Case Study
Exploration
Mohamed Y Amer; Adel M Salem; Mohammed S Farahat; Said Kamel Elsayed
Abstract
Sustainable production of sufficient energy to power the world’s economy with a minimum environmental footprint has been one of the most significant challenges for the decades. Geothermal energy has been considered as one of the promising options to meet the world’s future energy demand. ...
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Sustainable production of sufficient energy to power the world’s economy with a minimum environmental footprint has been one of the most significant challenges for the decades. Geothermal energy has been considered as one of the promising options to meet the world’s future energy demand. The cost of drilling geothermal wells is between 35% and 50% of the total investment cost for the new high-temperature geothermal plants. This “up front” cost makes the geothermal plants more expensive to build than the conventional plants, and because of this and the perceived risk, a lot of attention has been focused on reducing this cost.This paper attempts to minimize the cost of drilling deep wells such as AG-119X, in Egypt of 20060 ft. in depths; in this well, the actual cost was more than the proposed by about five million USD. The actual cost of the drilling operation has been analyzed and compared with the proposed; by observing the cost of each drilling item, it was found that the power drive tools in the bottom hole assembly such as the downhole motor with Rotary Steerable drilling system (RSS) or turbodrill hydraulic downhole motor is the most costly element of the drilling operation in 8.5 holes, which tack thirteen trips in every trip with a new bit, and it was found that the turbodrill hydraulic downhole motor was costly effected in drilling the shush section, in this, and can save around 1756999 USD; this paper is a road map for reducing the cost of drilling geothermal wells.
Original Research Paper
Exploitation
Pouya Nobahar; Yashar Pourrahimian; Roohollah Shirani Faradonbeh; Fereydoun Mollaei Koshki
Abstract
Mineral reserve evaluation and ore type detection using data from exploratory boreholes are critical in mine design and extraction. However, preparing core samples and conducting chemical and physical tests is a time-consuming and costly procedure, slowing down the modeling process. This paper presents ...
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Mineral reserve evaluation and ore type detection using data from exploratory boreholes are critical in mine design and extraction. However, preparing core samples and conducting chemical and physical tests is a time-consuming and costly procedure, slowing down the modeling process. This paper presents a novel Deep Learning (DL)-based model to recognize the types of kaolinite samples. For this purpose, a dataset containing the images of drilled cores and their types determined from conventional chemical and physical analyses was used. Eight Convolutional Neural Network (CNN) topologies based on individual features were developed, named A, B, C, D, E, F, G, and H. Six of the eight proposed CNN topologies described above had accuracy below 80%, whereas two of them, model A and H, had higher accuracy than other topologies. Due to their similarity in results, both of them analyzed deeply. Model A was more efficient, with 90% accuracy, than model B, with 84% accuracy. Furthermore, the class detection performance of model A was further evaluated using different indices, including precision, recall, and F1-score, which resulted in values of 92%, 92%, and 90%, respectively, which are acceptable accuracies to identify the type of samples when using this approach on six different types of kaolinite.
Original Research Paper
Environment
Aditi Nag
Abstract
Using quantitative data from visitor surveys, Environmental Impact Assessments (EIA), and stakeholder perspectives, this paper investigates the growth of sustainable tourism at Dhori Mines, a noteworthy mining heritage site (MHS) in India. The survey reveals that 82% of visitors value a site's heritage ...
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Using quantitative data from visitor surveys, Environmental Impact Assessments (EIA), and stakeholder perspectives, this paper investigates the growth of sustainable tourism at Dhori Mines, a noteworthy mining heritage site (MHS) in India. The survey reveals that 82% of visitors value a site's heritage value and prefer immersive experiences that highlight its cultural and historical significance, highlighting the complex relationship between conservation efforts and visitor engagement. The EIA revealed that 68% of regions experienced moderate to severe environmental degradation, and water contamination increased by 22% since baseline measurements. The findings suggest targeted measures to reduce environmental effects and encourage ethical tourism, emphasizing the importance of inclusive decision-making and collaborative governance in balancing conservation objectives with visitor satisfaction. Developing tailored visitor experiences, implementing sustainable practices based on EIA data, and enhancing community participation are merely some of the important recommendations made in the paper's conclusion. The research provides managers and policymakers with evidence-based recommendations for preserving the environmental sustainability and cultural integrity of MHSs like Dhori Mines, contributing to the growing knowledge on sustainable heritage tourism. Future research prospects include long-term monitoring of environmental impacts, assessing socio-economic outcomes for local communities, and conducting comparative studies across different MHSs.
Case Study
Environment
Debasmita Basu; Smriti Mishra
Abstract
This study presents a comprehensive analysis of community perceptions regarding the impacts of reclamation strategies for abandoned coal mines in India, with a specific focus on the Manikpur Coal Mine. Through a structured survey administered to residents in the vicinity of the mine, the research investigates ...
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This study presents a comprehensive analysis of community perceptions regarding the impacts of reclamation strategies for abandoned coal mines in India, with a specific focus on the Manikpur Coal Mine. Through a structured survey administered to residents in the vicinity of the mine, the research investigates the economic, socio-cultural, and environmental impacts of reclamation efforts. Utilizing Structural Equation Modeling (SEM), the study identifies key factors influencing community perceptions, including the perceived benefits of reclamation, levels of community involvement, and overall satisfaction with mining operations. The findings reveal significant relationships among these factors, such as the positive influence of reclamation availability/requirement (path coefficient = 0.633) on satisfaction and the negative impact of involvement on satisfaction (-0.805). Indirect effects highlight the interplay between constructs, with experience positively influencing involvement (0.673) and satisfaction (0.162) while negatively affecting reclamation availability/requirement (-0.194). Variations in latent variable scores for satisfaction (-1.63 to 3.031) and reclamation availability/requirement (-1.42 to 1.903) underscore the diverse respondent experiences. These insights emphasize the importance of effective community engagement and tailored reclamation strategies. Policy recommendations are provided to enhance the sustainability and effectiveness of reclamation efforts, emphasizing the need for holistic approaches that integrate economic viability, socio-cultural acceptance, and environmental sustainability. The study contributes to the field of mine reclamation by offering valuable insights into resident perceptions and practical guidelines for improving reclamation practices in mining-affected areas.
Original Research Paper
Mineral Processing
Rim Amata; Mohamed Bounouala; Ashraf Alsafasfeh; Amar Amata; Sofiane Bouabdallah
Abstract
The Djebel Onk region of Algeria faces a significant environmental concern, related to phosphate mining waste. Although these mining tailings contain relatively low quantities of valuable minerals, they still include up to 25% P₂O₅ in the particle size range of 0.25-1 mm (-1-+0.25), suggesting the ...
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The Djebel Onk region of Algeria faces a significant environmental concern, related to phosphate mining waste. Although these mining tailings contain relatively low quantities of valuable minerals, they still include up to 25% P₂O₅ in the particle size range of 0.25-1 mm (-1-+0.25), suggesting the potential for recovery and reuse. This research, based on the Bir El Ater area, explores the methods to recover phosphate-rich minerals, optimizing their reuse. Two techniques were explored: calcination, a heat treatment altering mineral chemistry, and electrostatic separation, which uses the electrical properties to separate minerals. The black phosphate tailings collected from the curved grids of wet processing were subjected to detailed analysis using Scanning Electron Microscopy (SEM), X-Ray Diffraction (XRD), and X-Ray Fluorescence (XRF), to examine their mineralogical and chemical properties. The results showed a notable improvement in the P₂O₅ concentration, with electrostatic separation reaching a 30.03% content and an 89% recovery rate, while calcination achieved the 30.91% content with a 91% recovery rate. These results highlight the effectiveness of both methods in recovering phosphate from mining tailings, contributing to a better waste management, a more efficient resource use, and a reduced environmental footprint. They also suggest sustainable recovery pathways, especially for the regions facing water scarcity, where flotation is impractical. With the ability to achieve high recovery rates without chemical inputs, calcination and electrostatic separation stand out as environmentally sustainable options for global phosphate beneficiation.
Original Research Paper
Rock Mechanics
Weiqun Liu; Tian Fang; Sheng Sang
Abstract
Mudstone is a common rock in underground engineering, and mudstone with fractures, have the certain self-closing capability. In this paper, we employed experiments and numerical analyses to investigate the mechanism of such a characteristic, and also examined the permeability pattern of mudstone overburdens. ...
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Mudstone is a common rock in underground engineering, and mudstone with fractures, have the certain self-closing capability. In this paper, we employed experiments and numerical analyses to investigate the mechanism of such a characteristic, and also examined the permeability pattern of mudstone overburdens. The experiments were performed with the MTS815.02 testing system, involving material properties under different water contents and their crack-closing behaviors. The principal task of numerical analysis is to determine the permeability of fractured mudstone layers, working with the COMSOL platform. The experimental results show that the Young’s Modulus of water-saturated mudstone is just 2.2% of that of natural mudstone, and the saturated also exhibit a remarkably obvious creep behavior. As the surrounding pressures increase, the permeability coefficient of fractured mudstone decrease exponentially, even dropping by two orders of magnitude corresponding to over 2.0MPa pressures. Based on these experiment outcomes, we can easily infer that rapid or complete fracture-closing is the main reason of permeability drop, and furthermore, both softening and creep are the major factors of self-closure of mudstone fractures, and especially, the softening behavior plays an absolutely fundamental role. The numerical analyses show that either a higher in-situ stress or lower fracture density can obviously become one of the advantageous conditions for fractured mudstone layers to restore towards impermeability. These results are also verified by the engineering observation in Yili No. 4 mine of China. There obviously existed the recovery of water-blocking capacity of overlying strata after a period of time. We hereby recommend this investigation as refences for underground mining or engineering construction involving mudstone.
Original Research Paper
Rock Mechanics
Festus Kunkyin-Saadaari; Jude Baah Offei; Sadique Ibn Sadique; Victor Kwaku Agadzie; Ishamel Abeiku Forson
Abstract
The underground mining operations at the Obuasi Gold Mine rely heavily on the stability of hard rock pillars for safety and productivity. The traditional empirical and numerical methods for predicting pillar stability have limitations, prompting the exploration of advanced machine learning techniques. ...
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The underground mining operations at the Obuasi Gold Mine rely heavily on the stability of hard rock pillars for safety and productivity. The traditional empirical and numerical methods for predicting pillar stability have limitations, prompting the exploration of advanced machine learning techniques. Hence, this work investigates the applicability of stacked generalisation techniques for predicting the stability status of hard rock pillars in underground mines. Four stacked models were developed, using Gradient Boosting Decision Trees (GBDTs), Random Forest (RF), Extra Trees (ET), and Light Gradient Boosting Machines (LightGBMs), with each model taking turns as the meta-learner, while the remaining three models acted as the base learners in each case. The models were trained and tested on a dataset of 201 pillar cases from the AngloGold Ashanti Obuasi Mine in Ghana. Model performance was evaluated using classification metrics, including accuracy, precision, recall, F1-score and Matthews Correlation Coefficient (MCC). The RF-stacked model demonstrated the best overall performance, achieving an accuracy of 93.44%, precision of 94.27%, recall of 93.44%, F1-score of 93.59%, and MCC of 88.90%. Feature importance analysis revealed pillar depth and pillar stress as the most influential factors affecting pillar stability prediction. The results indicate that stacked generalisation techniques, particularly the RF-stacked model, offer promising capabilities for predicting hard rock pillar stability in underground mining operations.
Original Research Paper
Mineral Processing
Sahil Thakur; Ravi Kumar Sharma
Abstract
Slope stability is critical for infrastructure safety, particularly in seismically active regions. This work evaluates the stability of a slope along the Baroti-Reyur road in Himachal Pradesh, located in Zone 5, using a novel combination of Limit Equilibrium Methods (LEMs) and Finite Element Methods ...
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Slope stability is critical for infrastructure safety, particularly in seismically active regions. This work evaluates the stability of a slope along the Baroti-Reyur road in Himachal Pradesh, located in Zone 5, using a novel combination of Limit Equilibrium Methods (LEMs) and Finite Element Methods (FEMs). The analysis examines natural slope conditions and the impact of sustainable mitigation measures, including retaining structures and bioengineering techniques, under the static and dynamic conditions. The soil model incorporated a modulus of elasticity (E) of 90,000 kN/m², and a poisson's ratio (v) of 0.3 to reflect realistic slope-soil-structure interactions. Retaining structures such as gravity, cantilever, and gabion walls (4 m, 6 m, and 5 m high) were constructed using M30 RCC and Fe500 steel. Bioengineering measures featured deep-rooted grasses like Vetiver and Broom grass to improve soil cohesion (c), shrubs like Lantana camara for surface stability, and trees like Albizia lebbeck to reinforce deeper soil layers. These vegetation-based interventions enhanced slope resilience, while promoting ecological restoration. Theoretical LEM analysis revealed marginal stability, with static FOS values of 1.1 and pseudo-static FOS of 1.05. GEO5 pseudo-static analysis indicated critically low FOS value of 0.88 for dynamic saturated conditions, improving to 2.01 with retaining structures. FEM analysis using PLAXIS 2D provided more detailed insights, capturing complex soil-structure interactions with a static FOS of 1.028 and dynamic FOS of 0.994. By combining FEM with sustainable mitigation strategies, this work offers a framework for resilient slope stabilization, ensuring safety, while promoting environmental sustainability in seismically active regions.
Original Research Paper
Exploration
Marco Antonio Cotrina-Teatino; Jairo Jhonatan Marquina-Araujo; Jose Nestor Mamani-Quispe; Solio Marino Arango-Retamozo; Johnny Henrry Ccatamayo-Barrios; Joe Alexis Gonzalez-Vasquez; Teofilo Donaires-Flores; Maxgabriel Alexis Calla-Huayapa
Abstract
This work aimed to categorize mineral resources in a copper deposit in Peru, using a machine learning model, integrating the K-prototypes clustering algorithm for initial classification and Random Forest (RF) as a spatial smoother. A total of 318,443 blocks were classified using geostatistical and geometric ...
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This work aimed to categorize mineral resources in a copper deposit in Peru, using a machine learning model, integrating the K-prototypes clustering algorithm for initial classification and Random Forest (RF) as a spatial smoother. A total of 318,443 blocks were classified using geostatistical and geometric variables derived from Ordinary Kriging (OK) such as kriging variance, sample distance, number of drillholes, and geological confidence. The model was trained and validated using precision, recall, and F1-score metrics. The results indicated an overall accuracy of 97%, with the measured category achieving 98% precision and an F1-score of 0.98. The total estimated tonnage was 5,859.36 Mt, distributed as follows: 1,446.13 Mt (measured), 2,249.22 Mt (Indicated), and 2,164.01 Mt (Inferred), with average copper grades of 0.43%, 0.33%, and 0.31% Cu, respectively. Compared to the traditional geostatistical methods, this hybrid approach improves classification objectivity, spatial continuity, and reproducibility, minimizing abrupt transitions between categories. The RF model proved to be a robust tool, reducing classification inconsistencies and better capturing geological uncertainty. Future studies should explore hybrid models (K-means with RF, ANN with K-Prototypes, gradient boosting, and deep learning) and incorporate economic variables to optimize decision-making in resource estimation.
Original Research Paper
Exploration
Mahdi Bajolvand; Ahmad Ramezanzadeh; Amin Hekmatnejad; Mohammad Mehrad; Shadfar Davoodi; Mohammad Teimuri
Abstract
Shear Wave Slowness Log (DTSM) is one of the most important petrophysical logs applicable for studying reservoirs, especially geomechanical studying of the oil and gas fields. However, lack of this parameter in wellbore logging can import great sources of uncertainty into geomechanical studies. This ...
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Shear Wave Slowness Log (DTSM) is one of the most important petrophysical logs applicable for studying reservoirs, especially geomechanical studying of the oil and gas fields. However, lack of this parameter in wellbore logging can import great sources of uncertainty into geomechanical studies. This study aims to provide solutions for decreasing the uncertainty of geomechanical models with estimation of the DTSM log using the high accurate deep machine learning models. The main idea is using data from offset fields for extending the range of training data and improving the estimation ability and generalizability of machine learning models. For this purpose, petrophysical data from 8 wells of 4 Iranian oil fields were collected. In the first stage, data preprocessing was performed for reducing the effects of wrong data, missing value, noises, and outliers. Then, machine learning (regression learning-based and deep neural network-based) and analytical models implemented for estimating DTSM. The results indicated that the Gated Recurrent Unit (GRU) model with the values of 1.9 and 2.14 for RMSE and 0.99 for R-square had the most exact answers, for training and test data, respectively. Meanwhile, evaluation of the accuracy of the models on the validation well data indicated that GRU model with the values of 2.43 and 0.93 had been the most accurate model for RMSE and R-square, respectively. Accordingly, using a multi-field comprehensive data bank and applying machine learning methods are strongly recommended to estimate the DTSM, for the cases where limited offset data is available.
Case Study
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.
Original Research Paper
Rock Mechanics
Mohammad Rezaei; Seyed Pourya Hosseini; Danial Jahed Armaghani; Manoj Khandelwal
Abstract
This paper presents an experimental-statistical study investigating the influence of five joint properties: density, filling type, angle, aperture, and roughness on the longitudinal wave velocity (LWV) of concrete samples. To achieve this, each of the five properties is categorized into distinct groups ...
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This paper presents an experimental-statistical study investigating the influence of five joint properties: density, filling type, angle, aperture, and roughness on the longitudinal wave velocity (LWV) of concrete samples. To achieve this, each of the five properties is categorized into distinct groups with specific intervals. Concrete samples measuring 15*15*15 cm are prepared in the laboratory based on an optimal combination of 75% sand, 15% cement, and 10% water. The LWV values of these samples are then measured. The experimental results indicate that joint density, roughness, and aperture have an inverse relation with LWV, resulting in reductions of 82%, 22.5% and 49%, respectively. Additionally, an approximate sinusoidal relationship between LWV and joint angle is established, leading to a variation of approximately 10% in LWV values for different joint angles. To evaluate the effect of joint filling on LWV, various filling materials, including iron oxide, calcite, silica, clay, and gypsum are used, resulting in approximately a 34% variation in LWV values. It was found that gypsum filling yields the highest LWV value while iron oxide filling produces the lowest. Furthermore, analysis of variance (ANOVA) confirms that a polynomial quadratic equation best represents the relation between LWV and each of the joint characteristics, with determination coefficient (R2) values ranging from 0.694 to 0.99. Finally, a verification study using "validation samples" demonstrates the acceptable accuracy for the proposed equations, with minimum relative errors ranging from 3% to 13%, a low root mean square error of 189.08 m/s, and a high R2 value of 0.926. This research enhances understanding of wave propagation through jointed rock masses with varying joint characteristics and provides theoretical support for rock reorganization and dynamic stability analysis of rock masses.
Original Research Paper
Rock Mechanics
Ehsan Taheri; Reza Mohammadpour; Mohammad Hossein Mokhtarzadeh
Abstract
In recent years, the demand for new trenchless methods has dramatically risen. Pipe jacking is a trenchless method widely used in recent years. Ground deformation is one of the significant parameters that may lead to unrepairable harm to facilities and even people. So, ground deformation analysis is ...
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In recent years, the demand for new trenchless methods has dramatically risen. Pipe jacking is a trenchless method widely used in recent years. Ground deformation is one of the significant parameters that may lead to unrepairable harm to facilities and even people. So, ground deformation analysis is necessary for safety and design reasons. The present study analyzes the factors affecting ground deformation during pipe jacking. This is a descriptive-interventional study. Pipe jacking causes soil displacement in three dimensions (3-D). Therefore, 3-D numerical methods were applied for analysis. In this study, numerical simulation was performed using PLAXIS finite element numerical software, taking the case study into account. The effect of each parameter on the ground deformation pattern was studied in three directions; the uplift and their exact position were then analyzed. It should be noted that displacement analyses were performed in two areas: pipe crown and ground surface. Also, the relation of each parameter was estimated with the ground subsidence. Finally, the effect of each different factor and their sensitivity index were determined using sensitivity analysis. The highest subsidence occurs at the end of the shield due to stress relaxation. Considering the results, it was found that the relationship between the internal friction angle and subsidence is linear and direct. The relationship between the elastic modulus and subsidence is also linear but indirect. The results indicate that the most sensitive factor of ground deformation is the diameter, but the least sensitive factor is the face pressure.
Original Research Paper
Rock Mechanics
Dariush Kaveh Ahangaran; Kaveh Ahangari; Mosleh Eftekhari
Abstract
Blast damage on the stability of the slopes plays an important role in the profitability and safety of mines. Determination of this damage is also revealed in the widely used Hoek-Brown failure criterion. Of course, this damage is used as a moderating factor in this failure criterion, and its accurate ...
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Blast damage on the stability of the slopes plays an important role in the profitability and safety of mines. Determination of this damage is also revealed in the widely used Hoek-Brown failure criterion. Of course, this damage is used as a moderating factor in this failure criterion, and its accurate determination is considered an important challenge in rock engineering. This study aims to investigate the effect of geological structures in blast damage factor using 3D discrete element modeling of two slopes with different directions of geological discontinuities. The dynamic pressure of the explosion is also simulated in three blastholes. To ensure the modeling results, other dynamic properties of the model have been selected based on the proven studies. An analytical analysis was conducted based on the failure zones (blast damage area), and quantitative and qualitative analyses were performed using the recorded PPV values during the blasting simulation. The results show that the geological discontinuities control, damp, and reduce blast damage. The expansion of blast damage is reduced by 75% along with the increase in rock mass strength, and the blast damage can expand up to 33 meters along with the decrease in strength. By reducing the distance of discontinuities, the role of discontinuities in damping becomes greater than other properties of the rock mass and the discontinuities further away from the blasting hole create more damping. The relation between the distance from the Hole and PPV values shows that for more realistic slope stability analysis results, the values of the damage factor in the Hoek-Brown failure criterion should be applied gradually and decreasingly in layers parallel to the slope surface.
Original Research Paper
Exploitation
Moslem Jahantigh; Hamidreza Ramazi
Abstract
Various methods have been used for clustering big data. Pattern recognition methods are suitable methods for clustering these data. Due to the large volume of samples taken in the drilling of mines and their analysis for various elements, this category of geochemical data can be considered big data. ...
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Various methods have been used for clustering big data. Pattern recognition methods are suitable methods for clustering these data. Due to the large volume of samples taken in the drilling of mines and their analysis for various elements, this category of geochemical data can be considered big data. Examining and evaluating drilling data in the Lar copper mine in Sistan and Baluchistan province located in the southeast of Iran requires the use of these methods. Therefore, the main goal of the article is the clustering of the drilling data in the mentioned mine and its zoning of the geochemical data. To achieve this goal, 3500 samples taken from drilling cores have been used. Elemental analysis for six elements has been done using the ICP-Ms method. Pattern recognition methods including SOM and K-MEANS have been used to evaluate the relation between these elements. The silhouette method has been used to determine and evaluate the number of clusters. Using this method, 4 clusters have been considered for the mentioned data. According to this method, it was found that the accuracy of clustering is higher in the SOM method. By considering the 4 clusters, 4 zones were identified using clustering methods. By comparing the results of the two methods and using the graphical method, it was determined that the SOM method has a better performance for clustering geochemical data in the studied area. Based on that, zones 2 and 4 were recognized as high-grade zones in this area.
Original Research Paper
Mineral Processing
Reza Zolfaghari; Mohammad Karamoozian
Abstract
In flotation, entrainment (ENT) affects the recovery of the concentrate, and the entrainment model is often supposed to be only a function of particle size in models. Some research shows that other variables may also significantly affect ENT. In this study, some flotation experiments executed using a ...
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In flotation, entrainment (ENT) affects the recovery of the concentrate, and the entrainment model is often supposed to be only a function of particle size in models. Some research shows that other variables may also significantly affect ENT. In this study, some flotation experiments executed using a mixture of pure quartz as the valuable mineral and a pure magnetite sample as the gangue mineral to investigate the effects of other variables, such as solid content, airflow rate, frother, and collector dosages, on ENT. The results showed ENT varied from 0.071 to 0.851 is different, while the entrainment recovery was between 0.006 to 0.23, which means that the difference is statistically significant. ENT affected by (1) collector dosage, (2) frother dosage, (3) solid content, (4) the interaction between airflow rate and solid content and, (5) the interaction between airflow rate and frother dosage. An empirical statistical model is presented based on operational parameters. As the present models for ENT incorporate just particle size, it is not enough to predict gangue recovery in industrial applications by keeping the operating conditions constant. This novel model can predict ENT based on different operational parameters. The developed model is presented based on the particle mass by changing the operation parameters.
Original Research Paper
Rock Mechanics
Amirhossein Naseri; Behnam Maleki; Tohid Asheghi Mehmandari; Amin Tohidi; Ahmad Fahimifar
Abstract
The present study delves into investigating the impact of sample size and geometry on the mechanical behavior of rock and concrete. More specifically, it examines factors including Uniaxial Compressive Strength (UCS), Elastic Modulus (E), and Pressure Wave Velocity (Vp). Results indicated a notable correlation ...
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The present study delves into investigating the impact of sample size and geometry on the mechanical behavior of rock and concrete. More specifically, it examines factors including Uniaxial Compressive Strength (UCS), Elastic Modulus (E), and Pressure Wave Velocity (Vp). Results indicated a notable correlation between the dimensions and morphology of the specimens with these properties. All tests were conducted at a uniform loading rate of 0.002 mm/s. According to the outcomes, the effect of sample size and shape on UCS for concrete is more predictable than for rock. The increase in the sample size led to an initial increase followed by a decline in the UCS values of the rocks. Furthermore, the concrete typically showed a drop in the UCS values as sample size increased. The UCS and E values rose at first before falling, suggesting the existence of a sample size with maximum UCS. The Vp values of the prismatic rock and concrete samples continually grew. After attaining their optimum strength, the prismatic samples showed greater degrees of flexibility and ductility compared to cylindrical ones because of post peak behavior. This suggests that prismatic samples, with their less slender geometry and reduced tendency for brittle behavior, are deemed more suitable for UCS testing. These results can improve the accuracy of assessing the mechanical properties of tunneling materials, particularly those used in subsurface construction in urban roads and highways.
Original Research Paper
Mineral Processing
Seyyed Mohsen Zamzami; Javad Vazifeh Mehrabani
Abstract
In this research, solid phase settling process from the liquid phase were optimized simultaneously on the different responses, using the response surface methodology (RSM). The effect of solid percentage, flocculant dosage, temperature, and pulp pH were evaluated on the responses of solid settling velocity, ...
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In this research, solid phase settling process from the liquid phase were optimized simultaneously on the different responses, using the response surface methodology (RSM). The effect of solid percentage, flocculant dosage, temperature, and pulp pH were evaluated on the responses of solid settling velocity, water turbidity, viscosity and density of settled pulp. The results showed that by increasing the flocculant dosage from 0.5 to 3.5 g/ton, settled pulp viscosity decreases from 49.05 cSt to 17.54 cSt. The higher values of pulp pH as well as low amount of solid percentage resulted in high water turbidity, which shows the lack of contact between flocs and suspended particles. The results indicated that the pulp solid percentage and the flocculants dosage are the most significant parameters on the responses. Optimum test conditions were obtained in industrial mode by using 5 g/t flocculant, solid percentage 23.96%, pH=7.5 temperature of the pulp 21.5°C in which condition, settling rate, pulp viscosity, pulp density and water turbidity were predicted to be 13.23 cm/min, 5.1 cSt, 1.61 g/cm3 and 15.7 NTU respectively. Repetition test in the model predicted optimum condition was carried out and verified the predicted optimized condition.
Original Research Paper
Exploration
Seyyed Saeed Ghannadpour; Samaneh Esmaelzadeh Kalkhoran; Maedeh Behifar; Hadi Jalili
Abstract
In this study, with the aim of identifying alteration zones related to the porphyry copper system, satellite images are processed in study area (the Zafarghand exploration area) in the NE of Isfahan. For this purpose, one of the common methods of separating geochemical anomalies from the background, ...
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In this study, with the aim of identifying alteration zones related to the porphyry copper system, satellite images are processed in study area (the Zafarghand exploration area) in the NE of Isfahan. For this purpose, one of the common methods of separating geochemical anomalies from the background, i.e. fractal Concentration-Number (C-N) model, has been employed. The C-N fractal model will normally be implemented on geochemical samples. While in this study, the digital number values belonging to the pixels of the ASTER sensor image are considered as a systematic sample network and also as input for this model. The output of this processing has been prepared in the form of maps of promising areas of the Zafarghand region. The correspondence of the resulting maps with the alteration map of the region shows that applying the proposed method in determining the propylitic and phyllic alteration zones has had acceptable performance. Finally, with the help of the aforementioned proposed method, a map of the promising areas of the study area has been prepared, and based on that, new zones of alterations have been introduced in the region.
Original Research Paper
Rock Mechanics
Aref Jaberi; Shokroallah Zare
Abstract
Unlike the mechanical properties of intact rock, which can be obtained on a laboratory scale, estimating the mechanical properties of the jointed rock mass is very difficult due to the presence of different joints and the complexity of the joints. Therefore, to calculate the mechanical parameters of ...
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Unlike the mechanical properties of intact rock, which can be obtained on a laboratory scale, estimating the mechanical properties of the jointed rock mass is very difficult due to the presence of different joints and the complexity of the joints. Therefore, to calculate the mechanical parameters of the jointed rock mass and use the continuous media theory of the jointed rock mass, it is necessary to calculate the Representative Element Volume (REV) of the rock mass. In this study, the Discrete Element Method (DEM) and the mechanical index of strength were used to investigate the effect of persistent and non-persistent joint angles, as well as model size on the REV in x, y, and z directions. The numerical results showed that by changing the joint angles and side length, both the strength and the REV of the rock mass were affected. The maximum representative side length for the persistent joint in the x and z directions occurred at angles of 60° and 75°, respectively. The minimum strength was obtained for joints in the x and z directions at a 45° angle. Finally, the REV for persistent and non-persistent joints is calculated as 10*0.5*8m and 4*0.5*4m, respectively.
