V. Sarfarazi; A. Tabaroei
Abstract
In this work, the effect of rock bolt angle on the shear behavior of Rock Bridges is investigated using the particle flow code in two dimensions (PFC2D) for three different Rock Bridge lengths. Firstly, the calibration of PF2D is performed to reproduce the gypsum sample. Then the numerical models with ...
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In this work, the effect of rock bolt angle on the shear behavior of Rock Bridges is investigated using the particle flow code in two dimensions (PFC2D) for three different Rock Bridge lengths. Firstly, the calibration of PF2D is performed to reproduce the gypsum sample. Then the numerical models with the dimensions of 100 mm * 100 mm are prepared. The Rock Bridge is created in the middle of the model by removal of the narrow bands of discs from it. The uniaxial compressive strength of the Rock Bridge is 7.4 MPa. The Rock Bridge lengths are 30 mm, 50 mm, and 70 mm. The rock bolt is calibrated by a parallel bond. The tensile strength of the simulated rock bolt is 360 MPa.One rock bolt is implemented in the Rock Bridge. The rock bolt angles related to the horizontal axis are the changes from 0 to 75 degrees. Totally, 18 models are prepared. The shear test condition is added to the models. The normal stress is fixed at 2 MPa, and the shear load is added to the model till failure occurs. The results obtained show that in a fixed rock bolt angle, the tensile crack initiates from the joint tip and propagates parallel to the shear loading axis till coalescence to rock bolt. In a constant Rock Bridge length, the shear strength decreases with increase in the rock bolt angle. The highest shear strength occurs when the rock bolt angle is 0°.
Environment
Şener Ceryan; Pijush Samui; Osman Samed Özkan; Samet Berber; Şule Tüdeş; Hakan Elci; Nurcihan Ceryan
Abstract
Balikesir province Akcay district (Biga Peninsula, South Marmara Region, Turkey); the studied area is located on the southern branch of the North Anatolian Fault Zone, where some earthquake, 1867 Edremit (Mw =7.0), 1919 Ayvalik-Sarmisakli (Mw = 7.0), 1944 Edremit (Mw =6.4) and 1953 Yenice (Mw = 7.2) ...
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Balikesir province Akcay district (Biga Peninsula, South Marmara Region, Turkey); the studied area is located on the southern branch of the North Anatolian Fault Zone, where some earthquake, 1867 Edremit (Mw =7.0), 1919 Ayvalik-Sarmisakli (Mw = 7.0), 1944 Edremit (Mw =6.4) and 1953 Yenice (Mw = 7.2) earthquakes occurred in the historical and the instrumental period. In the said area, generally, the groundwater level is high and sandy soils are widespread. In this study, therefore topography, depth of groundwater table and soil characteristics of the said area were investigated in terms of susceptibility to liquefaction. In addition, the safety factor against liquefaction (FL) for the soil layers were determined by using simple procedure based on SPT-N values. Then the spatial distributions of the safety factor at 3 m, 6 m, 9 m, 12 m, 15 m and 18 m depths were obtained. Taking into considering FL values obtained, the liquefaction potential index and the liquefaction severity index of soil profile in the location of boring were calculated, then the spatial distributions of these index were obtained. According to the maps obtained, 5.8% of the studied area has low liquefaction potential, 10.7% medium liquefaction potential, 18.3% high liquefaction potential, and 53.8% very high liquefaction potential, and 22.7% of the study area has very low liquefaction severity, 17.1% low liquefaction severity, 47.7% moderate liquefaction severity, and 1.1% high liquefaction severity and 11.4% of the studied area has none-liquefiable soil.
Exploitation
Patrick Adeniyi Adesida; Sunday Adex Adaramola
Abstract
This study focuses on predicting the drillability of granitic rocks—precisely the wear rate of button bits, by integrating rock strength and mineralogical properties. The objective is to develop a predictive model for bit wear rate using a Rock Engineering System (RES) approach. Key rock parameters ...
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This study focuses on predicting the drillability of granitic rocks—precisely the wear rate of button bits, by integrating rock strength and mineralogical properties. The objective is to develop a predictive model for bit wear rate using a Rock Engineering System (RES) approach. Key rock parameters (uniaxial compressive strength, porosity, specific gravity, and the mineral content of quartz, plagioclase, hornblende, and biotite) were analysed via a RES interaction matrix to derive a new Drillability Index capturing their combined influence. This analysis revealed that UCS and porosity are the most influential factors in the system. The resulting RES-based model correlates strongly with observed bit wear rates, achieving a high coefficient of determination (R² ≈ 0.93) and low prediction errors (RMSE = 2.79, MAE = 2.14). The MAPE (= 38%) indicates a marked improvement in accuracy over traditional regression methods. Integrating mechanical and mineralogical factors is a novel approach to drillability prediction, providing a more comprehensive account of rock characteristics than conventional models. Validation results show that the RES-derived Drillability Index reliably predicts field performance, offering practical value for optimising drilling operations and guiding geomechanical analysis. Additionally, the study proposes a drillability classification scheme to further support the field application of the findings.
Environment
Anna Perevoshchikova; Larisa Rudakova; Natalia Mitrakova; Elizaveta Malyshkina; Nikita Kobelev
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.
Exploitation
Yasar Agan; Turker Hudaverdi
Abstract
The purpose of this research work is to predict blast induced ground vibration in surface mine by using classical and machine learning algorithms. For the purpose of minimizing blast-induced ground vibration to acceptable levels, the level of vibration must be predicted. Blast-induced ground vibration ...
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The purpose of this research work is to predict blast induced ground vibration in surface mine by using classical and machine learning algorithms. For the purpose of minimizing blast-induced ground vibration to acceptable levels, the level of vibration must be predicted. Blast-induced ground vibration is defined peak particle velocity (ppv) in the ground. All data used to estimation were obtained by observing real blasting operations. After the measuring of the peak particle velocity, models of the prediction were created using independent site parameters. Most of the data is used to train the model, while remaining part is used for testing. The models were created using independent blasting parameters proportionally. Thus, more parameters are included in the models without complicating the models. A thorough validation process was conducted utilizing a diverse set of nine error criteria. Artificial intelligence models have been found to outperform traditional methods in predicting ground vibration. The mean absolute error values were found to be 1.42, 1.54, and 1.78 for ANFIS, GPR, and SVM, respectively. A similar situation is observed for other error criteria as well. ANFIS appears to be the most effective model for predicting ground vibration.
Mineral Processing
Meysam Nikfarjam; Ardeshir Hezarkhani; Farhad Azizafshari; Hamidreza Golchin
Abstract
Geometallurgical modeling (GM) plays a crucial role in the mining industry, enabling a comprehensive understanding of the complex relationship between geological and metallurgical factors. This study focuses on evaluating metallurgical varibles at the Sungun Copper mine in Iran by measuring and predicting ...
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Geometallurgical modeling (GM) plays a crucial role in the mining industry, enabling a comprehensive understanding of the complex relationship between geological and metallurgical factors. This study focuses on evaluating metallurgical varibles at the Sungun Copper mine in Iran by measuring and predicting process properties, including semi-autogenous power index (SPI), recovery (Re), and concentration grade. To overcome the additivity limitations of geostatistical methods, we utilized machine learning algorithms for enhanced predictive modeling, aiming to improve decision-making and optimize mining operations in geometallurgy. The research incorporates crucial data inputs such as sample coordinates, grades, lithology, mineralization zones, and alteration to assess the accuracy and reliability of different machine learning regression methods. The Relative Standard Deviation (RSD) is highlighted as a significant metric for comparing the accuracy of predicted process properties. Evaluation metrics such as Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and coefficient of determination (R2) further confirm the superiority of specific modeling methods in certain scenarios. The K-Nearest Neighbors (KNN) method exhibits superior accuracy, lower error metrics (RMSE and MAE), and a higher R2 for modeling the SPI test. For modeling Cu grade in concentrate, Support Vector Regression (SVR) proves to be effective and reliable, outperforming the Multilayer Perceptron (MLP) method. Despite MLP's high R2, its higher RSD suggests increased uncertainty and variability in the predictions. Therefore, SVR is considered more suitable for modeling Cu grade in concentrate. Findings optimize operations at Sungun Copper mine, improving decision-making, efficiency, and profitability.
E. von Sperling; C.A.P. Grandchamp
Abstract
The paper presents the case study of the current formation of a Brazilian pit lake from an iron ore mining activity. The water used for the filling of the lake comes from rain, ground water and the complementary pumpage from a close river. At its final stage, which will be reached around year 2018, Lake ...
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The paper presents the case study of the current formation of a Brazilian pit lake from an iron ore mining activity. The water used for the filling of the lake comes from rain, ground water and the complementary pumpage from a close river. At its final stage, which will be reached around year 2018, Lake Aguas Claras will have a surface area of 0.67 km2 and the depth of 234 m, which will make it the deepest lake in the country. The filling of the lake began in the year 2001 and a monthly monitoring programme (physical, chemical and biological characteristics) is since then in course Theanalyses show that Lake Âguas Claras presents a very good water quality (well oxygenated, low values of colour and turbidity, limited degree of mineralization, pH slightly alkaline, low nutrient concentrations, excellent bacteriological conditions), together with a remarkable shift in the dominance of phytoplanktonic groups, indicating the high instability of lakes that are undergoing a process of formation. One relevant point in the management of this valuable water resource is to create adequate conditions for the protection of the aquatic environment. Considering the very probable maintenance of these favourable characteristics in future years, the possible uses of the lake will be directed to recreation (swimming, diving, sailing and fishing), amenity value and water supply.
J. Gholamnejad; A.R. Mojahedfar
Abstract
The determination of the Ultimate Pit Limit (UPL) is the first step in the open pit mine planning process. In this stage
that parts of the mineral deposit that are economic to mine are determined. There are several mathematical, heuristic
and meta-heuristic algorithms to determine UPL. The optimization ...
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The determination of the Ultimate Pit Limit (UPL) is the first step in the open pit mine planning process. In this stage
that parts of the mineral deposit that are economic to mine are determined. There are several mathematical, heuristic
and meta-heuristic algorithms to determine UPL. The optimization criterion in these algorithms is maximization of the
total profit whilst satisfying the operational requirement of safe wall slopes. In this paper the concept of largest pit with
non- negative value is suggested. A mathematical model based on integer programming is then developed to deal with
this objective. This model was applied on an iron ore deposit. Results showed that obtained pit with this objective is
larger than that of obtained by using net profit maximization and contains more ore, whilst the total net profit of
ultimate pit is not negative. This strategy can also increase the life of mine which is in accordance to the sustainable
development principals.
Z. Bahri; S.Z. Shafaei; M. Karamoozian
Abstract
Investigations were carried out on coal tailings by conventional cell and column flotation techniques. Tests were conducted to assess processing coal tailings of Alborz Markazi coal washing plant in Iran by column flotation. The effects of reagent type/dosage were investigated with conventional flotation ...
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Investigations were carried out on coal tailings by conventional cell and column flotation techniques. Tests were conducted to assess processing coal tailings of Alborz Markazi coal washing plant in Iran by column flotation. The effects of reagent type/dosage were investigated with conventional flotation and their results were used in the performance of column flotation. Also the effects of the air rate, the feeding rate, the wash water rate, the frother concentration, the collector dosage were evaluated with column flotation. These coal tailings have an average of 56% ash. This paper used factorial design to optimize grade and recovery of coal tailings. The column flotation results indicated concentrate produced under optimum conditions, kerosene, 2909 g/t; superficial air velocity, 0.96 cm/s; feeding rate, 3.6 lit/min; superficial wash water velocity, 0.98 lit/min; frother dosage, 350 g/t having an ash content of 12.11% and a combustible recovery of 28.51% was obtained.
Exploration
Joshua Chisambi; Leornard Kalindekafe; Kettie Magwaza; Ruth Mumba; Martin Kameza
Abstract
The Nathenje region in central Malawi hosts significant gold mineralization within high-grade metamorphic rocks of the Mozambique Belt, yet remains underexplored despite extensive artisanal mining activity. The structural controls on primary bedrock gold mineralization within these high-grade metamorphic ...
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The Nathenje region in central Malawi hosts significant gold mineralization within high-grade metamorphic rocks of the Mozambique Belt, yet remains underexplored despite extensive artisanal mining activity. The structural controls on primary bedrock gold mineralization within these high-grade metamorphic rocks remain poorly understood, limiting systematic exploration and resource development. We conducted integrated field mapping, structural analysis, petrographic examination, and geochemical sampling to characterize gold mineralization controls in the Nathenje prospect, central Malawi. Detailed structural measurements combined with stereographic analysis reveal three deformation phases, with gold mineralization predominantly associated with D₂ transpressional structures. Fire assay results demonstrate significant gold concentrations (0.15–5.0 g/t Au) in arsenopyrite-bearing quartz veins, with the highest grades systematically occurring at structural complexity zones. Petrographic analysis reveals native gold particles (5–50 μm) intimately associated with arsenopyrite along grain boundaries and within microfractures, indicating coupled precipitation processes. Critically, we identify a hierarchical structural control system operating from regional NE-SW trending shear zones to microscale sulphide boundaries, with fold hinges, dilutional jogs, and amphibolite-gneiss contacts yielding consistently higher gold grades (>3 g/t Au) than other structural settings. Our results establish the first comprehensive structural model for gold mineralization in central Malawi's metamorphic terrain and provide specific targeting criteria applicable to similar high-grade metamorphic environments throughout the East African Orogen.
Ali Asghar khodaiari; A Jafarnejad
Abstract
Maximizing economic earnings is the most common goal in cut-off grade optimization of open-pit mining operations. When this is the case, the price of the product has a critical effect on optimum value of cut-off grade. This paper investigates the relationship between optimum cut-off grade and price to ...
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Maximizing economic earnings is the most common goal in cut-off grade optimization of open-pit mining operations. When this is the case, the price of the product has a critical effect on optimum value of cut-off grade. This paper investigates the relationship between optimum cut-off grade and price to maximize total cash flow and net percent value (NPV) of operation. In order to visualize this relationship, two hypothetical mines were employed. To determine the optimum value of cut-off grade in different cases, two nonlinear programming models were formulated, and then, all models were solved using Solver in Excel. The results show that the optimum cut-off grade would always be a descending function of price when we intend to maximize total cash flow. On the other hand, this function may be descending or ascending when we intend to maximize NPV. This result also reveals that both maximum cash flow and maximum NPV always increase and decrease, respectively when the price of product increases or decreases.
S. Mohammadi; M. Ataei; R. Khalokakaei; E. Pourzamani
Abstract
Optimization of the exploitation operation is one of the most important issues facing the mining engineers. Since several technical and economic parameters depend on the cut-off grade, optimization of this parameter is of particular importance. The aim of this optimization is to maximize the net present ...
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Optimization of the exploitation operation is one of the most important issues facing the mining engineers. Since several technical and economic parameters depend on the cut-off grade, optimization of this parameter is of particular importance. The aim of this optimization is to maximize the net present value (NPV). Since the objective function of this problem is non-linear, three methods can be used to solve it: analytical, numerical, and meta-heuristic. In this study, the Golden Section Search (GSS) method and the Imperialist Competitive Algorithm (ICA) are used to optimize the cut-off grade in mine No. 1 of the Golgohar iron mine. Then the results obtained are compared. Consecuently, the optimum cut-off grades using both methods are calculated between 40.5% to 47.5%. The NPVs obtained using the GSS method and ICA were 18487 and 18142 billion Rials, respectively. Thus the value for GSS was higher. The annual number of iterations in the GSS method was equal to 18, and that for ICA was less than 18. Also computing and programming the process of golden section search method were easier than those for ICA. Therefore, the GSS method studied in this work is of a higher priority.
A. Zarean; R. Poormirzaee
Abstract
Shear-wave velocity ( ) is an important parameter used for site characterization in geotechnical engineering. However, dispersion curve inversion is challenging for most inversion methods due to its high non-linearity and mix-determined trait. In order to overcome these problems, in this study, a joint ...
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Shear-wave velocity ( ) is an important parameter used for site characterization in geotechnical engineering. However, dispersion curve inversion is challenging for most inversion methods due to its high non-linearity and mix-determined trait. In order to overcome these problems, in this study, a joint inversion strategy is proposed based on the particle swarm optimization (PSO) algorithm. The seismic data considered for designing the objects are the Rayleigh wave dispersion curve and seismic refraction travel time. For joint inversion, the objective functions are combined into a single function. The proposed algorithm is tested on two synthetic datasets, and also on an experimental dataset. The synthetic models demonstrate that the joint inversion of Rayleigh wave and travel time return a more accurate estimation of VS in comparison with the single inversion Rayleigh wave dispersion curves. To prove the applicability of the proposed method, we apply it in a sample site in the city of Tabriz located in the NW of Iran. For a real dataset, we use refraction microtremor (ReMi) as a passive method for getting the Rayleigh wave dispersion curves. Using the PSO joint inversion, a three-layer subsurface model was delineated.The results obtained for the synthetic datasets and field dataset show that the proposed joint inversion method significantly reduces the uncertainties in the inverted models, and improves the revelation of boundaries.
H. R. Nejati; Seyed A. Moosavi
Abstract
Assessment of the correlation between rock brittleness and rock fracture toughness has been the subject of extensive research works in the recent years. Unfortunately, the brittleness measurement methods have not yet been standardized, and rock fracture toughness cannot be estimated satisfactorily by ...
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Assessment of the correlation between rock brittleness and rock fracture toughness has been the subject of extensive research works in the recent years. Unfortunately, the brittleness measurement methods have not yet been standardized, and rock fracture toughness cannot be estimated satisfactorily by the proposed indices. In the present study, statistical analyses are performed on some data collected from the literature to develop two equations for estimation of modes I and II fracture toughness. Then a probabilistic sensitivity analysis is performed to determine the impact of the input parameters on the output ones. Based on the results obtained for the probabilistic analysis, a new empirical brittleness index including tensile strength, uniaxial compressive strength, and elastic modulus is suggested for estimating modes I and II fracture toughness. The analyses results reveal that the proposed index is capable of estimating rock fracture toughness with more satisfactory correlation compared to the previous indices.
L. Akpan; A. Celestine Tse; F. dumbari Giadom; C. Iorfa Adamu
Abstract
In this study, the chemical composition of water and soils contiguous to two abandoned coal mines in southeastern Nigeria, was assessed to evaluate the impact of water flow from the mines ponds on the geoenvironment and potential for acid mine drainage (AMD). Parameters including the pH, anions and cations, ...
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In this study, the chemical composition of water and soils contiguous to two abandoned coal mines in southeastern Nigeria, was assessed to evaluate the impact of water flow from the mines ponds on the geoenvironment and potential for acid mine drainage (AMD). Parameters including the pH, anions and cations, and the heavy metals were measured. These were used to evaluate contamination/pollution using hybrid factors including Pollution Load Index, factors, enrichment factors, pollution load index and index of geoaccumulation. The pH range of 3.4 to 5.9 classified the water as weakly to strongly acidic, typical of AMD. The SO42– ion, which indicates pollution by mine waters, showed moderate to high concentrations. Iron, zinc lead and copper were the most abundant heavy metals. Pollution Load Index values were greater than unity which show progressive deterioration in water and sediment quality. The Enrichment Factor values of up to 1 indicated enrichment through lithogenic and anthropogenic sources. The mine dumps serve as pools that can release toxic heavy metals into the water bodies by various processes of remobilization. Based on the lithology, mineralogy, chemical concentrations and environmental factors, the study has shown that there exists a potential for the generation of AMD. The heavy metals enriched mine flow, especially iron, empty into the nearby water bodies which serve as sources of municipal water supply. Consumption of untreated water over a prolonged period from these water sources may be detrimental to health. Remedial measure and continuous monitoring are recommended for good environmental stewardship.
Rock Mechanics
S. Moshrefi; K. Shahriar; A. Ramezanzadeh; K. Goshtasbi
Abstract
A rock failure criterion is very important for prediction of the ultimate strength in rock mechanics and geotechnics; it is determined for rock mechanics studies in mining, civil, and oil wellborn drilling operations. Also shales are among the most difficult to treat formations. Therefore, in this research ...
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A rock failure criterion is very important for prediction of the ultimate strength in rock mechanics and geotechnics; it is determined for rock mechanics studies in mining, civil, and oil wellborn drilling operations. Also shales are among the most difficult to treat formations. Therefore, in this research work, using the artificial neural network (ANN), a model was built to predict the ultimate strength of shale, and comparison was made with support vector machine (SVM), multiple linear regression models, and the widely used conventional polyaxial failure criteria in the stability analysis of rock structures, Drucker-Prager, and Mogi-Coulomb. For building the model, the corresponding results of triaxial and polyaxial tests have been performed on shales by various researchers. They were collected from reliable published articles. The results obtained showed that a feed forward back propagation multi-layer perceptron (MLP) was used and trained using the Levenberg–Marquardt algorithm, and the 2-4-1 architecture with root-mean-square-error (RMSE) of 24.41 exhibits a better performance in predicting the ultimate strength of shale in comparison with the investigated models. Also for further validation, triaxial tests were performed on the deep shale specimens. They were prepared from the Ramshire oilfield in SW Iran. The results obtained were compared with ANN, SVM, multiple linear regression models, and the conventional failure criterion prediction. They showed that the ANN model predicted ultimate strength with a minimum error and RMSE being equal to 43.81. Then the model was used for prediction of the threshold broken pressure shale layer in the Gachsaran oilfield in Iran. For this, a vertical and horizontal stress was calculated based on a depth of shale layer. The threshold broken pressure was calculated for the beginning and ending of a shale layer to be 154.21 and 167.98 Mpa, respectively.
Rock Mechanics
Seyed S. Mousavi; M. Nikkhah; Sh. Zare
Abstract
In this work, we tried to automatically optimize the cost of the concrete segmental lining used as a support system in the case study of Mashhad Urban Railway Line 2 located in NE Iran. Two meta-heuristic optimization methods including particle swarm optimization (PSO) and imperialist competitive algorithm ...
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In this work, we tried to automatically optimize the cost of the concrete segmental lining used as a support system in the case study of Mashhad Urban Railway Line 2 located in NE Iran. Two meta-heuristic optimization methods including particle swarm optimization (PSO) and imperialist competitive algorithm (ICA) were presented. The penalty function was used for unfeasible solutions, and the segmental lining structure was defined by nine design variables: the geometrical parameters of the lining cross-section, the reinforced feature parameters, and the dowel feature parameters used among the joints to connect the segment pieces. Furthermore, the design constrains were implemented in accordance with the American Concrete Institute code (ACI318M-08) and guidelines of lining design proposed by the International Tunnel Association (ITA). The objective function consisted of the total cost of structure preparation and implementation. Consequently, the optimum design of the system was analyzed using the PSO and ICA algorithms. The results obtained showed that the objective function of the support system by the PSO and ICA algorithms reduced 12.6% and 14% per meter, respectively.
Sonu Singh; Vijay Shankar; Joseph Tripura
Abstract
With an emphasis on establishing a connection between electrical and sub-surface hydro-geophysical features of soils, a critical evaluation of electrical resistivity technique applications is conducted in the current work. In order to identify diverse subsurface soil characteristics at different stratifications, ...
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With an emphasis on establishing a connection between electrical and sub-surface hydro-geophysical features of soils, a critical evaluation of electrical resistivity technique applications is conducted in the current work. In order to identify diverse subsurface soil characteristics at different stratifications, the electrical resistivity approach is a widely utilized geophysical method that is extensively adopted in various Earth landforms. The assessment of sub-surface hydro-geophysical features of soils, on the other hand, offers information on the hydrogeological and geological properties including the classification of aquifer types, groundwater pollution, and seismic data. The vast majority of the information compiled in this work may help the researchers better understand some basic fundamental issues relating the hydrogeology.
M. Alipour Shahsavari; P. Afzal; A. Hekmatnejad
Abstract
The Urumieh-Dokhtar Magmatic Arc (UDMA) is recognized as an important porphyry, disseminated, vein-type and polymetallic mineralization arc. The aim of this study is to identify and subsequently determine geochemical anomalies for exploration of Pb, Zn and Cu mineralization in Mial district situated ...
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The Urumieh-Dokhtar Magmatic Arc (UDMA) is recognized as an important porphyry, disseminated, vein-type and polymetallic mineralization arc. The aim of this study is to identify and subsequently determine geochemical anomalies for exploration of Pb, Zn and Cu mineralization in Mial district situated in UDMA. Factor analysis, Concentration-Number (C-N) fractal model and Local Linear Model Tree (LOLIMOT) algorithm used for this purpose. Factor analysis utilized in recognition of the correlation between elements and their classification. This classified data used for training the LOLIMOT algorithm based on relevant elements. The results of the LOLIMOT algorithm represent anomalies in areas with no lithogeochemical samples. Although, the C-N log-log plot for target elements were generated based on stream sediment and lithogeochemical samples which could be delineated mineral potential maps of the target elements. Results obtained by the LOLIMOT and fractal modeling show that the SW and the Eastern parts of the area are proper for further exploration of Cu, Pb, and Zn.
F. Doulati Ardejani; S. Maghsoudy; M. Shahhosseini; B. Jodeiri Shokri; Sh. Doulati Ardejani; F. Shafaei; F. Amirkhani Shiraz; A. Rajaee
Abstract
Considering that mining has many environmental impacts from the exploration phase to production and finally closure, it is necessary to plan the activities so that the concept of green mining is realized in its true meaning. This means that mining is carried out in order to obtain the minerals that are ...
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Considering that mining has many environmental impacts from the exploration phase to production and finally closure, it is necessary to plan the activities so that the concept of green mining is realized in its true meaning. This means that mining is carried out in order to obtain the minerals that are used in various industries; however, by taking appropriate measures, the impacts of mining on the environment are reduced to a minimum level. Since there is little information about the environmental, ecological, hydrological, and hydrogeological status in most mining areas, a comprehensive study of the area's water, soil, plants, and animal species should be conducted. The existence of permanent and seasonal rivers in the vicinity of some mines, in some cases being located in protected areas of the Iranian Department of Environment, and the presence of vegetation near some mines are among the matters that cause many environmental challenges in the mining areas. For this purpose, a series of comprehensive studies are critical in the pre-mining, during mining, and closure phases of the mine life. In addition, detailed studies should be done on factories such as smelters located in the mining areas. Life cycle assessment (LCA) is widely used in order to determine the environmental status of these factories. Furthermore, the issue of process water and water recycling, as well as waste management, should be considered. Nowadays, the environmental monitoring technology is one of the widely used tools in many mines in the world. Moreover, these mining companies' green space management system should be given special attention according to the obligatory standards of the Iranian Department of Environment. In this paper, a conceptual framework for the green mining method will be introduced for the coal mines to consider the economic and social aspects, and we pay a special attention to the health, safety, and environmental requirements.
Exploitation
Marco Antonio Cotrina-Teatino; Jairo Jhonatan Marquina-Araujo; Solio Marino Arango-Retamozo; Luis Alex Rios-LLaure; Jose Nestor Mamani-Quispe; Salomon Ortiz-Quintanilla
Abstract
This work aimed to optimize fuel consumption and CO2 emissions in mining haul trucks through a sustainability focused machine learning approach in a gold mine in La Libertad, Peru. The methodology comprised three stages. First, operational data from 26 m3 haul trucks (10,103 records over 12 months) were ...
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This work aimed to optimize fuel consumption and CO2 emissions in mining haul trucks through a sustainability focused machine learning approach in a gold mine in La Libertad, Peru. The methodology comprised three stages. First, operational data from 26 m3 haul trucks (10,103 records over 12 months) were normalized using Z-score scaling. Second, a Ridge regression model was trained to predict fuel consumption based on variables such as truck utilization, trips, road gradient, material type, haul distance, and operating hours. Finally, three operational strategies were simulated: Controlled Reduction (CRS), Balanced Efficiency (BES), and Maximum Utilization (MUS), to evaluate environmental, economic, and social impacts. The results indicated that the Ridge model achieved strong predictive performance in estimating fuel consumption (R2 = 0.83; MSE = 38.16). According to the simulated scenarios, environmentally, CRS reduced fuel consumption by 30% and CO2 emissions by 1,481.3 tons; BES achieved 7.99% savings and 394.9 tons less CO2. Economically, CRS saved USD 664,924.6 in fuel costs and BES USD 177,276.3. Socially, the carbon cost decreased by USD 11,406.1 (CRS) and USD 3,041.0 (BES). MUS increased emissions by 864.3 tons and fuel costs by USD 387,966.4. This research proposes a novel integration of machine learning and sustainability analysis applied to haul trucks in open-pit mining material transport. It also offers a replicable, data-driven framework for mining companies to reduce emissions, optimize costs, and align their operations with sustainability goals.
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.
Mine Economic and Management
Aditi Nag; Smriti Mishra
Abstract
Integrating Artificial Intelligence (AI) into heritage tourism has opened new avenues for transforming visitors’ engagement with historical sites. This research paper delves into a novel paradigm, focusing on AI integration in inter- and intra-regional mining heritage site planning and design. ...
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Integrating Artificial Intelligence (AI) into heritage tourism has opened new avenues for transforming visitors’ engagement with historical sites. This research paper delves into a novel paradigm, focusing on AI integration in inter- and intra-regional mining heritage site planning and design. Recognizing this context's unique challenges and opportunities, the study aims to uncover critical ideas and theories on how AI enhances visitor experience, promotes cultural preservation, sustainability, and stakeholder collaboration. Acknowledging the distinctive challenges and opportunities presented by inter- and intra-regional mining heritage contexts, this research work underscores the critical importance of striking a harmonious equilibrium between technological advancements and preserving historical and cultural legacies. Drawing from a cross-disciplinary approach, the study examines the profound implications of integrating AI into mining heritage sites' planning and design strategies. The study reviews 199 articles on AI-driven planning and design benefits, examining potential advantages. Ethical considerations, algorithmic biases, and the role of interdisciplinary research are also explored. The study highlights the intricate interplay between AI-enhanced engagement, responsible tourism practices, and the meaningful representation of local cultures. By shedding light on this uncharted territory, the research contributes to developing informed strategies that harness AI's potential to shape inter- and intra-regional mining heritage site planning and design, fostering responsible and impactful tourism experiences. By delving into this paradigm, it hopes to arm the researchers, policy-makers, practitioners, and other stakeholders with information and understanding that will help them forge a progressive and morally upright future, in which technology co-exists peacefully with practices for cultural preservation and sustainable tourism.
M Ebadi; Saeed Karimi Nasab; H Jalalifar
Abstract
rnDetermination of rock mass deformation modulus is very important in different projects, especially in civil and mining engineering works. In-situ measurements such as dilatometer, plate load and flat jack methods may be applied to determine the deformation modulus. However, these methods are very expensive ...
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rnDetermination of rock mass deformation modulus is very important in different projects, especially in civil and mining engineering works. In-situ measurements such as dilatometer, plate load and flat jack methods may be applied to determine the deformation modulus. However, these methods are very expensive and time- consuming. Analytical methods are very useful approaches which can also be used to estimate rock mass deformation modulus. Using these methods, the parameters influencing the rock mass modulus can also be evaluated. Analytical methods are based on the resultant displacement of rock mass and joints which are finally used to predict the rock modulus. It should be mentioned that none of the available analytical models could present a model to consider the effect of lateral stresses on rock mass modulus calculations. Therefore, this paper tries to investigate the effect of intermediate principal stress (σ2) and minimum principal stress (σ3) on the deformation modulus of jointed rock mass.rn
H. Khoshdast; M. Mahmoodabadi
Abstract
A new method is developed for a fast identification of the stability situation of industrial processes. The proposed method includes two factor ratios of the control constants for the upper and lower control limits to process these constants. An indication ratio is then defined as the ratio of the maximum ...
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A new method is developed for a fast identification of the stability situation of industrial processes. The proposed method includes two factor ratios of the control constants for the upper and lower control limits to process these constants. An indication ratio is then defined as the ratio of the maximum data range value to the difference between the maximum and average values for individual data points. It is shown that if the indication ratio comes into values between the corresponding control factor ratios, the process will be under control, and otherwise, if the indication ratio decreases to smaller than the lower control factor ratio or gets more than the upper control factor ratio, the process will be expected to be out-of-control. Validation of the method was successfully resulted using two series of quality control datasets obtained from Zarand Iron Ore Complex (Zarand, Iran) and Miduk Copper Complex (Shahr Babak, Iran). The results obtained show that the process responses predicted by the proposed method are in agreement with those indicated by the conventional chart-based method. The developed method eliminates the need for drawing the process control charts used to assess the process control level. The superiority of the proposed method over the chart-based method becomes apparent especially when a large number of control charts are necessary to be drawn and interpreted for engineering decision-making purposes.
