Original Research Paper
Rock Mechanics
Pankaj Bhatt; Anil Kumar Sinha; Mariya Dayana P J; Murtaza Hasan; Parvathi Geetha Sreekantan
Abstract
The rapid development of road networks needs huge construction materials. Mining and industrial wastes can be used as sustainable road construction materials and will be alternatives to fulfill the huge demand in road construction. Zinc tailing is one such mining waste and has the potential for road ...
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The rapid development of road networks needs huge construction materials. Mining and industrial wastes can be used as sustainable road construction materials and will be alternatives to fulfill the huge demand in road construction. Zinc tailing is one such mining waste and has the potential for road construction. This material was collected from Zawar mines (Rajasthan), and characterization was carried out for embankment/subgrade applications. A physical model test was conducted in the laboratory to examine the stress-settlement behaviour. To improve the modulus value of tailing, it was reinforced with geogrid in two different laying patterns, viz. layer/loop and stress-settlement behavior was studied. Different parameters were studied: reinforcement depth, layer of reinforcement, number of loops, and depth of loop of reinforcement. The experimental result was validated with the numerical finite element method (SoilWorks). Tailing comprises fine-grained silt-size particles (61%) with no swelling behavior and non-plastic nature. It has values of MDD and OMC as 1.86 g/cm3 and 11%, respectively. It has a higher value of CBR (12%) and internal friction angle (34.6o) with cohesionless nature. The variation of settlement with stress is linear for reinforced and unreinforced tailing fill. As the depth of reinforcement increases, settlement increases in both layer and loop reinforcement. The settlement trajectory obtained from a numerical method closely resembles that of a laboratory physical model, particularly when the applied stress is up to 600 kPa. The modulus of elasticity of tailing was significantly improved with the introduction of geogrid reinforcement either in layer or loop.
Case Study
Environment
Aditi Nag; Smriti Mishra
Abstract
The convergence of Mining Heritage Tourism (MHT) and Artificial Intelligence (AI) presents a transformative paradigm, reshaping heritage preservation, visitor engagement, and sustainable growth. This paper investigates the dynamic synergy between these realms, probing how AI-driven technologies can augment ...
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The convergence of Mining Heritage Tourism (MHT) and Artificial Intelligence (AI) presents a transformative paradigm, reshaping heritage preservation, visitor engagement, and sustainable growth. This paper investigates the dynamic synergy between these realms, probing how AI-driven technologies can augment the authenticity, accessibility, and educational significance of mining heritage sites. Focusing on the profound impact of AI on MHT, this study centers its examination on the Barr Conglomerate located in the culturally rich Pali District, India. Employing a mixed-methods approach involving survey data analysis and neural network modelling, the research work explores AI applications that enhance visitor experiences, interpret historical narratives, optimize resource allocation, and mitigate the adverse effects of over-tourism. The study meticulously navigates a vast landscape of AI technologies, spanning machine learning, natural language processing, and augmented reality, show-casing their potential to enrich encounters with mining heritage. While AI promises to revolutionize heritage management, the paper emphasizes the critical importance of ethical considerations and cultural sensitivities. Balancing innovation with preservation, the study advocates for an inclusive approach that honors diverse cultural values and encourages community engagement. Through this exploration, the paper delves into the practical implementation of AI, unveiling best practices lessons learned and illuminating challenges and opportunities. Ultimately, this research work envisions a future where AI empowers mining heritage to transcend temporal boundaries, cultivating immersive experiences resonating with authenticity, global understanding, and sustainable stewardship.
Case Study
Mineral Processing
SAHIL KUMAR; Ravi Kumar Sharma
Abstract
Landslides affecting life and property losses has become a serious threat in various countries worldwide which highlights the importance of slope stability and mitigation. The methods and tools employed for slope stability analysis, ranging from traditional limit equilibrium methods to worldly-wise numerical ...
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Landslides affecting life and property losses has become a serious threat in various countries worldwide which highlights the importance of slope stability and mitigation. The methods and tools employed for slope stability analysis, ranging from traditional limit equilibrium methods to worldly-wise numerical modelling techniques. It focuses on the importance of accurate and reliable data collection, including geotechnical investigations, in developing precise slope stability assessments. Further, it also addresses challenges associated with predicting and mitigating slope failures, particularly in dynamic and complex environments. Mitigation strategies for unstable slopes were systematically reviewed of different researchers, encompassing both traditional and innovative measures. Traditional methods, such as retaining walls and drainage systems, the mitigation strategies were explored, emphasizing both preventive measures and remedial interventions. These include the implementation of engineering solutions such as slope structures, and Matrix Laboratory (MATLAB) techniques along with the comprehensive analysis of four prominent slope stability assessment tools: Rock Mass Rating (RMR), Slope Mass Rating (SMR), and the Limit Equilibrium Method (LEM). The comparative analysis of these tools highlights their respective strengths, limitations, and areas of application, providing researchers, authors, and practitioners with valuable insights to make informed choices based on project-specific requirements. To ensure the safety and sustainability of civil infrastructure, a thorough understanding of geological, geotechnical, and environmental factors in combination with cutting-edge technologies is required. Furthermore, it highlights the important role that slope stability assessment and mitigation play a major role in civil engineering for infrastructure development and mitigation strategies.
Original Research Paper
Rock Mechanics
Naeem Abbas; Li Kegang
Abstract
The study examined the influence of cohesion, friction angle, and tunnel diameter on stability within engineering and geotechnical frameworks, while considering the consequences of nearby excavations on the overall stability assessment. The results show that a higher angle of internal friction leads ...
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The study examined the influence of cohesion, friction angle, and tunnel diameter on stability within engineering and geotechnical frameworks, while considering the consequences of nearby excavations on the overall stability assessment. The results show that a higher angle of internal friction leads to a decrease in soil stability number and weighting coefficient. Tunnel diameter significantly affects face support pressure, with larger diameters requiring stronger support due to increased stress. Higher friction angles help stabilize tunnel faces and mitigate diameter-related pressure effects. Stress redistribution around the tunnel is significant within 2 meters from the center, transitioning to elastic behavior elsewhere. A safety factor of 1.3 ensures tensile failure prevention in single and twin tunnels. Balanced stress distribution between tunnels with a slight difference is observed under isotropic in-situ stress. Numerical modeling enhances stress estimations and reveals changes during tunnel excavation, weakening the rock mass. Ground reaction curve analysis with support measures shows reduced tunnel convergence after implementation, suggesting support strategies like extended bolts using updated rock mass rating. The study improves tunnel design and stability assessment by comprehensively understanding stress redistribution and support strategies.
Review Paper
Rock Mechanics
Tanya Thakur; Kanwarpreet Singh; Abhishek Sharma
Abstract
Landslides affecting life and property losses has become a serious threat in various countries worldwide which highlights the importance of slope stability and mitigation. The methods and tools employed for slope stability analysis, ranging from traditional limit equilibrium methods to worldly-wise numerical ...
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Landslides affecting life and property losses has become a serious threat in various countries worldwide which highlights the importance of slope stability and mitigation. The methods and tools employed for slope stability analysis, ranging from traditional limit equilibrium methods to worldly-wise numerical modeling techniques. It focuses on the importance of accurate and reliable data collection, including geotechnical investigations, in developing precise slope stability assessments. Further, it also addresses challenges associated with predicting and mitigating slope failures, particularly in dynamic and complex environments. Mitigation strategies for unstable slopes were systematically reviewed of different researchers, encompassing both traditional and innovative measures. Traditional methods, such as retaining walls and drainage systems, the mitigation strategies were explored, emphasizing both preventive measures and remedial interventions. These include the implementation of engineering solutions such as slope structures, and Matrix Laboratory (MATLAB) techniques along with the comprehensive analysis of four prominent slope stability assessment tools: Rock Mass Rating (RMR), Slope Mass Rating (SMR), and the Limit Equilibrium Method (LEM). The comparative analysis of these tools highlights their respective strengths, limitations, and areas of application, providing researchers, authors, and practitioners with valuable insights to make informed choices based on project-specific requirements. To ensure the safety and sustainability of civil infrastructure, a thorough understanding of geological, geotechnical, and environmental factors in combination with cutting-edge technologies is required. Furthermore, it highlights the important role that slope stability assessment and mitigation play a major role in civil engineering for infrastructure development and mitigation strategies.
Original Research Paper
Environment
Anna Perevoshchikova; Elizaveta Malyshkina; Natalia Mitrakova; Nikita Kobelev; Larisa Rudakova
Abstract
The utilisation of potash reserves has various environmental consequences, such as the generation of substantial volumes of solid waste containing high levels of sodium chloride. The accumulation of environmental harm gives rise to an unfavourable environmental scenario in potash production areas, which ...
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The utilisation of potash reserves has various environmental consequences, such as the generation of substantial volumes of solid waste containing high levels of sodium chloride. The accumulation of environmental harm gives rise to an unfavourable environmental scenario in potash production areas, which requires the investigation of waste management solutions. The predominant approach to reducing surface waste involves backfilling mined areas. In other countries, salt dump reclamation is utilised alongside backfilling. The distinctive characteristic of salt dump reclamation lies in the water-solubility and phytotoxicity of the dump rock. This research aims to evaluate the morphometric and biochemical parameters (using phytotesting) of vegetation throughout the process of salt dump reclamation using different variants. A model reclamation was carried out in a laboratory setting, where three different variants were subjected to experimentation. A reduction in the thickness of the protective clay barrier resulted in a decline in morphometric aspects of the experimental crops as well as the woody vegetation. Reducing the thickness of the protective clay barrier leads to an elevation in the redox activity of the examined crops, thus pointing towards potential environmental toxicity. Superior morphometric and biochemical parameters were noted in vegetation possessing a substantial protective covering, hinting at the feasibility of utilising insulating layers for salt dump reclamation. Phytotesting serves as an indicative approach to assessing soil toxicity and as a parameter for determining soil resilience against pollution. The findings hold potential for application in further research within the field of biological reclamation in areas with dump sites.
Original Research Paper
Exploitation
AVULA RAJASHEKAR YADAV; Sreenivasa Rao Islavath; Srikanth katkuri
Abstract
The installation gallery/set-up room of a longwall panel is driven for installation of the longwall face machineries to start the extraction of coal from the longwall panel. The width of the installation gallery is 8 to 9 m. This gallery needs to be stabilized till the face machineries to be deployed ...
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The installation gallery/set-up room of a longwall panel is driven for installation of the longwall face machineries to start the extraction of coal from the longwall panel. The width of the installation gallery is 8 to 9 m. This gallery needs to be stabilized till the face machineries to be deployed from the driving of the room as it required to stand more than 8 to 10 months and develop the high stress concentration, roof-to-floor convergence and yield zone in the roof and sides. Hence, in this study, a deep longwall mine of India is considered to analyze the behavior of set-up room. For this, a total of twelve 3D numerical models are developed and analyzed considering Mohr’s-Coulomb failure criterion. Three panels located at 417, 462, 528 m having three different widths (8, 10 and 12 m) of set-up rooms are examined. The width of the set-up room is taken based on the length of the shield support. The results in terms of vertical stress distribution, vertical displacement, roof-to-floor convergence, plastic strain and yield zone distribution are presented.
Review Paper
Environment
Kushai Caleb Aluwong; Mohd Hazizan bin Mohd Hashim; Suhaina Ishmail
Abstract
In the past, assessing water quality has typically involved labor-intensive and costly processes such as laboratory analysis and manual sampling, which do not provide real-time data. In addition to tasting bad, drinking acidic water on a regular basis can result in acid reflux and recurrent heartburn ...
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In the past, assessing water quality has typically involved labor-intensive and costly processes such as laboratory analysis and manual sampling, which do not provide real-time data. In addition to tasting bad, drinking acidic water on a regular basis can result in acid reflux and recurrent heartburn while high total dissolved solids water can cause kidney stones, especially when the hard water content is more than 500ppm. With growing concerns about water quality, there is a need for continuous monitoring of pH and TDS levels in surface and groundwater sources. To address this, a cutting-edge wireless sensor system leveraging on Internet of Things (IoT) technology has been developed. This system incorporates top-notch pH and TDS sensors known for their accuracy, durability, and environmental compatibility. Integrated with microcontrollers featuring wireless communication capabilities, these sensors enable seamless data transmission to a central server through IoT protocols like cellular networks. The collected data is processed and calibrated to ensure reliability and precision. The IoT platform connected to the central server manages device connectivity, data storage, and analysis, making real-time data accessible via user-friendly web or mobile applications with interactive graphs and dashboards. Power-saving features are implemented to optimize battery life in remote and off-grid locations, and weather-resistant enclosures protect the sensor nodes from harsh environmental conditions. By deploying this wireless-based sensor system, users can gain valuable real-time insights into water quality in surface and groundwater monitoring locations.
Original Research Paper
Exploitation
Soufi Amine; Zerradi Youssef; Bahi Anas; Ouadif Latifa; Soussi Mohamed
Abstract
The aim of this study is to thoroughly analyze the relaxation zone developing around sublevel stopes in underground mines and identify the main parameters controlling its extent. A numerical approach based on the finite element method, combined with the Hoek-Brown failure criterion, was implemented to ...
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The aim of this study is to thoroughly analyze the relaxation zone developing around sublevel stopes in underground mines and identify the main parameters controlling its extent. A numerical approach based on the finite element method, combined with the Hoek-Brown failure criterion, was implemented to simulate various geometric configurations, geological conditions, and in-situ stress states. A total of 425 simulations were carried out by varying depth, horizontal-to-vertical stress ratio (k), rock mass quality (RMR), foliation orientation and spacing, as well as the height, width, and inclination of the sublevels. The results enabled the development of robust predictive models using regression analysis techniques and artificial neural networks (ANNs) to estimate the extent of the relaxation zone as a function of the different input parameters. It was demonstrated that depth and the k ratio significantly influence the extent of the relaxation zone. Additionally, a decrease in rock mass quality leads to a substantial increase in this zone. Structural characteristics, such as foliation orientation and spacing, also play a decisive role. Finally, the geometric parameters of the excavations, notably the height, width, and inclination of the sublevels, directly impact stress redistribution and the extent of the relaxation zone. The overall ANN model, taking into account all these key parameters, exhibited high accuracy with a correlation coefficient of 0.97. These predictive models offer valuable tools for optimizing the design of underground mining operations, improving operational safety, and increasing productivity.
Original Research Paper
Exploitation
Marco Antonio Cotrina Teatino; Jairo Jhonatan Marquina Araujo; Eduardo Manuel Noriega Vidal; Jose Nestor Mamani Quispe; Johnny Henrry Ccatamayo Barrios; Joe Alexis Gonzalez Vasquez; Solio Marino Arango Retamozo
Abstract
The primary objective of this research was to apply machine learning techniques to predict the production of an open pit mine in Peru. Four advanced techniques were employed: Random Forest (RF), Extreme Gradient Boosting (XGBoost), K-Nearest Neighbors (KNN), and Bayesian Regression (RB). The methodology ...
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The primary objective of this research was to apply machine learning techniques to predict the production of an open pit mine in Peru. Four advanced techniques were employed: Random Forest (RF), Extreme Gradient Boosting (XGBoost), K-Nearest Neighbors (KNN), and Bayesian Regression (RB). The methodology included the collection of 90 datasets over a three-month period, encompassing variables such as operational delays, operating hours, equipment utilization, the number of dump trucks used, and daily production. The data were allocated 70% for training and 30% for testing. The models were evaluated using metrics such as Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Variance Accounted For (VAF), and the Coefficient of Determination (R2). The results indicated that the Bayesian Regression model was the most effective in predicting production in the open pit mine. The RMSE, MAPE, VAF, and R2 for the models were 3686.60, 3581.82, 4576.61, and 3352.87; 12.65, 11.09, 15.31, and 11.90; 36.82, 40.72, 1.85, and 47.32; 0.37, 0.41, 0.41, and 0.47 for RF, XGBoost, KNN, and RB, respectively. This research highlights the efficacy of machine learning techniques in predicting mine production and recommends adjusting each model's parameters to further enhance outcomes, significantly contributing to strategic and operational management in the mining industry.
Original Research Paper
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%.
Original Research Paper
Exploitation
Meisam Saleki; Reza Khaloo Kakaie; Mohammad Ataei; Ali Nouri Qarahasanlou
Abstract
One of the most critical designs in open-pit mining is the ultimate pit limit (UPL). The UPL is frequently computed initially through profit-maximizing algorithms like the Lerchs-Grossman (LG). Then, in order to optimize net present value (NPV), production planning is executed for the blocks that ...
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One of the most critical designs in open-pit mining is the ultimate pit limit (UPL). The UPL is frequently computed initially through profit-maximizing algorithms like the Lerchs-Grossman (LG). Then, in order to optimize net present value (NPV), production planning is executed for the blocks that fall within the designated pit limit. This paper presents a mathematical model of the UPL with NPV maximization, enabling simultaneous determination of the UPL and long-term production planning. Model behavior is nonlinear. Thus, in order to achieve model linearization, the model has been partitioned into two linear sub-problems. The procedure facilitates the model solution and the strategy by decreasing the number of decision variables. Naturally, the model is NP-Hard. As a result, in order to address the issue, the Dynamic Pit Tracker (DPT) heuristic algorithm was devised, accepting economic block models as input. A comparison is made between the economic values and positional weights of blocks throughout the steps in order to identify the most appropriate block. The outcomes of the mathematical model, LG, and Latorre-Golosinski (LAGO) algorithms were assessed in relation to the DPT on a two-dimensional block model. Comparative analysis revealed that the UPLs generated by these algorithms are consistent in this instance. Utilizing the new algorithm to determine UPL for a 3D block model revealed that the final pit profit matched LG UPL by 97.95%.
Original Research Paper
Exploitation
Mehdi Rahmanpour; Golpari Norozi; Hassan Bakhshandeh Amnieh
Abstract
Drift-and-fill mining is a variation of cut-and-fill mining method. Drift-and-fill mining method refers to the excavation of several parallel drifts in ore. Excavation of a new drift could start when its adjacent drifts are backfilled or not excavated. The amount of ore material and its grade depends ...
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Drift-and-fill mining is a variation of cut-and-fill mining method. Drift-and-fill mining method refers to the excavation of several parallel drifts in ore. Excavation of a new drift could start when its adjacent drifts are backfilled or not excavated. The amount of ore material and its grade depends on the excavation sequence of drifts. As the number of drifts increases, one will need a model to optimize the drift excavation and backfilling sequence. This paper introduces a mathematical model to determine the optimal drift-and-fill sequence while the safety constraints, excavation, and backfilling capacities and their dependencies are satisfied. The model seeks to minimize the deviations from some predefined goals, and it handles the long-term and short-term constraints in separate and integrated scenarios. An application of the model is presented based on the data available from a lead/zinc underground mining project. There are 91 drifts in the selected level. Based on the monthly planning horizon, the integrated model leads to the slightest deviations in both the mining rate and average grade, and the deviation from the predetermined annual goals is negligible. For the case where long-term and short-term plans are determined separately, the deviation is approximately 10%.
Original Research Paper
Exploration
Ali Aalianvari; shirin Jahanmiri; malihehe Abbaszadeh
Abstract
Groundwater inflow is a critical subject within the domains of hydrology, hydraulic engineering, hydrogeology, rock engineering, and related disciplines. Tunnels excavated below the groundwater table, in particular, face the inherent risk of groundwater seepage during both the excavation process and ...
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Groundwater inflow is a critical subject within the domains of hydrology, hydraulic engineering, hydrogeology, rock engineering, and related disciplines. Tunnels excavated below the groundwater table, in particular, face the inherent risk of groundwater seepage during both the excavation process and subsequent operational phases. Groundwater inflows, often perceived as rare geological hazards, can induce instability in the surrounding rock formations, leading to severe consequences such as injuries, fatalities, and substantial financial expenditures. The primary objective of this research is to explore the application of machine learning techniques to identify the most accurate method of forecasting tunnel water seepage. The prediction of water loss into the tunnel during the forecasting phase employed a tree equation based on gene expression programming (GEP). These results were compared with those obtained from a hybrid model comprising particle swarm optimization (PSO) and artificial neural networks (ANN). The Whale Optimization Algorithm (WOA) was selected and developed during the optimization phase. Upon contrasting the aforementioned methods, the Whale Optimization Algorithm demonstrated superior performance, precisely forecasting the volume of water lost into the tunnel with a correlation coefficient of 0.99. This underscores the effectiveness of advanced optimization techniques in enhancing the accuracy of groundwater inflow predictions and mitigating potential risks associated with tunneling activities.
Original Research Paper
Mineral Processing
Alireza Javadi
Abstract
The main and economic mineral of antimony is stibnite or antimony sulfide, and the research and processes in the world are based on it, and oxide minerals are not considered among the economic and important reserves of antimony due to the difficulty of processing and the lack of optimal efficiency of ...
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The main and economic mineral of antimony is stibnite or antimony sulfide, and the research and processes in the world are based on it, and oxide minerals are not considered among the economic and important reserves of antimony due to the difficulty of processing and the lack of optimal efficiency of the flotation method. On the other hand, taking into account that a large part of the antimony reserve of Sefidabeh is made up of low-grade oxidized ore; this research on the method of economic extraction and the possibility of recovering this type of reserve will be important due to the strategic nature of antimony metal. According to the experiments conducted in this research, the effective parameters for flotation include: pH, collector concentration, activator concentration, depressant concentration, activator type, and humic acid concentration. DX7 software was used for statistical modeling of experiments. Based on the above parameters, the design of the experiment was carried out using a partial factorial method and finally the number of 16 experiments was determined for the effect of the above factors on the grade and weight recovery of the sample. Antimony ore flotation with a grade of 4.32% was carried out in a two-stage method. In this method, in the first stage, flotation of antimony sulfur (stibnite, Sb2S3) was performed at a specific pH by adding the activator of copper sulfate or lead nitrate and the depressant together, potassium amyl xanthate collector and MIBC. In the second stage of flotation, the tailings of the first stage of flotation for antimony oxides were treated with a sodium oleate collector (with determined concentrations) at a specific pH by adding copper sulfate or lead nitrate activator, sodium oleate collector and humic acid and MIBC frother agent. The interaction between pH and activator concentration (BD) has a direct effect on the amount of concentrated antimony, with an increase in pH from 6 to 8 antimony when using an activator concentration of 300 g/t, and a decrease when using an activator concentration of 500 g/t. Flotation was done. In the best conditions, with two-stage flotation of antimony, 68.99% recovery and 13.32 grade were obtained.
Original Research Paper
Exploitation
Mohammad Sina Abdollahi; Mehdi Najafi; Alireza Yarahamdi Bafghi; Ramin Rafiee
Abstract
The stability analysis of chain pillars is crucial, especially as coal extraction rates increase, making it essential to reduce the size of these pillars. Therefore, a new method for estimating the load on chain pillars holds significant importance. This research introduces a novel solution for estimating ...
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The stability analysis of chain pillars is crucial, especially as coal extraction rates increase, making it essential to reduce the size of these pillars. Therefore, a new method for estimating the load on chain pillars holds significant importance. This research introduces a novel solution for estimating side abutment load and analyzing the stability of chain pillars using the dynamic mode of the Coulmann Graphical (CG) method. The solution is implemented using Visual Studio software and is named Coulmann Chain Pillar Stability Analysis (CCPSA). The CG method is widely recognized in civil engineering as a highly efficient technique for determining soil side abutment pressure in both static and dynamic conditions. This method involves calculating the top-rupture wedge of chain pillars using the CG method. The CCPSA software functions share significant similarities with those of the Analysis Longwall Pillar Stability (ALPS) method. However, the main point of departure between the proposed method and the ALPS empirical method lies in their respective approaches to calculating side abutment load on chain pillars and evaluating subsidence conditions. The effectiveness of this method has been validated using a database of chain pillars from various mines worldwide and has been compared with the ALPS method. The results of the comparison demonstrate that the CCPSA is highly effective in evaluating chain pillar stability. This underscores the potential of the CG method and CCPSA software in providing valuable insights for assessing and ensuring the stability of chain pillars in mining operations.
Case Study
Exploration
Moslem Jahantigh; Hamid Reza Ramazi
Abstract
The present paper gives out data-driven method with airborne magnetic data, airborne radiometric data, and geochemistry data. The purpose of this study is to create a mineral potential model of the Shahr-e-Babak studied area. The studied area is located in the south-eastern of Iran. The various evidential ...
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The present paper gives out data-driven method with airborne magnetic data, airborne radiometric data, and geochemistry data. The purpose of this study is to create a mineral potential model of the Shahr-e-Babak studied area. The studied area is located in the south-eastern of Iran. The various evidential layers include airborne magnetic data, airborne radiometric data (potassium and thorium), lineament density map, cu geochemistry signature, and multi-variate geochemistry signature (PC1). High magnetic anomalies, lineament structures, and alteration zones (K/Th) were derived from airborne geophysics data. Geochemistry signatures (Cu and PC1) were derived from stream sediment data. The principal Component Analysis (PCA) as an unsupervised machine learning method and five evidential layers were used to produce a porphyry prospectivity model. As a result of this combination, mineral prospectivity model was produced. Then a plot of cumulative percent of the studied area versus pca prospectivity value was used to discrete high potential areas. Then to evaluate the ability of this MPM, the location of known cu indications was used. The results confirm an acceptable outcome for porphyry prospectivity modeling. Based on this model high-potential areas are located in south southwestern and eastern parts of the studied area.
Original Research Paper
Exploitation
Elham Lotfi; Javad Gholamnejad; Mehdi Najafi; Mohammad Sadegh Zamani; Mahboobe Honarvar
Abstract
In the context of open pit mining operations, long-term production scheduling faces significant challenges due to inherent uncertainties, particularly in commodity prices. Traditional mathematical models often adopt a single-point estimation strategy for commodity price, leading to suboptimal mine plans ...
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In the context of open pit mining operations, long-term production scheduling faces significant challenges due to inherent uncertainties, particularly in commodity prices. Traditional mathematical models often adopt a single-point estimation strategy for commodity price, leading to suboptimal mine plans and missed production targets. The simultaneous effect of commodity price uncertainty on the cut-off grade and long-term production scheduling is less considered. This paper introduces a novel model for optimizing open pit mine long-term production scheduling under commodity price uncertainty considering a dynamic cut-off grade strategy, based on a two-stage Stochastic Production Programming (SPP) framework. The presented model seeks to identify optimal mining block sequences, maximizing total discounted cash flow while penalizing deviations from production targets. To illustrate the model's efficiency, it was implemented in a copper mine. First, the Geometric Brownian Motion (GBM) model is used to quantify the future commodity price. Then, both deterministic and SPP models were solved using GAMS software. The results showed that the practical NPV obtained from the SPP model is approximately 3% higher than the DPP model, while all constraints are satisfied.
Original Research Paper
Rock Mechanics
masoud yazdani; Mohammad Fatehi Marji; Hamid Soltanian; Mehdi Najafi; Manouchehr Sanei
Abstract
Approximately 70% of the world's hydrocarbon fields are located in reservoirs with low-strength rocks such as sandstone. During the production of hydrocarbons from sandstone reservoirs, sand-sized particles may become dislodged from the formation, and enter the hydrocarbon fluid flow. Sand production ...
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Approximately 70% of the world's hydrocarbon fields are located in reservoirs with low-strength rocks such as sandstone. During the production of hydrocarbons from sandstone reservoirs, sand-sized particles may become dislodged from the formation, and enter the hydrocarbon fluid flow. Sand production is a significant issue in the oil industry due to its potential to cause erosion of pipes and valves. Separating grains from oil is a costly process. Therefore, oil and gas-producing companies are motivated to reduce sand production during petroleum extraction. Various methods exist for predicting this phenomenon including continuous, discontinuous, experimental, physical, analytical, and numerical methods. Given the significance of the subject, this research work aims to achieve two primary objectives. Firstly, it proposes a two-dimensional numerical model based on the discrete element method to address the issues of high strain and deformation in granular materials. This method is highly reliable in simulating the mechanism of sand production in oil wells. Secondly, the production of sand is influenced by two factors: fluid pressure and stress; to evaluate changes in production from a particular reservoir, it is necessary to analyze each parameter. Two sandstone samples, similar to reservoir rock conditions, were prepared and tested in the laboratory to demonstrate sand production phenomenon. The numerical results have been verified and compared to their experimental counterparts.
Original Research Paper
Exploitation
Mehrnaz Mohtasham; Hossein Mirzaei Nasir Abad; Farshad Rahimzadeh-Nanekaran
Abstract
Transportation of materials is the most cost-intensive component in open-pit mining operations. The aim of the allocation models is to manage and optimize transportation activities, leading to reduced wasted time, and ultimately, increasing profitability while reducing operational costs. Given that the ...
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Transportation of materials is the most cost-intensive component in open-pit mining operations. The aim of the allocation models is to manage and optimize transportation activities, leading to reduced wasted time, and ultimately, increasing profitability while reducing operational costs. Given that the implementation of allocation models is one of the essential requirements in Iranian mining operations, this research work focuses on the transportation system in the Sungun copper mine, one of the largest mines in Iran, and highlights the challenges faced by the fixed allocation approach. The aim is to develop and implement a mathematical model to evaluate its performance, and suggest improvements. The allocation model attempts to optimize truck capacity utilization and maximize mining production. Implementing the model in the mine results in a 13.42% increase in total production compared to the conventional method, with a cost increase of 14.7%. The model shows the potential to meet operational and technical constraints to achieve optimal production. Overall, the developed model, with optimized management and improved fleet efficiency, outperforms the traditional haulage method in the mine.
Original Research Paper
Exploitation
Behnam Alipenhani; mehran jalilian; Abbas Majdi; Hassan Bakhshandeh Amnieh; Mohammad Hossein Khosravi
Abstract
The paper presents the effect of the dip of joints, joint spacing, and the undercutting method on the height of the caving in block caving. The obtained results show that among the three investigated parameters, respectively, the dip of joints, undercutting method, and joint spacing have the greatest ...
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The paper presents the effect of the dip of joints, joint spacing, and the undercutting method on the height of the caving in block caving. The obtained results show that among the three investigated parameters, respectively, the dip of joints, undercutting method, and joint spacing have the greatest effect on increasing the height of the caving zone. Comparing the data obtained from physical and numerical modeling shows a 97% match. Also, by increasing the joint spacing from 4 to 6 cm, 14%, from 6 to 8 cm, about 35%, and from 8 to 10, about 50%, the height of the caving zone has decreased. Regarding the dip of the joint, with the dip increasing from 30 to 45 degrees, about 3% of the caving height decreases. By increasing the dip of the joint from 45 to 60 degrees, the caving height has decreased by 42%. By increasing this value from 60 to 75 degrees, the caving height has increased by 50%. Also, changing the undercutting method from symmetric to advanced undercutting has increased the caving height by 40%. Additionally, three mathematical models have been proposed based on the shape of the caving zone in physical modeling.
Original Research Paper
Rock Mechanics
Mohammad Fatehi Marji; masoud yazdani; Mehdi Najafi; Manouchehr Sanei
Abstract
Around 70% of the world's hydrocarbon fields are situated in reservoirs containing low-strength rocks, such as sandstone. During the production of hydrocarbons from sandstone reservoirs, sand-sized particles may become dislodged from the formation and enter the hydrocarbon fluid flow. Sand production ...
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Around 70% of the world's hydrocarbon fields are situated in reservoirs containing low-strength rocks, such as sandstone. During the production of hydrocarbons from sandstone reservoirs, sand-sized particles may become dislodged from the formation and enter the hydrocarbon fluid flow. Sand production is a significant issue in the oil industry due to its potential to cause erosion of pipes and valves. Separating grains from oil is a costly process. Oil and gas companies are motivated to reduce sand production during petroleum extraction. Hydraulic fracturing is one of the parameters that can influence sand production. However, understanding the complex interactions between hydraulic fracturing mechanisms and sand production around wellbores is critical for optimizing reservoir recovery and ensuring the integrity of production wells. This article explores the integrated simulation approach to model hydraulic fracturing processes and assess their effects on sand production. Two-dimensional models were created using the discrete element method in PFC2D software for this research. The fractures' length in the models varies based on the well's radius. The angle between two fractures at 90 and 180 degrees to each other was also modeled. In the first case, the length of the fracture is less than the radius of the well, in the second case, the values are equal and finally, the fracture length is assumed to exceed the well radius. The calibrated and validated results demonstrate the change in sand production rate in comparison to the unbroken state.
Original Research Paper
Exploration
Sepideh Ghasemi; Ali Imamalipur; Samaneh Barak
Abstract
This investigation centers on the Qarah Tappeh copper deposit, situated in the northern region of West Azerbaijan province, approximately 15 kilometers northeast of Maku city. The primary objective of the study is to comprehensively examine the study area through the analysis of 253 lithogeochemical ...
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This investigation centers on the Qarah Tappeh copper deposit, situated in the northern region of West Azerbaijan province, approximately 15 kilometers northeast of Maku city. The primary objective of the study is to comprehensively examine the study area through the analysis of 253 lithogeochemical samples, and assessing reserves utilizing ordinary kriging, guided by subsurface data obtained from 14 boreholes totaling 909.2 meters. The concentration–volume (C–V) multifractal modeling approach was employed to estimate the deposit's reserve. The findings of this research project indicate an estimated 988,604 tons of the deposit with an average grade of 0.14%. Through the analysis of log–log plots within the C–V relationship, threshold values signifying various copper (Cu) concentrations were identified. These plots revealed a pronounced power-law correlation between Cu concentrations and their corresponding volumes, with arrows denoting four specific threshold values. Utilizing this analytical methodology, mineralized zones were classified into five distinct categories: high (>0.42%), above-average (0.35-0.42%), average (0.27-0.35%), below-average (0.14-0.27%), and low (<0.14%) mineralized zones.
Original Research Paper
Exploration
Hossein Mahdiyanfar; Mirmahdi Seyedrahimi-Niaraq
Abstract
In this investigation, the hybrid approach of wavelet transforms and fractal method named Wavelet-Fractal model has been utilized for geochemical contamination mapping as a novel application. For this purpose, the distribution maps of pollutant elements were transformed to the position-scale domain using ...
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In this investigation, the hybrid approach of wavelet transforms and fractal method named Wavelet-Fractal model has been utilized for geochemical contamination mapping as a novel application. For this purpose, the distribution maps of pollutant elements were transformed to the position-scale domain using two-dimensional discrete wavelet transformation (2DDWT). The Symlet2 and Haar mother wavelets were applied for two-dimensional signal analysis of elemental concentrations of As, Pb, and Zn based on soil samples taken from the Irankuh mining district, Central Iran. The Symlet2 and Haar wavelet coefficients of approximate and detail components were obtained at one level frequency decomposition using 2DDWT. The wavelet coefficients of approximate component (WCAC) were modeled using a fractal method for delineating the geochemical contamination populations of toxic elements. Based on the results of wavelet-fractal models, the As, pb, and Zn were classified into three and four populations. Two areas contaminated with metals have been found in the district. These areas are within the limit of mining operations and its surroundings. The wavelet-fractal proposed model has been able to separate environmental areas contaminated with toxic metals accurately. Anomalously intense pollution has spread to one kilometer outside the mining operation limit. This dispersion in the case of Pb and Zn elements is well seen in the geochemical map prepared with the Haar class.
Original Research Paper
Mineral Processing
ahmad abbasi gharaei; Bahram Rezai; Hadi Hamidian
Abstract
This paper examines the performance of Atmospheric Leaching (AL) and High-Pressure Acid Leaching (HPAL) on nickel laterite, classified as limonite. The study, conducted on a laboratory scale, involved temperatures of 35-95°C for AL and 220-250°C for HPAL. Nickel and cobalt contents were found ...
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This paper examines the performance of Atmospheric Leaching (AL) and High-Pressure Acid Leaching (HPAL) on nickel laterite, classified as limonite. The study, conducted on a laboratory scale, involved temperatures of 35-95°C for AL and 220-250°C for HPAL. Nickel and cobalt contents were found to be 0.7% and 0.04%, respectively. AL achieved an 89% yield of Al with a pH of 0.2 and a 14-hour leaching time, while nickel and iron recoveries reached 92% and 87% after 20 hours, with an acid consumption of 1.2 kg H2SO4 per 100 kg laterite (dry) at pH 0.2. Leaching experiments at 220-250°C for 2 hours showed similar nickel recovery rates, indicating no improvement beyond 240°C. Hematite, a stable compound associated with nickel, hindered its release during HPAL due to its resistance to leaching. Nickel yields remained around 90% in both AL and HPAL tests. Iron behavior differed significantly between the two methods, with HPAL dissolving iron initially but transforming it into hematite in situ, leading to lower net acid consumption compared to AL. The leaching mechanism for iron oxides followed empirical power law kinetics of order 1.5 with activation energies of 36.23 and 25.09 kJ/mol for Ni and Fe, respectively.
Original Research Paper
Exploitation
Sri Chandrahas
Abstract
To conducting efficient blasting operations, one needs to analyze the bench geology, structural and dimensional parameters to obtain the required optimum fragmentation with minimum amount of ground vibration. Joints presence causes difficulty during drilling and subsequent rock breakage mechanism. An ...
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To conducting efficient blasting operations, one needs to analyze the bench geology, structural and dimensional parameters to obtain the required optimum fragmentation with minimum amount of ground vibration. Joints presence causes difficulty during drilling and subsequent rock breakage mechanism. An idea on joints density will give an idea on deciding with column charging in-terms of decking-stemming and firing patterns. The goal of the research is to develop a hybrid algorithm model to predict joints width and joint angle. In order to achieve the task, advanced softwares, machine learning models and a field data tests were used in this study.
Original Research Paper
Rock Mechanics
Manendra Singh; Moqin Mushtaq Zargar; Vivek Kumar Sharma; Ritu Raj Nath
Abstract
Non-structural slope stabilization techniques are gaining popularity for cost-affordability and environmental sustainability and are intended primarily to enhance the soil shear strength parameters. The present study evaluates the performance of three biopolymers: Guar Gum, Gellan Gum, and Xanthan Gum ...
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Non-structural slope stabilization techniques are gaining popularity for cost-affordability and environmental sustainability and are intended primarily to enhance the soil shear strength parameters. The present study evaluates the performance of three biopolymers: Guar Gum, Gellan Gum, and Xanthan Gum as slope stabilizers for a quintessential soil slope of a local district in the foothills of the Lesser Himalayas. The study measures the shear strength of biopolymer-treated soil at varying concentrations and moisture contents, and concludes that the soil shear strength is highly influenced by the concentration of biopolymer and the moisture content. The results demonstrate significant increase (48% and 7%) of the cohesion and friction angle of a particular biopolymer-treated sample for a specific moisture content. However, the addition of biopolymers to the soil also leads to a decrease in the permeability of the original sample. The study, in the next phase, numerically computes the Factor of Safety of the test-bed slope before and after the application of biopolymers, and observes that the addition of biopolymers in soil significantly increases (34%) the factor of safety at an optimum combination concentration and moisture content for all three biopolymers. This signifies their utility as non-structural slope stabilizers. By highlighting the improved shear strength of the biopolymer-treated soils, the study complements the current initiatives for non-structural slope stabilization and sustainable soil enhancement and adds to the new yet expanding body of information regarding long-term, non-structural slope stabilizing techniques.
Original Research Paper
Exploration
Babak Sohrabian; Erhan Tercan
Abstract
Mineral Resources have commonly been estimated through the kriging method that assigns weights to the samples based on variogram distance to the estimation point without considering their values. More robust estimators such as spatial copulas are promising tools because they consider both distance ...
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Mineral Resources have commonly been estimated through the kriging method that assigns weights to the samples based on variogram distance to the estimation point without considering their values. More robust estimators such as spatial copulas are promising tools because they consider both distance and sample values in determining weights. The purpose of this study is to demonstrate the effectiveness of the Gaussian copulas (GC) by estimating the copper grade values in the Sungun porphyry copper deposit located in Iran. Performance of the method was compared to ordinary kriging (OK) and indicator kriging (IK) by running the Jackknife test of cross-validation. The metrics used in measuring performance of the methods are global accuracy and precision of the distribution of the estimates, error statistics, and variability for globally accurate and precise estimates. The case study shows advantages of GC over OK and IK by producing globally accurate and precise estimates with acceptable error statistics and variability.
Case Study
Exploration
Moslem Jahantigh; Hamid Reza Ramazi
Abstract
Fuzzy c-means (FCM) is an unsupervised machine learning algorithm. This method assists in integrating airborne geophysics data and extracting automatic geological map. This paper tries to combine airborne geophysics data consisting of aeromagnetic, potassium, and thorium layers to classify the lithological ...
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Fuzzy c-means (FCM) is an unsupervised machine learning algorithm. This method assists in integrating airborne geophysics data and extracting automatic geological map. This paper tries to combine airborne geophysics data consisting of aeromagnetic, potassium, and thorium layers to classify the lithological map of the Shahr-e-Babak area, a world-class porphyry area in the south of Iran. The resulting clusters with FCM show appropriate coincidence with the geological map of the study area. The clusters are adapted with high magnetic anomalies corresponding to the mafic volcanic rocks and the clusters with high radiometric signature associated with igneous rocks. The cluster is associated with low magnetic anomaly and low radioelements concentration representing sedimentary rocks. some clusters are associated with two or more lithological formations due to similar signatures of geophysics properties. The fuzzy score membership in all clusters is above 0.71 indicating a high correlation between geological signatures and multigeophysical data. This study shows geophysical signatures analyzed with the machine learning method can reveal geological units.
Original Research Paper
Rock Mechanics
Hamid Chakeri; Faezeh Barri; Mohammad Darbor; Hamed Haghkish
Abstract
Excavation with Tunnel Boring Machine (TBM) in urban environments can have risks, such as ground surface settlement. The empty space between the cutterhead and the segment should be filled with suitable grout during the excavation. Nowadays, using grout behind the segment and other fillers fill the empty ...
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Excavation with Tunnel Boring Machine (TBM) in urban environments can have risks, such as ground surface settlement. The empty space between the cutterhead and the segment should be filled with suitable grout during the excavation. Nowadays, using grout behind the segment and other fillers fill the empty space behind the segment and reduce the amount of ground surface settlement. Undoubtedly, using a grout with appropriate mechanical behavior can be a suitable substitute for excavated soil in mechanized tunneling. In this research, the mechanical behavior of the grout behind the segment during injection into the space between the soil and the segment and its mixture with the soil is studied. Also, the effect of mechanical properties of grout mixed with soil on the ground surface settlement is investigated using numerical modeling. The components of two-component grout of this study comprises Sufian type 2 cement with 28-day strength of 44 MPa and density of 3050 kg/m3, Salafchegan bentonite with density of 2132 kg/m3 and precipitator of liquid sodium silicate with density of the solution 1500 kg/m3. The results of the laboratory studies indicated that mixing the grout and soil increases the mechanical properties of grout significantly. Increasing the soil in the mixture of soil and grout up to 40% increases the uniaxial compressive strength up to 300%, the elasticity of modulus up to 156% and the cohesion of the mixture up to 100%. On the other hand, based on the results of numerical modeling, the proper injection pressure can significantly reduce the ground surface settlement. Increasing the injection pressure from 0 to 120 kPa has a 17% influence on the reduction of ground surface settlement.
Review Paper
Rock Mechanics
Mohammad Reza Shahverdiloo; Shokroallah Zare
Abstract
The deformation modulus of rock mass is necessary for stability analysis of rock structures, which is generally estimated by empirical models with one to five input parameters/indexes. However, appropriate input parameter participation to establish a sound basis for a reliable prediction has been a challenging ...
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The deformation modulus of rock mass is necessary for stability analysis of rock structures, which is generally estimated by empirical models with one to five input parameters/indexes. However, appropriate input parameter participation to establish a sound basis for a reliable prediction has been a challenging task. In this study, the concept of the principal input parameters was developed based on an analytical method with an emphasis on in situ stress. Based on analytical methods, Young’s modulus of intact rock, the joint’s shear and normal stiffness, joint set spacing, and in situ stress are introduced as the main principal input parameters. A review of seventy empirical models revealed that most of them suffered from a lack of analytical parameters. Due to considering practical issues, the geological strength index (GSI) is replaced with joint set spacing; moreover, the in situ stress effect is perceived by combining Young’s modulus and joint stiffness with specific confining pressure and normal stress, respectively. The integration of the analytical base input parameters and practical issues enhanced the reliability of empirical models due to the reasonable prediction of the deformation modulus to numerical or analytical deformability analysis.
Original Research Paper
Exploitation
mohammad hossein jalalian; Raheb Bagherpour; mehrbod khoshouei; S. Najmedin Almasi
Abstract
Diamond wire cutting is a common method to extract dimension stones, which depends on various factors, including the mechanical and physical properties of the stone, cutting specifications, and operational characteristics. Specific energy, production rate, efficiency, and wear of diamond beads are some ...
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Diamond wire cutting is a common method to extract dimension stones, which depends on various factors, including the mechanical and physical properties of the stone, cutting specifications, and operational characteristics. Specific energy, production rate, efficiency, and wear of diamond beads are some of the criteria that influence economic and environmental optimization of diamond wire cutting operations. In this study, the specific energy of the diamond wire cutting process was measured for 11 samples of Granite stones. By analyzing the impact of parameters such as stone density, porosity, and cutting rate on energy consumption, a linear regression model was developed with a correlation coefficient (R2) of 0.944 to predict specific energy for different types of stones. Statistical analyses, including ANOVA, have confirmed that the model accurately predicts specific energy values. Data from three new stone samples were used to validate the model, and their predicted energy values were compared with actual values. The model presented achieved an R2 value of 0.827, demonstrating its high accuracy. The results indicate that energy consumption in dimension stone cutting operation can be accurately predicted and characterized indirectly using high precision stone properties and operational parameters. This method can accurately and indirectly monitor energy consumption and cutting machine performance during the dimension stone cutting operation and can be used to optimize economic and environmental aspects of this process.
Original Research Paper
Environment
Behnoosh khataei; Farhad Qaderi; Farzad Mosavat
Abstract
The increase in the number of factories, the industrialization of human life, and the increasing use of industrial paints have caused an increase in dye wastewater and consequent environmental pollution. Discharging wastewater containing the dyes mentioned above, which are often carcinogenic, is a severe ...
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The increase in the number of factories, the industrialization of human life, and the increasing use of industrial paints have caused an increase in dye wastewater and consequent environmental pollution. Discharging wastewater containing the dyes mentioned above, which are often carcinogenic, is a severe threat to living organisms. In this research, a photocatalytic method (as an advanced oxidation method) using zinc oxide nanoparticles was investigated to treat the colored wastewater containing methylene blue. This type of nanoparticle is cheap (based on the used synthesis method), abundant and readily available, and low in toxicity. For this purpose, an evaluation of the optimal ratio between zinc acetate and polyvinylpyrrolidone for the synthesis of zinc oxide nanoparticles was carried out. Furthermore, the simultaneous decreasing and increasing effects of independent parameters (pH, irradiation time, methylene blue concentration, zinc acetate to PVP ratio) on the efficiency of the photocatalytic process and kinetic model were evaluated. The results showed that the best pollutant removal efficiency (91.7%) was obtained using the ratio of zinc acetate and polyvinylpyrrolidone equal to 33.67 in 60 minutes of irradiation time. This result shows that the lower ratio of zinc acetate to polyvinylpyrrolidone indicates higher dye removal.
Original Research Paper
Exploration
Rashed Pourmirzaee; Hadi Jamshid Moghaddam
Abstract
In recent years, hyperspectral data have been widely used in earth sciences because these data provide accurate spectral information of the earth's surface. This research aims to apply match filtering (MF) on Hyperion hyperspectral imagery for mapping alteration mineral in the Astarghan area, NW Iran. ...
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In recent years, hyperspectral data have been widely used in earth sciences because these data provide accurate spectral information of the earth's surface. This research aims to apply match filtering (MF) on Hyperion hyperspectral imagery for mapping alteration mineral in the Astarghan area, NW Iran. Astarghan is located in the northwest of Iran where deposits of low-sulfide gold-bearing ore rocks occur as veins and stockworks. Therefore, at first, the Astarghan Hyperion scene was topographically and atmospherically corrected. Then, the data quality was surveyed to recognize bad bands and improve the accuracy of the subsequent processing steps. In MF analysis, it is a challenge to separate MF abundance images to target and background pixels. Therefore, to cope with this challenge, a moving threshold technique is proposed. The results indicated three indicative minerals including kaolinite, opal and jarosite. Then, the results were statistically verified by virtual verification and geological data. The verification was performed virtually using United States Geological Survey (USGS) spectral library data, which showed an agreement of 78.06%. Moreover, a comparison of the MF analysis results showed a good agreement with field investigations and overlaying with a detailed geological map of the study area. Finally, in this study the X-ray diffraction (XRD) of three indicative mineral samples was used to check the efficiency of the applied method.
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
Mohammad Rezaei; Seyed Zanyar Seyed Mousavi; Kamran Esmaeili
Abstract
This study introduces a novel approach, known as Hybrid Probabilistic Slope Stability Analysis (HPSSA), tailored for Mine 4 of the Gol-E-Gohar iron complex in Iran. The mine walls are first divided into 8 separate structural zones, including A-A' to H-H' sections for slope stability analysis. Then, sufficient ...
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This study introduces a novel approach, known as Hybrid Probabilistic Slope Stability Analysis (HPSSA), tailored for Mine 4 of the Gol-E-Gohar iron complex in Iran. The mine walls are first divided into 8 separate structural zones, including A-A' to H-H' sections for slope stability analysis. Then, sufficient core specimens are prepared from 22 drilled boreholes and the required parameters for slope design, including cohesion (c), friction angle (φ), and unit weight (γ), are measured. Finally, the HPSSA approach is performed through the combination of Monte Carlo simulation (MCS), Mohr-Coulomb criterion and Bishop's technique. According to the HPSSA results, the normal distribution function is achieved as the best curve fit for c, φ and γ parameters. Also, the obtained values of mean probabilistic safety factor (SF) for defined structural zones vary from 0.93 to 1.86, with the probability of failure (PF) of 0 to 75.6%. Moreover, SF values varied from 0.68 to 1.22 (mean value of 0.93) with a PF of 75% for the A-A' section and from 0.65 to 1.24 (mean value of 0.97) with a PF of 60% for the H-H' section. Hence, it is concluded that the A-A' section and mine’s north wall are more prone to instability with PF>60%. On the other hand, SF>1.2 and PF<5% for other mine walls (sections B-B'-G-G') prove that they are highly unlikely to be unstable. Displacement monitoring of the pit walls using installed prisms confirmed that average displacements in structural zones have a similar trend with SF values of the HPSSA. The results show a good agreement between the trend of probabilistic SFs and monitored slope displacements. Lastly, comparative analysis confirmed the validity of the suggested HPSSA approach with relatively higher accuracy than most previous slope stability analysis methods.
Original Research Paper
Rock Mechanics
Ajay Sharma; Neha Shrivastava
Abstract
The present study aims to assess the utility of construction and demolition (C&D) waste, specifically recycled concrete aggregates (RCA) and recycled brick aggregates (RBA), as fill materials in highway embankments. The assessment of slope stability is crucial in determining the suitability of any ...
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The present study aims to assess the utility of construction and demolition (C&D) waste, specifically recycled concrete aggregates (RCA) and recycled brick aggregates (RBA), as fill materials in highway embankments. The assessment of slope stability is crucial in determining the suitability of any material for embankment fill. GeoStudio software is employed in this study for slope stability assessment of 12 models with LS, RCA, RBA, and their blends as embankment fill materials. The embankment configuration is designed to represent a six-lane highway (carriageway width = 13 m, adhering to IRC: 36 standards), featuring varying slope elevations (3 m, 6 m, and 9 m) and diverse horizontal to vertical slope ratios (H:V = 2:1, 1:1, 1:2, and 1:3). The Morgenstern-Price method is employed to analyze slope stability and determine factor of safety (FOS) values. The study highlights the impact of slope heights, slope ratios, and fill materials (RCA, RBA, LS, and their blends) on FOS values in embankment models. Incorporating RCA or RBA in LS significantly boosts embankment FOS, exceeding stability expectations beyond 45˚ slope angles, potentially reducing costs and required area in construction projects. The incorporation of RCA/RBA into LS increases the FOS values to a range of 1.38 to 5.91, indicating very stable slopes for highway embankments. Based on the findings, replacing LS with RCA or RBA in embankment fill can enhance environmental sustainability and economic efficiency. However, these slope stability results apply specifically to C&D waste with similar composition, grain size, geotechnical properties, and embankment conditions.
Original Research Paper
Exploitation
Assefa Hailesilasie Wolearegay; Yowhas Birhanu Amare; Asmelash Abay Hagos; Kassa Amare Mesfin; Hagos Abraha; Bereket Gebresilassie; Yewuhalashet Fissha; nageswararao cheepurupalli
Abstract
The Dichinama area in northern Ethiopia is a potential source of dimension stone, but the quality of the marble has been a major challenge for mining operations. This research aims to evaluate the quality of dimension stone by conducting a comprehensive study involving geological mapping, geotechnical ...
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The Dichinama area in northern Ethiopia is a potential source of dimension stone, but the quality of the marble has been a major challenge for mining operations. This research aims to evaluate the quality of dimension stone by conducting a comprehensive study involving geological mapping, geotechnical testing, and geochemical analysis. The study collected nine rock samples from three active mining sites in the Dichinama area, analyzing properties such as density, water absorption, compressive strength, flexural strength, and abrasion resistance. Additionally, ten samples were collected for geochemical analysis, focusing on parameters like calcite, CaO values, LOI, SiO2 content, and other oxide concentrations. The geotechnical tests revealed that the properties of the marble in the Dichinama area were mainly calcite, with compressive strength values ranging from 29.6 to 74.5 MPa, flexural strength from 7 to 52.5 MPa, abrasion resistance from 8.3 to 17.2, density from 2257 to 2562 kg/m3, and water absorption from 0.12 to 0.93. However, most of these parameters fell below the minimum ASTM standards for marble dimension stone. The results suggest that these inferior characteristics negatively affect the recovery and quality of the dimension stone.
