explorations, most of which are very time-consuming and costly. The main goal of mineral prospecting is applying a transparent and robust approach for identifying high potential areas to be explored further in the future. This work presents the procedure taken to create two different Cu-mineralization prospectivity maps. The first map is created using a knowledge-driven fuzzy technique and the second one by a data-driven Artificial Neural Network (ANN) approach. In this study aim is to investigate the results of applying the ANN technique and to compare them with the outputs of applying the fuzzy logic method. The geo-datasets employed for creating evidential maps of porphyry Cu mineralization include the solid geology map, alteration map, faults, dykes, airborne total magnetic intensity, airborne gamma-ray spectrometry data (U, Th, K and total count), and known Cu occurrences. Based on this study, the ANN technique is a better predictor of Cu mineralization compared to the fuzzy logic method. The ANN technique, due to capabilities such as classification, pattern matching, optimization, and prediction, is useful in identifying the anomalies associated with the Cu mineralization.
Rock Mechanics
I. Kheyrandish; M. Ahmadi; H. Jahankhah
Abstract
During an earthquake, the better performance of segmental tunnel lining, compared to the continuous in-cast concrete lining, is generally related to the joints between segments. In order to better understand the influence of the segment joints, their effect on the internal forces induced in tunnel lining ...
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During an earthquake, the better performance of segmental tunnel lining, compared to the continuous in-cast concrete lining, is generally related to the joints between segments. In order to better understand the influence of the segment joints, their effect on the internal forces induced in tunnel lining simultaneously with the effects of the other influential parameters should be considered. In this work, the segmental joints were simulated by the representative stiffnesses and effects of these characteristics in relation to the other parameters such as the soil-liner interface behavior, number of segments in each ring and thickness of segments on the internal forces induced in structure were investigated. For this purpose, 2D numerical analyses were performed and the results obtained were discussed. Results showed that under the seismic condition, the components that had the most significant role on the internal axial forces induced in the segmental lining were rotational stiffness and axial stiffness of joints. Also the bending moments were more affected by the rotational stiffness. Generally, the radial joint stiffness had a less effect on the induced internal forces. With increase in the number of segments and their thickness, the effect of joint stiffness on the internal forces increases and the design of joints should be given more attention; however, the effects of joint stiffness and frictional behavior at the soil-liner interface on the maximum induced forces are almost independent from each other. Also in a specified joint behavior, by variation in each one of the other parameters including the soil-liner interface condition, number of segments and their thickness, the absolute magnitude of the maximum induced internal forces sometimes change significantly.
Exploration
Irshad Khan; Afayou Afayou; Naeem Abbas; Asghar Khan; Numan Alam; Kausar Sultan Shah
Abstract
The study utilizes the Limit Equilibrium Method (LEM) to investigate slope movements. These movements were initially generated by construction activities at the slope's base, and subsequent events were driven by seismic activities, as the study studied area lies within the Main Karakoram Thrust (MKT) ...
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The study utilizes the Limit Equilibrium Method (LEM) to investigate slope movements. These movements were initially generated by construction activities at the slope's base, and subsequent events were driven by seismic activities, as the study studied area lies within the Main Karakoram Thrust (MKT) and Main Mantle Thrust (MMT) zones. Soil samples, characterized by a moisture content of 13% and a dry unit weight of 18.14 kN/m³ were analyzed. The study revealed that an increase in saturation caused by rainwater infiltration, resulted in a reduction in unconfined compression strength, decreasing from 712 kPa to 349 kPa. The shear strength and deformation parameters (cohesion, angle of internal friction, and deformation modulus) were also examined with varied degrees of saturation. The results revealed a decrease in these parameters as the percentage of saturation increased from 30% to 90%. The slope stability study revealed that the Factor of Safety (FOS) reduced from 1.85 to 0.86 as the saturation of the material raised from 30% to 90%. To assess the influence of unit weight, cohesion, and angle of internal friction on the FOS, multiple cases were considered. The analysis revealed that the FOS increased with higher cohesion and angle of internal friction, while an increase in unit weight resulted in a lower factor of safety. Furthermore, stability of the slope was evaluated by modifying the slope geometry such as lowering the height. According to the GeoStudio investigation, the slope remained steady even at saturation levels exceeding 80%.
Exploitation
Somaye Khajevand; Mojtaba Rezakhah; Masoud Monjezi; Fabián Alejandro Manríquez León
Abstract
Efficient loading and hauling systems, with trucks and shovels as the primary transportation machinery, are essential for optimizing mining operations. This study introduces a simulation-based approach to enhance the utilization of the hauling system in an Abbasbad copper mine in Iran. A dynamic truck ...
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Efficient loading and hauling systems, with trucks and shovels as the primary transportation machinery, are essential for optimizing mining operations. This study introduces a simulation-based approach to enhance the utilization of the hauling system in an Abbasbad copper mine in Iran. A dynamic truck allocation model is proposed to overcome the limitations of fixed allocation methods. In this approach, trucks are assigned to loading equipment based on the real-time throughput data, prioritizing equipment experiencing the highest production delays. The simulation results demonstrate that this flexible allocation model improves productivity, achieving a 13% increase in waste material handling compared to the fixed allocation scenario. These findings indicate that the proposed framework to significantly improve the efficiency and productivity of haulage systems in mining operations.
Z. Manafi; M. Kargar; F. Kafilzadeh
Abstract
Optimization of the effective parameters in the copper bioleaching of chalcopyrite concentrates (CuFeS2) is studied by moderately thermoacidophilic microorganisms. The microorganisms with extensive metabolic properties are used in two different ways: 'top-down' and 'bottom-up'. The bioleaching experiments ...
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Optimization of the effective parameters in the copper bioleaching of chalcopyrite concentrates (CuFeS2) is studied by moderately thermoacidophilic microorganisms. The microorganisms with extensive metabolic properties are used in two different ways: 'top-down' and 'bottom-up'. The bioleaching experiments are performed based on the parameters of silver, activated charcoal, concentrate type (Sarcheshmeh and Miduk), and a type of bacteria. By regrinding the concentrate particles down to 10 µm, bottom-up consortium, 500 ppm silver, and 3 g/L of coal, more than 97% of the copper from the Miduk chalcopyrite concentrate is recovered within 12 days. The final recovery of the control test without the microbes is 35%. The performance of the bottom-up method is significantly better than the top-down one. The moderate thermophiles have an important role in copper biomining.
K. Seifpanahi Shabani; B. Abedi-Orang
Abstract
In this work, three types of natural clays including kaolinite, montmorillonite, and illite with different molecular structures, as adsorbents, are selected for the removal of methylene blue dye, and their performance is investigated. Also the optimization and the analysis of the dye adsorption mechanism ...
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In this work, three types of natural clays including kaolinite, montmorillonite, and illite with different molecular structures, as adsorbents, are selected for the removal of methylene blue dye, and their performance is investigated. Also the optimization and the analysis of the dye adsorption mechanism are performed using the response surface methodology, molecular modeling, and experimental studies. The response surface optimization results demonstrate that the parameters affecting on the dye adsorption process are somewhat similar in all the three types of clays, and any difference in the impacts of the different parameters involved depends on the different structures of these three types of clays. The results of the experimental studies show that all the three clays follow the Temkin isotherm, and the comparison of the clay adsorption capacity is illite (3.28) > kaolinite (4.15) > montmorillonite (4.5) L/g. On the other hand, the results obtained from the laboratory studies and the response surface optimization were obtained using molecular modeling with the Gaussian and Chem-Office softwares. The results of these achievements confirm that the number of acceptor hydrogen bonds around the clays influence the adsorption capacity of methylene blue. Based on the results obtained, most adsorption capacities of clays are related to illite > kaolinite > montmorillonite that have 24, 18, and 16 acceptor hydrogens, respectively. The assessment of the adsorption mechanism process by the different methods confirms the dominance of the physical adsorption process and a minor effect of the chemical adsorption.
Iraj Alavi; Arash Ebrahimabadi; Hadi Hamidian
Abstract
Estimating the costs of mine reclamation is a significant part of mine closure projects. One approach to mine reclamation is planting mine areas. In this approach, the optimum selection of plant types is cosidered a multiple-criteria decision-making (MCDM) problem. Once proper plant species are identified, ...
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Estimating the costs of mine reclamation is a significant part of mine closure projects. One approach to mine reclamation is planting mine areas. In this approach, the optimum selection of plant types is cosidered a multiple-criteria decision-making (MCDM) problem. Once proper plant species are identified, it is required to estminate planting costs through statistical analysis. This work aims to introduce an algorithm for optimal plant type selection and a reclamation cost estimation model for open-pit mines. To this end, the plant species compatible with the sorrounding areas of Sungun copper mine are identified and ranked using the PROMETHEE technique. In this analysis, the main criteria are local landscape, pest resistance, plant growth ability, availability, economic issues, soil protection, water storage ability, and pollution prevention. Among the six plant types, Maple trees have the highest score (4.34). After that, to develop the reclamation cost estimation model, the data (99 datasets) is collected from the Sungun copper mine, Sarcheshmeh copper mine, and Chadormaloo iron mine. The variables in the database include soil gradation by graders, slope trimming and topography by bulldozers, the ripping and softening of the compacted soil, chemical fertilizers, natural fertilizers and mulch and biosolid, lime soil pH adjustment, herbicide, seedling, tree planting, workers and drivers, and fuel and maintenance. Regression analysis is performed to analyze the data, and a reclamation cost estimation model is developed with high accuracy (R2 = 0.78). On the whole, this study proposes an innovative, step-by-step, technical, and economic approach to the optimal selection of plant species, and presents a reclamation cost estimation model so as to promote the open-pit mine reclamation process.
Mineral Processing
Chol Ung Ryom; Kwang Hyok Pak; Il Chol Sin; Kwang Chol So; Un Chol Han
Abstract
Scheelite ore with heavy and magnetic minerals can be generally concentrated using shaking table centered gravity-magnetic processing. When magnetic field is formed by fixing magnetic bars on which permanent magnets are arranged at a constant interval, above the table desk, heavy scheelite particles ...
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Scheelite ore with heavy and magnetic minerals can be generally concentrated using shaking table centered gravity-magnetic processing. When magnetic field is formed by fixing magnetic bars on which permanent magnets are arranged at a constant interval, above the table desk, heavy scheelite particles can be concentrated by gravity, whereas heavy magnetic mineral particles can be floated off like light mineral particles by upward magnetic force. In this paper, concentration of scheelite and removal of pyrrhotite floated by magnetic force was simulated using CFD for the sample containing 1% scheelite and 2% pyrrhotite, and compared with the experiment. As a result, WO3 grade and separation efficiency of concentrate were 65.3% and 80.1%, respectively, in the new table equipped with magnetic bars, whereas 28.4% and 76.5%, respectively, in conventional table. The magnetic field formed by fixing magnetic bars above table could be significant in simplifying the sequential tabling-magnetic separation process and reducing the loss of scheelite.
Exploration
V.S.S.A Naidu Badireddi; Vije durga raju Mullagiri; MVS sekhar Bezawada; Ambili V; K S N Reddy
Abstract
The Bavanapadu-Nuvvalarevu coastal sector in Andhra Pradesh, India, hosts substantial subsurface heavy mineral (HM) resources, presenting significant economic potential. This study employs ArcGIS raster techniques to estimate Total Heavy Mineral (THM) and Total Economic Heavy Mineral (TEHM) resources ...
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The Bavanapadu-Nuvvalarevu coastal sector in Andhra Pradesh, India, hosts substantial subsurface heavy mineral (HM) resources, presenting significant economic potential. This study employs ArcGIS raster techniques to estimate Total Heavy Mineral (THM) and Total Economic Heavy Mineral (TEHM) resources in a 39 square kilometers area, integrating geospatial analysis with field data from core sediment samples. The findings reveal a total of 2.681953 million tons of THM, including 2.434422 million tons of TEHM, with the highest concentration observed in the top 1-meter sea bed sediment layer (1.605286 million tons). Ilmenite, garnet, and sillimanite dominate the mineral assemblage, accompanied by smaller quantities of zircon, monazite, and rutile, offering an estimated revenue potential of $634 to $851 million USD. The application of ArcGIS methodologies, particularly inverse distance weighting (IDW) interpolation, enabled precise mapping of HM distribution, despite challenges such as wide sample spacing and shallow core penetration. While the study highlights the economic and industrial significance of the Bavanapadu sector, it also underscores environmental concerns, including habitat disruption and sediment degradation, associated with mining. Sustainable practices, such as advanced separation technologies, site rehabilitation, and comprehensive environmental impact assessments (EIAs), are essential to mitigate ecological impacts. This research demonstrates the efficacy of GIS-based techniques in resource estimation and sustainable mining, offering a replicable framework for coastal and offshore mineral resource management globally. The findings provide critical insights into balancing economic growth with environmental preservation, setting a benchmark for responsible heavy mineral extraction in dynamic coastal environments.
Exploration
Ahmed Ali Madani
Abstract
Innovation in mineral exploration occurs either in the construction of new ore deposit models or the development of new techniques used to locate the ore deposits. Band ratio is the image processing technique developed for mineral exploration. The present study presents a new approach used to evaluate ...
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Innovation in mineral exploration occurs either in the construction of new ore deposit models or the development of new techniques used to locate the ore deposits. Band ratio is the image processing technique developed for mineral exploration. The present study presents a new approach used to evaluate the band ratio technique for discrimination and prediction of the Iron-Titanium mineralization exposed in the Khamal area, Western Saudi Arabia using the ensemble Random Forest model (RF) and SPOT-5 satellite data. SPOT-5 band ratio images are prepared and used as the explanatory variables. The target variable is prepared in which (70%) of the target locations are used for training and the rest are for validation. A confusion matrix and the precision-recall curves are constructed to evaluate the RF model performance and the Receiver Operating Characteristics curves (ROC) are used to rank the band ratio images. Results revealed that the 3/1, 2/1 & 3/2 band ratio images show excellent discrimination with AUC values of 0.986, 0.980 & 0.919 respectively. The present study successfully selects the 3/1 band ratio image as the best classifier and presents a new Fe-Ti mineralization image map. The present study proved the usefulness of the Random Forest classifier for the prediction of the Fe-Ti mineralization with an accuracy of 97%.
Exploration
Mohammad Ebdali; Ardeshir Hezarkhani; Adel Shirazy; Amin Beiranvand Pour
Abstract
This research endeavor concentrates on minerals exploration within the context of a hydrothermal polymetallic vein deposit environment. Stream sediment sampling was executed to acquire geochemical signatures pertinent to mineralization zones. The mineralization nature is classified as epithermal, predominantly ...
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This research endeavor concentrates on minerals exploration within the context of a hydrothermal polymetallic vein deposit environment. Stream sediment sampling was executed to acquire geochemical signatures pertinent to mineralization zones. The mineralization nature is classified as epithermal, predominantly involving polymetallic sulfides. The geochemical analyses yielded multi-element concentration maps, facilitating the identification of anomalies and the establishment of zoning. Although recent developments underscore the efficacy of machine learning, notably deep learning techniques, in the detection of geochemical anomalies, the majority of preceding studies were predicated on univariate statistical methodologies. To address this constraint, a multivariate approach was implemented, incorporating spatial characteristics such as shape, overlap, and zoning within anomalies and halos. Considering the limited availability of validated mineralized samples, unsupervised and semi-supervised methodologies—most notably Generative Adversarial Networks (GANs)—were employed. GANs were trained using multi-element geochemical maps, applying transfer learning to mitigate the challenges posed by restricted deposit data, thereby facilitating the delineation of prospective exploration zones. Quantitative analyses have indicated that the approach utilizing GANs attained an accuracy exceeding 92% alongside a minimal cross-entropy loss of approximately 0.07, thereby surpassing conventional methodologies in detecting of weak anomalies. The model effectively corroborated previously recognized anomalies while simultaneously detecting new prospective mineralization areas, thereby augmenting exploration opportunities. This investigation illustrates that GANs enable a more thorough utilization of geochemical datasets, integrating a wide range of variables and intricate spatial characteristics. Although GANs demonstrate superior proficiency in modeling weak anomalies, conventional techniques continue to be effective for more pronounced anomalies. The integration of both methodologies may enhance the efficiency of mineral exploration endeavors. In summary, the results emphasize the promise of GANs and sophisticated machine learning frameworks in enhancing anomaly detection and expanding mineral exploration within hydrothermal polymetallic systems.
Akbar Farzanegan; Morteza Gholami; M. H. Rahimian
Abstract
Dense Medium Cyclone is a high capacity device that is widely used in coal preparation. It is simple in design but the swirling turbulent flow, the presence of medium and coal with different density and size fraction and the presence of the air-core make the flow pattern in DMCs complex. In this article ...
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Dense Medium Cyclone is a high capacity device that is widely used in coal preparation. It is simple in design but the swirling turbulent flow, the presence of medium and coal with different density and size fraction and the presence of the air-core make the flow pattern in DMCs complex. In this article the flow pattern simulation of DMC is performed with computational fluid dynamics and Fluent software. Simulations are performed to give the axial velocity profile and the air-core. Multiphase simulations (air/water/medium) are performed with RSM model to predict turbulence dispersion, VOF model to achieve interface between air and water phases, Mixture model to give multiphase simulation and DPM model to predict coal particle tracking and partition curve. The numerical results were compared with experimental data and good agreement was observed. Also, separation efficiency of DMC was predicted using CFD simulations and shown by the Tromp curve. The comparison of simulated and measured Tromp curves showed that CFD simulation can predict Tromp curve reasonably within acceptable tolerance, however, for more accurate multiphase simulation including solid phase, it is suggested to use discrete element modeling (DEM) approach coupled with CFD.
Hamid Khoshdast; Sasan Mirshekari; Arefeh Zahab-Nazouri
Abstract
Dynamic frothability index (DFI) is a characteristic of any frother which presents useful information about frothing properties. The objective of this study is to introduce a prediction model for estimation of DFI value of dual-frother blends. Model uses the DFIs of frothers and mole ratio of weaker ...
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Dynamic frothability index (DFI) is a characteristic of any frother which presents useful information about frothing properties. The objective of this study is to introduce a prediction model for estimation of DFI value of dual-frother blends. Model uses the DFIs of frothers and mole ratio of weaker frother to calculate the blend’s DFI. The model reliability was confirmed by comparing the experimental and predicted DFIs for different frother blends, including n-butanol/MIBC, ethanol/MIBC, isoamyl alcohol/MIBC, and PPG-250/MIBC, with high determination coefficients (> 95%). A reference chart was also proposed for rapid estimation of DFI of frother mixture.
M. Mohseni; M. Ataei
Abstract
In this work, the time series modeling was used to predict the Tazareh coal mine risks. For this purpose, initially, a monthly analysis of the risk constituents including frequency index and incidence severity index was performed. Next, a monthly time series diagram related to each one of these indices ...
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In this work, the time series modeling was used to predict the Tazareh coal mine risks. For this purpose, initially, a monthly analysis of the risk constituents including frequency index and incidence severity index was performed. Next, a monthly time series diagram related to each one of these indices was for a nine year period of time from 2005 to 2013. After extrusion of the trend, seasonality, and remainder constituents of the time series modeling, the final time series model of the indices was determined with high precision. The precision level of the resulting model was evaluated using the root mean square error (RMSE) method. The values obtained for the severity index and accident frequency index were 0.001 and 6.400, respectively. Evaluation of the seasonal time series constituent of the frequency index showed that, yearly, most number of accidents occurred in April, and the least one took place in January. Additionally, evaluation of the seasonal time series constituent of the severity index showed that, every year, the severest accidents occurred in October, and the least ones happened in January. Using the final model, a monthly prediction of indices was performed for a four year period of time from 2014 to 2017. Subsequently, using the known mean work hours in the mine, predictions of the number of accidents and the number of work days lost within a similar time period were made. The prediction results showed that in the future, the number of accidents and the number of work days lost would have a down-going trend such that for similar months, annually, an average 22% decrease in the number of accidents and an average 24% decrease in the number of work days lost are expected.
Exploitation
S. Talesh Hosseini; O. Asghari; Seyed R. Ghavami Riabi
Abstract
Due to the existence of a constant sum of constraints, the geochemical data is presented as the compositional data that has a closed number system. A closed number system is a dataset that includes several variables. The summation value of variables is constant, being equal to one. By calculating the ...
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Due to the existence of a constant sum of constraints, the geochemical data is presented as the compositional data that has a closed number system. A closed number system is a dataset that includes several variables. The summation value of variables is constant, being equal to one. By calculating the correlation coefficient of a closed number system and comparing it with an open number system, one can see an increase in the values of the closed number system, which is false. Such features of this data prevent the application of standard statistical techniques to process the data. Therefore, several methods have been proposed for transforming the data from closed to open number systems. There are various geostatistical methods consisting of estimation and simulation methods in order to model a deposit. Geostatistical simulations can produce various models for a deposit with different probability percentages. The most applicable geostatistical simulation method is the sequential Gaussian simulation technique, which is highly flexible. In this work, 392 Litho-geochemical data of the Baghqloom region of Kerman in Iran consisting of 20 elements were at first converted using an open number system. Afterwards, the elements that were helpful for exploring the area and were normally standard were simulated for 100 times. After the simulations, the valid output was chosen using geostatistical validation. The maps derived from the simulations revealed the enriched concentrations of mineralization elements in the central regions.
H. Haghnazar; B. Hashemzadeh Ansar; R. Amini; M. Saneie
Abstract
River bed sand and gravel are utilized more than mountain materials due to their availability and closeness to the transit roads and sites of usage. Excessive and non-technical extraction of gravel and sand bring a kind of interference in them, leading to many negative consequences. Therefore, presenting ...
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River bed sand and gravel are utilized more than mountain materials due to their availability and closeness to the transit roads and sites of usage. Excessive and non-technical extraction of gravel and sand bring a kind of interference in them, leading to many negative consequences. Therefore, presenting solutions to reduce these impacts and infilling mining pits are essential. In this research work, through an experimental work, locating two consequent river bed mining pits in the form of the distance between them and also their distance from the walls for the purpose of infilling and extraction management was investigated. The results obtained showed that movement of the downstream pit did not significantly affect the infilling volume and migration of the upstream pit but by movement of the pit towards the wall, the infilling volume of the upstream pit was reduced by up to 25% compared to the channel center. Concerning the downstream pit, the impact of the distance between pits depended on their distance from the wall so that if the pit was close to the channel center, the infilling volume was increased, and if it was located close to the wall, the infilling volume was increased up to a distance equal to 9 times the flow depth, and after that the infilling was reduced. In case the pits were excavated towards the channel center and the downstream pit was excavated at a distance equal to 12 times the flow depth, the best state of infilling and pit migration did occur.
V. Sarfarazi; H. Karimi Javid; K. Asgari
Abstract
The experimental and numerical methods were used to investigate the effects of joint number and joint angle on the failure behaviour of rock pillars under a uniaxial compressive test. The gypsum samples with dimensions of 200 mm × 200 mm × 50 mm were prepared. The compressive strength of ...
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The experimental and numerical methods were used to investigate the effects of joint number and joint angle on the failure behaviour of rock pillars under a uniaxial compressive test. The gypsum samples with dimensions of 200 mm × 200 mm × 50 mm were prepared. The compressive strength of the intact sample was 7.2 MPa. The imbeded joint was placed inside the specimen. The joint length was 6 cm in a constant joint length. There were several numbers of cracks including one, two, and three cracks. In the experimental tests, the angles of the diagonal plane with respect to the horizontal axis were 0, 30, 60, and 90 degrees. The axial load was applied to the model with a rate of 0.01 mm/s. In the fracture analysis code, the angles of the diagonal plane with respect to the horizontal axis were 0, 15, 30, 45, 60, 75, and 90 degrees. A constant axial load of 135 MPa was applied to the model. The results obtained showed that the failure process was mostly dependent on the angle and number of the non-persistent joint. The compressive strength of the samples was dependent on the fracture pattern and the failure mechanism of the discontinuities. It was shown that the tensile cracks were developed whithin the model. The strength of the specimens increased by increasing both the joint angle and joint number. The joint angle of 45° KI had the maximum quantity. The stress intensity factor was decreased by increasing the joint number. The failure pattern and failure strength were analogous in both methods, i.e. the experimental testing and the numerical simulation methods.
M. Ghaedi Ghalini; M. Bahaaddini; M. Amiri Hossaini
Abstract
Estimation of the in-situ block size is known as a key parameter in the characterization of the mechanical properties of rock masses. As the in-situ block size cannot be measured directly, several simplified methods have been developed, where the intrinsic variability of the geometrical features of discontinuities ...
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Estimation of the in-situ block size is known as a key parameter in the characterization of the mechanical properties of rock masses. As the in-situ block size cannot be measured directly, several simplified methods have been developed, where the intrinsic variability of the geometrical features of discontinuities are commonly neglected. This work aims to estimate the in-situ block size distribution (IBSD) using the combined photogrammetry and discrete fracture network (DFN) approaches. To this end, four blasting benches in the Golgohar iron mine No. 1, Sirjan, Iran, are considered as the case studies of this research work. The slope faces are surveyed using the photogrammetry method. Then 3D images are prepared from the generated digital terrain models, and the geometrical characteristics of discontinuities are surveyed. The measured geometrical parameters are statistically analysed, and the joint intensity, the statistical distribution of the orientation, and the fracture trace length are determined. The DFN models are generated, and IBSD for each slope face is determined using the multi-dimensional spacing method. In order to evaluate the validity of the generated DFN models, the geological strength index (GSI) as well as the stereographic distribution of discontinuities in the DFN models are compared against the field measurements. A good agreement has been found between the results of the DFN models and the filed measurements. The results of this work show that the combined photogrammetry and DFN techniques provide a robust, safe, and time-efficient methodology for the estimation of IBSD.
Exploitation
M. Ghobadi Samani; M. Monjezi; J. Khademi Hamidi; A. Mousavinogholi
Abstract
Truck-Shovel fleet, as the most common transportation system in open-pit mines, has a significant part of mining costs, for which optimal management can lead to substantial cost reductions. Among the available dispatch mathematical models, the multi-stage approach is well suited for allocating trucks ...
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Truck-Shovel fleet, as the most common transportation system in open-pit mines, has a significant part of mining costs, for which optimal management can lead to substantial cost reductions. Among the available dispatch mathematical models, the multi-stage approach is well suited for allocating trucks to respected shovels in a dynamic dispatching program. However, with this kind of modeling sequencing of the allocated trucks is not possible though it is important to find out the best solution so that getting the minimum accrued cost. To comply with the shortcoming of the traditional model, in this paper, a new hybrid model is developed and applied in Copper Mine of Iran, in which for each truck an allocation matrix is considered as input to the genetic algorithm implemented to determine the best solution. According to the obtained results, the optimal sequencing of the trucks can result in a significant (31%) cost reduction in a shift.
Zahra Rezaee Shahzadehaliakbari; Mehran Arian; Mohsen Pourkermani; Ali Solgi; Anahita Keynezhad
Abstract
The Gazkhizan Copper deposit is located in the Troud-Reshm zone, Central Iran. It is situated in a shear zone bounded by the Anjilo and Troud sinistral strike-slip faults from the north and south, respectively. Mineralization is done by siliceous-shear veins along with copper mineralization. About 41 ...
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The Gazkhizan Copper deposit is located in the Troud-Reshm zone, Central Iran. It is situated in a shear zone bounded by the Anjilo and Troud sinistral strike-slip faults from the north and south, respectively. Mineralization is done by siliceous-shear veins along with copper mineralization. About 41 mapping points carried out around the fault outcrops, along with the interpretation of the Win Tensor software data and geometrical analysis of structural features paved our way to study the Riddle pattern in the region. The structural features include sinistral and dextral strike-slip faults, normal faults, reverse faults (rarely), and mineralized veins, as well as different types of shear zone fractures with different grades of copper ore. The mineralized veins in the area are frequent in four types including the R´, R, T, and X fractures, respectively. The highest number of the veins have been formed within the Riddle fractures. Because of the hybrid nature of the fractures, the veins are formed within the tensile fractures, and then they are aligned along the R fractures’ strike by the clockwise rotations. The importance and necessity of this research work is as what follows. The definitive reserve of this mineralized area is 434,500 tons of copper ore with an average grade of 1.61% of copper. For this reason, it is necessary to determine and classify the fractures that host this reserve.
