ebrahim elahi; Reza Kakaie; amir yusefi
Abstract
Ultimate limits of an open pit, which define its size and shape at the end of the mine’s life, is the pit with the highest profit value. A number of algorithms such as floating or moving cone method, floating cone method II and the corrected forms of this method, the Korobov algorithm and the corrected ...
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Ultimate limits of an open pit, which define its size and shape at the end of the mine’s life, is the pit with the highest profit value. A number of algorithms such as floating or moving cone method, floating cone method II and the corrected forms of this method, the Korobov algorithm and the corrected form of this method, dynamic programming and the Lerchs and Grossmann algorithm based on graph theory have been developed to find out the optimum final pit limits. Each of these methods has special advantages and disadvantages. Among these methods, the floating cone method is the simplest and fastest technique to determine optimum ultimate pit limits to which variable slope angle can be easily applied. In contrast, this method fails to find out optimum final pit limits for all the cases. Therefore, other techniques such as floating cone method II and the corrected forms of this method have been developed to overcome this shortcoming. Nevertheless, these methods are not always able to yield the true optimum pit. To overcome this problem, in this paper a new algorithm called floating cone method III has been introduced to determine optimum ultimate pit limits. The results show that this method is able to produce good outcome.
M. R. Tavakoli Mohammadi; Seyed M. J. Koleini; M. Abdollahy
Abstract
Efforts to increase the mass transfer coefficient, enhance the contact area, and decrease the power input of contractors have given risen to the development of the pre-dispersed solvent extraction (PDSE) contactor and the devise of the new dissolved nitrogen PDSE (DNPDSE) contactors. The studies conducted ...
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Efforts to increase the mass transfer coefficient, enhance the contact area, and decrease the power input of contractors have given risen to the development of the pre-dispersed solvent extraction (PDSE) contactor and the devise of the new dissolved nitrogen PDSE (DNPDSE) contactors. The studies conducted after the design of the new contactor to determine the working conditions for its suitable performance (2.5-3.5 bar pressure, 0.1 L/min sparger flow rate, and 1.5 L of the aqueous phase) showed that for all the evaluated conditions (i.e. the pressure, polyaphron type, and dilution percentage), the recovery in the DNPDSE contactor was higher than that in the PDSE one. In addition, pictures of the performance modes of the two contactor indicated the presence of the organic phase in the form of colloidal gas aphrons (CGAs) in the DNPDSE contactor and of polyaphron aggregations in the PDSE one. This is a good reason for the increased copper recovery in the DNPDSE contactor. The best recovery for the extraction process in the DNPDSE contactor was achieved using the anionic polyaphron of sodium dodecylbenzene sulphonate (NaDBS) with five-fold dilution at 3.5 bar.
H. Fattahi
Abstract
Slope stability analysis is an enduring research topic in the engineering and academic sectors. Accurate prediction of the factor of safety (FOS) of slopes, their stability, and their performance is not an easy task. In this work, the adaptive neuro-fuzzy inference system (ANFIS) was utilized to build ...
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Slope stability analysis is an enduring research topic in the engineering and academic sectors. Accurate prediction of the factor of safety (FOS) of slopes, their stability, and their performance is not an easy task. In this work, the adaptive neuro-fuzzy inference system (ANFIS) was utilized to build an estimation model for the prediction of FOS. Three ANFIS models were implemented including grid partitioning (GP), subtractive clustering method (SCM), and fuzzy c-means clustering method (FCM). Several important parameters such as cohesion coefficient, internal angle of friction, slope height, slope angle, and unit weight of slope material were utilized as the input parameters, while FOS was used as the output parameter. A comparison was made between these three models, and the results obtained showed the superiority of the ANFIS-SCM model. Also performance of the ANFIS-SCM model was compared with multiple linear regression (MLR). The results obtained demonstrated the effectiveness of the ANFIS-SCM model.
Exploitation
J. Gholamnejad; A. Azimi; M.R. Teymouri
Abstract
Stockpiling and blending play a major role in maintaining the quantity and quality of the raw materials fed into processing plants, especially the cement, iron ore and steel making, and coal-fired power generation industries that usually require a much uniformed feed. Due to the variable nature of such ...
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Stockpiling and blending play a major role in maintaining the quantity and quality of the raw materials fed into processing plants, especially the cement, iron ore and steel making, and coal-fired power generation industries that usually require a much uniformed feed. Due to the variable nature of such materials, they even come from the same source and the produced ores or concentrates are seldom homogeneous enough to be directly fed to the processing plant ore furnaces. Processing plants in iron ore mines need uniform feed properties in terms of each variable (in this work, iron phosphorous ratio and Fe content in magnetite phase) grade of ore, and therefore, homogenization of iron ore from different benches of an open pit or ore dumps has become an essential part of modern mine scheduling. When ore dumps are considered as an ore source, the final grade of the material leaving the dump to the blending bed cannot be easily determined. This difficulty contributes to mixing the materials of different grades in a dump. In this work, the ore dump elements were treated as normally distributed random variables. Then a stochastic programming model was formulated in an iron ore mine in order to determine the optimum amount of ore dispatched from different bench levels in open pit and also four ore dumps to a windrow-type blending bed in order to provide a mixed material of homogenous composition. The chance-constrained programming technique was used to obtain the equivalent deterministic non-linear programming problem of the primary model. The resulting non-linear model was then solved using LINGO. The results obtained showed a better feed grade for the processing plant with a higher probability of grade blending constraint satisfaction.
Exploitation
H. Nikoogoftar Safa; A. Hezarkhani
Abstract
In this paper, we aim to present a quantitative modeling for delineating the alteration zones and lithological units in the hypogene zone of Masjed-Daghi Cu-Au porphyry deposit (NW Iran) based on the drill core data. The main goal of this work is to apply Ordinary Kriging (OK) and concentration-volume ...
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In this paper, we aim to present a quantitative modeling for delineating the alteration zones and lithological units in the hypogene zone of Masjed-Daghi Cu-Au porphyry deposit (NW Iran) based on the drill core data. The main goal of this work is to apply Ordinary Kriging (OK) and concentration-volume (C-V) fractal model based on Cu grades in order to separate the different alteration zones and lithological units. Initially, anisotropy was investigated and modeled based on calculating the experimental semi-variograms of the Cu values, and the main variography directions were identified and evaluated. Then a block model of the Cu grades was generated using the kriging, and the estimation obtained for OK was applied to the C-V fractal model. The C–V log–log plot based on the estimation method represents the various alteration and lithological zones via threshold values. The comparison and interpretation of the alteration zones and lithological units based on the C–V fractal modeling proved that the method was acceptable and capable of correctly delineating the alteration and lithological units. Regarding the correlation derived from log ratio matrix (used to compare the geological model with the C-V fractal results), it was observed that Cu values less than 0.4% were obtained for OK overlapped voxels with the phyllic alteration zone by an overall accuracy (OA) of 0.737. The spatial correlation between the potassic alteration zones resulting from a 3D geological modeling and the high concentration zones in the C-V fractal model based on OK indicated that the alteration zone contained Cu values greater than 0.4% with OA of 0.791. Also using this method, trustworthy results were obtained for the rock units.
F. Khorram; O. Asghari; H. Memarian; A. Hoseein Morshedy; X. M. Emery
Abstract
The key input parameters for mine planning and all subsequent mining activities is based on the block models. The block size should take into account for the geological heterogeneity and the grade variability across the deposit. Providing grade models of smaller blocks is more complex and costly than ...
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The key input parameters for mine planning and all subsequent mining activities is based on the block models. The block size should take into account for the geological heterogeneity and the grade variability across the deposit. Providing grade models of smaller blocks is more complex and costly than larger blocks, but larger sizes cannot represent areas with high spatial variability accurately. Hence, a unique block size is not an optimal solution for modeling a mine site. This paper presented a novel algorithm to create an adaptive block model with locally varying block sizes aiming to control dilution and ore loss in Sungun porphyry copper deposit of Iran with a complex geometry characterized by multiple dikes. Three grade block models with different block sizes and simulated by direct block simulation are the inputs of algorithm. The output is a merged block model, assigning the smaller blocks to the complex zones, such as ore-waste boundaries, and larger blocks to the continuous and homogeneous zones of the ore body. The presented algorithm is capable to provide an accurate spatial distribution model with a fewer number of blocks in comparison to the traditional block modeling concepts.
M. Sakizadeh; M. T. Sattari; H. Ghorbani
Abstract
The soil samples were collected from 170 sampling stations in an arid area in Shahrood and Damghan, characterized by prevalence of mining activity. The levels of Co, Pb, Ni, Cs, Cu, Mn, Sr, V, Zn, Cr, and Tl were recorded in each sampling location. A new method known as min/max autocorrelation factor ...
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The soil samples were collected from 170 sampling stations in an arid area in Shahrood and Damghan, characterized by prevalence of mining activity. The levels of Co, Pb, Ni, Cs, Cu, Mn, Sr, V, Zn, Cr, and Tl were recorded in each sampling location. A new method known as min/max autocorrelation factor (MAF) was applied for the first time in the environmental research works to de-correlate these elements before their geo-statistical simulation. The high cross-correlation among some elements, while poor spatial correlation among the others, could have made spectral decomposition of MAFs unstable, resulting in some negative eigenvalues, so it was decided to reduce the dimensionality of the original variables by Principal Component Analysis (PCA). The resultant 6 heavy metals (Cr, Mn, Cu, V, Ni, and Co) were converted to their respective MAFs followed by their geo-statistical simulation using Sequential Gaussian Simulation (SGS) independently. Examination of the cross-variograms of MAFs indicated that the resultant factors had been rigorously de-correlated, especially at zero lag and around ∆ lag distance. Several validation checks including reproduction of variograms in data and normal score space, close matching between distribution of MAFs versus simulated realizations, and reproduction of descriptive statistics and data histograms all confirmed that the data values had been honored by this applied method. The results obtained indicated that this method could reproduce the data values as well as the spatial continuity of heavy metals (e.g. semi-variograms) successfully. In addition, this technique is simpler and more computationally efficient than its equivalent sequential Gaussian co-simulation as fitting a linear model of co-regionalization (LMC) is not required in the data-driven MAF method.
Mineral Processing
S. Mohammadi; B. Rezai; A. A. Abdolahzadeh
Abstract
Geometallurgy tries to predict the instability the behavior of ores caused by variability in the geological settings, and to optimize the mineral value chain. Understanding the ore variability and subsequently the process response are considered to be the most important functions of an accurate geometallurgical ...
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Geometallurgy tries to predict the instability the behavior of ores caused by variability in the geological settings, and to optimize the mineral value chain. Understanding the ore variability and subsequently the process response are considered to be the most important functions of an accurate geometallurgical study. In this paper, the geometallurgical index is presented as a new tool to optimize the mining activities. Geometallurgical index is described as any geological feature that makes a footprint on the process performance of ores. In a comprehensive research work at the Sarcheshmeh porphyry copper mine, the geological features that affect the main process responses including the product grade and recovery and plant’s throughput are subjected to investigation. In the current report, the rock hardness variability in terms of semi-autogenous grinding power index (SPI) and its effects on the mill throughput and energy consumption are presented. Ninety samples are collected based on the geological features including lithology, hydrothermal alteration, and geological structures. The samples are mineralogically characterized using XRD, XRF, and electron and optical microscopy. The Starkey laboratory mill, commercialized by Minnovex, is used to perform the SPI comminution test. The SPI results show a wide range of hardness, varying from 12 to 473 minutes. The correlation between the SPI results and the geological features show that lithology is a key geological feature that defines the hardness variability. In addition, the hydrothermal alteration would be an effective parameter in the period that the plant is fed with a single lithology.
J. Shakeri; H. Amini Khoshalan; H. Dehghani; M. Bascompta; K. Onyelowe
Abstract
In this research work, a comprehensive study is conducted to predict flyrock as a typical and undesirable phenomenon occurring during the blasting operation in open-pit mining. Despite the availability of several empirical methods for predicting the flyrock distance, the complexity of flyrock analysis ...
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In this research work, a comprehensive study is conducted to predict flyrock as a typical and undesirable phenomenon occurring during the blasting operation in open-pit mining. Despite the availability of several empirical methods for predicting the flyrock distance, the complexity of flyrock analysis has resulted in the low performance of these models. Therefore, the statistical and robust artificial intelligence techniques are applied for flyrock prediction in the Sungun copper mine in Iran. For this purpose, the linear multivariate regression (LMR), imperialist competitive algorithm (ICA), adaptive neuro-fuzzy inference system (ANFIS), and artificial neural network (ANN) methods are applied to predict flyrock with effective parameters including the blasthole diameter, stemming, burden, powder factor, and maximum charge per delay. According to the attained results, the ANN model with the structure of 5-8-1, Levenberg-Marquardt as the learning algorithm, and log-sigmoid (logsig) as the transfer functions are selected as the optimal network with the RMSE and R2 values of 5.04 m and 95.6% to predict flyrock, respectively. Also it can be concluded that the ICA technique has a relatively high capability in predicting flyrock, with the LMR and ANFIS models placed in the next. Finally, the sensitivity analysis reveal that the powder factor and blasthole diameters have the most importance on the flyrock distance in the present work.
Ankit Kumar; Ravi Kumar Sharma
Abstract
Granular pile anchor is a new technique that is commonly used to improve the pull-out resistance of expansive soil like soft clay, loose sand, and black cotton soil. Using the Abaqus software, this work presents a numerical investigation to estimate the pull-out capacity of granular pile anchor ...
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Granular pile anchor is a new technique that is commonly used to improve the pull-out resistance of expansive soil like soft clay, loose sand, and black cotton soil. Using the Abaqus software, this work presents a numerical investigation to estimate the pull-out capacity of granular pile anchor in soft clay. By applying a specified displacement of 10% of D (pile diameter) on the granular pile anchor, the effects of length, diameter, angle of inclination (α), and number of GPA at varying spacing values on uplift capacity is examined. Additionally, L/D ratios of both individual and group piles are examined using various variables. The study uses expansive soil and GPA of unit weight 17 kN/m3 and 22 kN/m3, poisson’s ratio of 0.4 and 0.3, modulus of elasticity 4 MPa, and 11 MPa, respectively, for the estimation of uplift capacity. The cohesion value for the expansive clay is 25 kPa, and the angle of shearing resistance for GPA is 36˚. According to the numerical study, both for a single pile and for piles placed in a group, with increases in pile length and diameter, the granular pile anchor's pull-out capability improves. For a pile placed in group the value of the pull-out capacity shows optimum result when spacing (S) is 2.5D. Additionally, the uplift capacity of the granular pile anchor increases with an increase in angle inclination (α) from 0˚ to 10˚, and then decreases from 10˚ to 15˚. The efficiency of GPA is examined, which assists in the choice of the different granular pile anchor parameters.
Environment
Aditi Nag; Smriti Mishra
Abstract
This study examines the revitalization of mining ghost towns (MGTs) through heritage tourism, focusing on sustainability and heritage preservation. The study highlights the transformative potential of heritage tourism in revitalizing these towns, highlighting the economic resilience achieved through ...
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This study examines the revitalization of mining ghost towns (MGTs) through heritage tourism, focusing on sustainability and heritage preservation. The study highlights the transformative potential of heritage tourism in revitalizing these towns, highlighting the economic resilience achieved through diversified local economies and responsible tourism practices. Cultural preservation ensures the endurance of unique identities and cultural legacies, sparking community pride and cultural exchange. Sustainability measures extend beyond heritage preservation, promoting environmental stewardship and long-term ecological well-being. Community engagement, educational initiatives, and responsible tourism practices are crucial in sustaining the heritage of these towns. The implications extend beyond individual communities, offering a model for responsible and sustainable tourism practices with global relevance. The significance of revitalizing MGTs through heritage tourism lies in preserving history, empowering communities, and creating vibrant, sustainable destinations for generations.
Exploration
Mustafa Yasser Elgindy; Ahmed Zakaria Nooh; Ali Mostafa Wahba
Abstract
Kick monitoring, detection, and control are key elements to ensure safe drilling operations and avoid catastrophic blow-out incidents that can cause loss of life, equipment, and environmental damage. Conventional kick detection systems such as the pit volume totalizer and the flow in/out sensors identify ...
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Kick monitoring, detection, and control are key elements to ensure safe drilling operations and avoid catastrophic blow-out incidents that can cause loss of life, equipment, and environmental damage. Conventional kick detection systems such as the pit volume totalizer and the flow in/out sensors identify the kick after a large amount of influx has been recorded on the surface. So, we aim to recognize the kick before it enters the wellbore by detecting the abnormal formation pressure once the bit penetrates the rock. This paper proposes a new machine learning model as an alternative solution using field drilling parameters such as true vertical depth, porosity, bulk density, resistivity, rate of penetration, weight on bit, rotation per minute, torque, standpipe pressure, flow rate, flowline temperature, and gas level. The data-driven models were developed using three separate algorithms: K-Nearest Neighbor, Random Forest, and XG Boost. 6022 field data points were split for training, testing, and validation processes. On average, the model using the random forest algorithm showed the highest accuracy in forecasting the formation pressure, with root mean squared error values and coefficient of determination values of 12.868 and 0.9638, respectively. Streamlit Deployment tool was used to create a user interface program to facilitate the prediction process. The program was tested using 196 field data points and recorded a high accuracy of 95%.
Environment
Asep Nurohmat Majalis; Muhammad Razzaaq Al Giffari; R Arif Suryanegara; M Rifat Noor; Rachmat Ramadhan; Noviarso Wicaksono
Abstract
Due to its large nickel reserves, Indonesia has become one of the world's largest nickel mining sites and producers. Nickel is a mining commodity with high economic value. However, its mining activity can negatively impact the environment if not managed properly. Therefore, mitigation of the impact of ...
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Due to its large nickel reserves, Indonesia has become one of the world's largest nickel mining sites and producers. Nickel is a mining commodity with high economic value. However, its mining activity can negatively impact the environment if not managed properly. Therefore, mitigation of the impact of nickel mining is necessary. This research has conducted erosion and infiltration tests at various locations in pre-nickel mining zones to mitigate the environmental impact of nickel mining activity. Erosion tests were performed using a rainfall simulator with five nozzles on a 12.5 m² demo plot. Infiltration tests were conducted using a double-ring infiltrometer. The result shows that surface runoff coefficients for disposal, limonite, saprolite, and quarry zones were higher than those for vegetated zones such as grassland, pepper plantation, and forest. The saprolite zone released the highest sediment load, i.e., 484.3 kg ha-1 hour-1, followed by the limonite and the pepper plantation zone, with 243.6 kg ha-1 hour-1 and 185 kg ha-1 hour-1. The highest Cr(VI) concentration, 0.7 mg L-1, was released from the disposal zone, followed by the saprolite, limonite, and pepper plantation zones, with concentrations of 0.56, 0.06, and 0.06 mg L-1, respectively. The infiltration equation obtained from each zone shows that revegetation can significantly reduce runoff. Therefore, revegetation should be prioritized in addition to end-of-pipe treatment to mitigate the impact of nickel mining activities.
A. Salimi; M. Ziaii; A. Amiri; M. Hosseinjani Zadeh
Abstract
Remote sensing image analysis can be carried out at the per-pixel (hard) and sub-pixel (soft) scales. The former refers to the purity of image pixels, while the latter refers to the mixed spectra resulting from all objects composing of the image pixels. The spectral unmixing methods have been developed ...
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Remote sensing image analysis can be carried out at the per-pixel (hard) and sub-pixel (soft) scales. The former refers to the purity of image pixels, while the latter refers to the mixed spectra resulting from all objects composing of the image pixels. The spectral unmixing methods have been developed to decompose mixed spectra. Data-driven unmixing algorithms utilize the reference data called training samples and end-members. The performance of algorithms using training samples can be negatively affected by the curse of dimensionality. This problem is usually observed in the hyperspectral image classification, especially when a low number of training samples, compared to the large number of spectral bands of hyperspectral data, are available. An unmixing method that is not highly impressed by the curse of dimensionality is a promising option. Among all the methods used, Support Vector Machine (SVM) is a more robust algorithm used to overcome this problem. In this work, our aim is to evaluate the capability of a regression mode of SVM, namely Support Vector Regression (SVR), for the sub-pixel classification of alteration zones. As a case study, the Hyperion data for the Sarcheshmeh, Darrehzar, and Sereidun districts is used. The main classification steps rely on 20 field samples taken from the Darrehzar area divided into 12 and 8 samples for training and validation, respectively. The accuracy of the sub-pixel maps obtained demonstrate that SVR can be successfully applied in the curse of dimensional conditions, where the size of the training samples (12) is very low compared to the number of spectral bands (165).
B. A. Mert
Abstract
This paper presents the procedures used for determining and defining the tonnage and grade of the coalfields of Kangal basin from the developed GIS-aided block model. In this work, firstly, all the lithological logs of drill holes and chemical analysis data of core in the basin were analyzed with the ...
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This paper presents the procedures used for determining and defining the tonnage and grade of the coalfields of Kangal basin from the developed GIS-aided block model. In this work, firstly, all the lithological logs of drill holes and chemical analysis data of core in the basin were analyzed with the help of geostatistics, and then the digital raster maps of each one of the attributes such as the thickness, calorific value (LCV), ash content (AC%), moisture content (MC%), and surface maps of lignite seams were mapped in GIS environment. In the second stage, quantities of the overburden and resources with different categories were calculated on the basis of field-based quality and volume queries with the help of the digital maps on GIS platform. As a result, it was estimated that the Kalburçayırı field had a tonnage of 116 Mt of lignite with an LCV of 1308 kcal/kg, the Hamal field had a tonnage of 30 Mt of lignite with an LCV of 987 kcal/kg, and the Etyemez field had a tonnage of 48 Mt of lignite with an LCV of 1282 kcal/kg. Also it was estimated that almost 24,278,151 tons of lignite in the Hamal and Etyemez fields had a quality of less than 950 kcal/kg that could be directly fired without the blending process in the power plant. As a consequence, the Hamal and Etyemez fields should go into production as soon as possible and be fired in the power plant after being mixed with the lignite in the Kalburcayırı field so that they can be redounded to economy.
M. R. Azad; A. Kamkar Rouhani; B. Tokhmechi; M. Arashi
Abstract
Upscaling based on the bandwidth of the kernel function is a flexible approach to upscale the data because the cells will be coarse-based on variability. The intensity of the coarsening of cells in this method can be controlled with bandwidth. In a smooth variability region, a large number of cells will ...
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Upscaling based on the bandwidth of the kernel function is a flexible approach to upscale the data because the cells will be coarse-based on variability. The intensity of the coarsening of cells in this method can be controlled with bandwidth. In a smooth variability region, a large number of cells will be merged, and vice versa, they will remain fine with severe variability. Bandwidth variation can be effective in upscaling results. Therefore, determining the optimal bandwidth in this method is essential. For each bandwidth, the upscaled model has a number of upscaled blocks and an upscaling error. Obviously, higher thresholds or bandwidths cause a lower number of upscaled blocks and a higher sum of squares error (SSE). On the other hand, using the smallest bandwidth, the upscaled model will remain in a fine scale, and there will be practically no upscaling. In this work, different approaches are used to determine the optimal bandwidth or threshold for upscaling. Investigation of SSE changes, the intersection of two charts, namely SSE and the number of upscaled block charts, and the changes of SSE values versus bandwidths, are among these approaches. In this particular case, if the goal of upscaling is to minimize the upscaling error, the intersection method will obtain a better result. Conversely, if the purpose of upscaling is computational cost reduction, the SSE variation approach will be more appropriate for the threshold setting.
S. Kumar Jha; P. Warwade; S. Kumar Mahto
Abstract
This work illustrates the impact of excessive mining on the precipitation trends and ground water condition of the Ramgarh district over a period of 12 years (2007-2018). The Landsat 8 and Landsat TM- 5 data is processed under Arc-GIS in order to compare the LULC maps. Out of 7 classified classes, the ...
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This work illustrates the impact of excessive mining on the precipitation trends and ground water condition of the Ramgarh district over a period of 12 years (2007-2018). The Landsat 8 and Landsat TM- 5 data is processed under Arc-GIS in order to compare the LULC maps. Out of 7 classified classes, the Results obtained indicate the expansion of the mining area, barren land, settlement, and water body by 10.95%, 10.07%, 3.44%, and 0.43%, while a reduction in the forest, fallow, and crop land by 11.24%, 11.31%, and 2.34% respectively. The TRMM 3B43 data is used to trace out the annual precipitation values of 5 selected raster location points through Arc GIS. The annual precipitation under the mining regions (lower Mandu, Ramgarh, Bhurkunda) shows a decreasing trend. The Mann-Kendall test and Sen’s slope estimator method is used in order to evaluate the ground water pattern in the pre- and post-monsoonal conditions. The Mandu block, the densest mining region of the district with the positive Z values of 1.714 and 0.137 in the pre- and post- monsoon period shows a decrease in the ground water level at the rates of 0.103 m/year and 0.017 m/year, respectively. The continuous rise in the mining activities has created an alarming shift of weather pattern and deteriorated ground water table in Ramgarh.
Afrodita Zendelska; Adrijana Trajanova; Mirjana Golomeova; Blagoj Golomeov; Dejan Mirakovski; Nikolinka Doneva; Marija Hadzi-Nikolova
Abstract
The treatment of acid mine drainages is usually based on two basic technologies, active and passive treatment technologies. Whichever acid mine drainage (AMD) treatment method is employed, a neutralizing procedure that raises the water's pH over 7.0 using alkaline agents is required prior to discharge. ...
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The treatment of acid mine drainages is usually based on two basic technologies, active and passive treatment technologies. Whichever acid mine drainage (AMD) treatment method is employed, a neutralizing procedure that raises the water's pH over 7.0 using alkaline agents is required prior to discharge. A comparison of eight different agents (BaCO3, Na2CO3, NaOH, KOH, K2CO3, MgO, CaCO3, and Ba(OH)2) was performed in order to choose the most effective neutralizing agent for acid mine drainage treatment. The experiments were performed using a multi-component synthetic aqueous solution with an initial concentration of 10 mg/L of the Cu, Mn, Zn, Fe, and Pb ions and an initial pH value of 1.9. According to the research, the most effective neutralizing agent for the removal of heavy metals from a multi-component aqueous solution is MgO, while the least effective agent was Na2CO3. The obtained series of effective neutralizing agents for the removal of heavy metals from a multi-component aqueous solution are presented in the work. The effect of the studied concentration of neutralizing agents depends on the neutralizing agents and heavy metals that are used. The percentage of heavy metals removed from aqueous solutions increases along with rising pH values. The consumption of the neutralizing agent decreases as the concentration of the neutralizing agent is increased. In addition, the time taken to achieve pH depends on the agent concentration. In particular, as the concentration of the neutralizing agent increases, the time to reach the pH decreases.
Exploitation
F. Sotoudeh; M. Ataei; R. Kakaie; Y. Pourrahimian
Abstract
In mining projects, all uncertainties associated with a project must be considered to determine the feasibility study. Grade uncertainty is one of the major components of technical uncertainty that affects the variability of the project. Geostatistical simulation, as a reliable approach, is the most ...
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In mining projects, all uncertainties associated with a project must be considered to determine the feasibility study. Grade uncertainty is one of the major components of technical uncertainty that affects the variability of the project. Geostatistical simulation, as a reliable approach, is the most widely used method to quantify risk analysis to overcome the drawbacks of the estimation methods used for an entire ore body. In this work, all the algorithms developed by numerous researchers for optimization of the underground stope layout are reviewed. After that, a computer program called stope layout optimizer 3D is developed based on a previously proposed heuristic algorithm in order to incorporate the influence of grade variability in the final stope layout. Utilizing the sequential gaussian conditional simulation, 50 simulations and a kriging model are constructed for an underground copper vein deposit situated in the southwest of Iran, and the final stope layout is carried out separately. It can be observed that geostatistical simulation can effectively cope with the weakness of the kriging model. The final results obtained show that the frequency of economic value for all realizations varies between 6.7 M$ and 30.7 M$. This range of variation helps designers to make a better and lower risk decision under different conditions.
Avinash Chandan; Abhishek Sharma
Abstract
Due to disposal concerns, an enormous quantity of personal protective equipment (PPE) waste from the COVID-19 pandemic constituted a severe health and environmental risk. During the pandemic, the usage of protective suits increased dramatically raising concerns about how to dispose of them to safeguard ...
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Due to disposal concerns, an enormous quantity of personal protective equipment (PPE) waste from the COVID-19 pandemic constituted a severe health and environmental risk. During the pandemic, the usage of protective suits increased dramatically raising concerns about how to dispose of them to safeguard the environment. This research work uses shredded face masks (SFM) to stabilise clayey soil for sub-grade usage. Shredded face masks are added to clayey soil to investigate consistency limits, compaction characteristics, unconfined compressive strength (UCS), and California bearing ratio (CBR). Laboratory experiments demonstrate that clayey soil geo-technical characteristics such differential free swell, consistency limits, UCS, and CBR values have improved. Based on the CBR results, the IITPAVE software is used to design flexible pavement thickness, which was reduced for various commercial vehicles per day for all combinations. Cost analysis is also done to determine the total cost for a 1000-meter stretch. The results show that addition of SFM to clayey soils strengthen the geo-technical properties of clayey soil as the UCS values increase for all curing periods of 3, 7, and 28 days with a maximum improvement of 64% for 28 days curing for 1% SFM content. Also, the CBR value is found to be increased from 1.96% to 6.72%.
B. Tokhmechi; M. Rabiei; H. Azizi; V. Rasouli
Abstract
A complete and accurate analysis of the complex spatial structure of heterogeneous hydrocarbon reservoirs requires detailed geological models, i.e. fine resolution models. Due to the high computational cost of simulating such models, single resolution up-scaling techniques are commonly used to reduce ...
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A complete and accurate analysis of the complex spatial structure of heterogeneous hydrocarbon reservoirs requires detailed geological models, i.e. fine resolution models. Due to the high computational cost of simulating such models, single resolution up-scaling techniques are commonly used to reduce the volume of the simulated models at the expense of losing the precision. Several multi-scale techniques have also been developed for simulating heterogeneous reservoirs including those in which a limited number of blocks down-scale, i.e. splitting coarse blocks into fine cells around the well-zones in the case of simulation of hydraulic fracturing. In these cases, locally computed basis functions are employed to construct a global solver at a coarse-scale such as wavelet- and kernel-based up-scaling techniques. In this paper, a novel/robust 2D block-ordering system is presented, which enables solving multi-resolution up-scaling fluid flow simulations. The results will be described for a simple model, and fluid flow equations will be developed in order to show the structure of transmissibility matrix. It is confirmed that with a developed block-ordering system not only the accuracy of history match increases but also the CPU time decreases.
Environment
Debasmita Basu; Smriti Mishra
Abstract
This study presents a comprehensive analysis of community perceptions regarding the impacts of reclamation strategies for abandoned coal mines in India, with a specific focus on the Manikpur Coal Mine. Through a structured survey administered to residents in the vicinity of the mine, the research investigates ...
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This study presents a comprehensive analysis of community perceptions regarding the impacts of reclamation strategies for abandoned coal mines in India, with a specific focus on the Manikpur Coal Mine. Through a structured survey administered to residents in the vicinity of the mine, the research investigates the economic, socio-cultural, and environmental impacts of reclamation efforts. Utilizing Structural Equation Modeling (SEM), the study identifies key factors influencing community perceptions, including the perceived benefits of reclamation, levels of community involvement, and overall satisfaction with mining operations. The findings reveal significant relationships among these factors, such as the positive influence of reclamation availability/requirement (path coefficient = 0.633) on satisfaction and the negative impact of involvement on satisfaction (-0.805). Indirect effects highlight the interplay between constructs, with experience positively influencing involvement (0.673) and satisfaction (0.162) while negatively affecting reclamation availability/requirement (-0.194). Variations in latent variable scores for satisfaction (-1.63 to 3.031) and reclamation availability/requirement (-1.42 to 1.903) underscore the diverse respondent experiences. These insights emphasize the importance of effective community engagement and tailored reclamation strategies. Policy recommendations are provided to enhance the sustainability and effectiveness of reclamation efforts, emphasizing the need for holistic approaches that integrate economic viability, socio-cultural acceptance, and environmental sustainability. The study contributes to the field of mine reclamation by offering valuable insights into resident perceptions and practical guidelines for improving reclamation practices in mining-affected areas.
Environment
Aditi Nag; Smriti Mishra
Abstract
This review paper delves into the burgeoning cultural phenomenon of dark tourism, specifically exploring its connection with Mining Heritage Towns (MHTs). The paper navigates the intricate interplay between tourism competitiveness and ethical considerations in these sites laden with historical trauma ...
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This review paper delves into the burgeoning cultural phenomenon of dark tourism, specifically exploring its connection with Mining Heritage Towns (MHTs). The paper navigates the intricate interplay between tourism competitiveness and ethical considerations in these sites laden with historical trauma through a meticulous analysis of existing literature, case studies, and ethical frameworks. Dark tourism, characterised by exploring locations associated with tragedy, has emerged as a global trend, prompting a critical examination of its economic, cultural, and ethical dimensions within mining heritage contexts. Drawing on a wide array of sources, this comprehensive review elucidates the challenges confronting managers of heritage sites, shedding light on the complex ethical dilemmas they face. The paper comprehensively analyses the complex relationship between tourism competitiveness and ethical practices. It critically evaluates the impact of dark tourism on MHTs' economic landscape, explores its cultural implications, and delves into the ethical complexities of such visits, enriching academic discourse and offering valuable guidance for practitioners and policy-makers. The study enhances understanding of dark tourism's role in MHTs and advocates for sustainable tourism development, emphasising ethical considerations in shaping the future of these unique and historically significant sites.
O.E. Ifelola
Abstract
Metals are ubiquitous within the earth crust. However, the exceptional high-level concentration of heavy metals in the soil due to natural or anthropogenic activities and the chemical forms in which they exist determine the level of risk they portend to the environment. This work was aimed at determining ...
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Metals are ubiquitous within the earth crust. However, the exceptional high-level concentration of heavy metals in the soil due to natural or anthropogenic activities and the chemical forms in which they exist determine the level of risk they portend to the environment. This work was aimed at determining the background level of the presence of seven priority toxic metals (Cr, Ni, Pb, As, Cd, Cu, Zn) in the chemical phases of the overburden topsoil of a bituminous deposit prior to mining activities through the speciation analysis. The grab samples of overburden topsoil were initially obtained and homogenized to composites based on locations for the subsequent sequential extraction procedure (SEP). The specific physico-chemical properties of the sampled soils were simultaneously determined to complement the SEP inferential analysis. The results obtained showed that most metals were spatially bounded to the Fe-Mn oxides (reducible phase) followed by the organic (oxidizable) and the carbonates phases, respectively. Fractionally, the dominant soil texture in the studied area was sand (55.45%); however, the colloidal organic matter and Fe-Mn oxide phases played the dominant roles in the sorption activities of the selected metals. The soil chemical phase with the least metal pool was the exchangeable (water/salt) soluble fraction. The overall assessment revealed that the geogenic heavy metals in the topsoil posed no threats since a marginal fraction of the metals existed in the bio-available form in non-toxic concentrations in the order of Pb > Zn > Cu, while the potential mobility of metals showed that Zn was preferentially higher than Pb and Cu, respectively.
S. Hryhorovych Nehrii; T. Oleksandrivna Nehrii; H. Viktorivna Piskurska; E. Viktorovych Fesenko; Y. Yevhenovych Pavlov; A. Mykolaiovych Surzhenko
Abstract
In this work, we focus on the technology of stabilizing roof rocks by constructing separate rock supports reinforced with metal grids. Their parameters are specified using the results of physical structural modeling. The reinforced and non-reinforced rock supports with different fractional compositions ...
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In this work, we focus on the technology of stabilizing roof rocks by constructing separate rock supports reinforced with metal grids. Their parameters are specified using the results of physical structural modeling. The reinforced and non-reinforced rock supports with different fractional compositions are arranged and tested. Their initial shapes are similar to rectangular parallelepipeds with the base width-to-length ratios of 1:1, 1:1.5, and 1:2. Their shrinkage is determined by loading the supports regarding the rock particle size and the reinforcement density. Increasing the reinforcement density leads to reducing the linear dimensions without losing load-bearing capacity. It is proved that using the grids conduces the self-wedging of the rock particles. They are most effective at the initial stage of the formation of the load-bearing core. The exponential power dependence of the relative support shrinkage on the grid partitions number is obtained. The bearing core sizes in different supports are determined. For the non-reinforced supports, the core width is about 60% of the initial support width, and for the reinforced ones, it is about 90%. The exponential dependence of the core width-to-height ratio on the number of grid partitions is established. The expression for determining the reinforced support width is obtained. The support stability depends on the smallest initial base size. The size of the rock material has a little effect on the shrinkage. Reinforcement by three metal grids leads to reducing the pliability by 21% and 24% for the supports with the side ratios of 1:1 and 2:1, respectively.
