Mineral Processing
H. Jafari; H. Abdollahi; M. Gharabaghi; A.A. Balesini
Abstract
In this research work, solvent extraction and stripping of zinc ions from a Zn-Mn-Cd-bearing solution was investigated using D2EHPA as the extractant in a chloride medium. The efficiency of the extraction and stripping stages was evaluated separately, and different parameters such as the pH, extractant ...
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In this research work, solvent extraction and stripping of zinc ions from a Zn-Mn-Cd-bearing solution was investigated using D2EHPA as the extractant in a chloride medium. The efficiency of the extraction and stripping stages was evaluated separately, and different parameters such as the pH, extractant concentration, reaction temperature, and contact time were studied. Based on the results obtained, 97% of zinc, 14% of manganese, and 3% of cadmium were extracted at pH = 2.5, 10% (v/v) of D2EHPA, and 40 °C from the solution containing 5 g L-1 of each metal ion. The stripping isotherms of zinc, manganese, and cadmium at different pH values showed that manganese and zinc were stripped at two different pH values. Thus more than 70% of manganese and more than 90% of zinc were stripped at pH = 2.5 and pH = 0.5, respectively. Kinetic studies indicated that the extraction and stripping of zinc in the first 0.5-1 minute was high. The McCabe–Thiele diagrams showed that two stages of extraction and two stages of stripping in the continuous counter-current flow condition were adequate to separate zinc from Mn and Cd. The dominant Zn species extracted by D2EHPA was ZnCl+, and the values for the thermodynamic parameters ΔHo, ΔSo, and ΔGo were 25.65 kJ mol−1, 79.20 J K−1 mol−1, and 0.86 kJ mol−1, respectively, which showed that the reaction was endothermic at equilibrium.
Rock Mechanics
Amirhossein Naseri; Behnam Maleki; Tohid Asheghi Mehmandari; Amin Tohidi; Ahmad Fahimifar
Abstract
The present study delves into investigating the impact of sample size and geometry on the mechanical behavior of rock and concrete. More specifically, it examines factors including Uniaxial Compressive Strength (UCS), Elastic Modulus (E), and Pressure Wave Velocity (Vp). Results indicated a notable correlation ...
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The present study delves into investigating the impact of sample size and geometry on the mechanical behavior of rock and concrete. More specifically, it examines factors including Uniaxial Compressive Strength (UCS), Elastic Modulus (E), and Pressure Wave Velocity (Vp). Results indicated a notable correlation between the dimensions and morphology of the specimens with these properties. All tests were conducted at a uniform loading rate of 0.002 mm/s. According to the outcomes, the effect of sample size and shape on UCS for concrete is more predictable than for rock. The increase in the sample size led to an initial increase followed by a decline in the UCS values of the rocks. Furthermore, the concrete typically showed a drop in the UCS values as sample size increased. The UCS and E values rose at first before falling, suggesting the existence of a sample size with maximum UCS. The Vp values of the prismatic rock and concrete samples continually grew. After attaining their optimum strength, the prismatic samples showed greater degrees of flexibility and ductility compared to cylindrical ones because of post peak behavior. This suggests that prismatic samples, with their less slender geometry and reduced tendency for brittle behavior, are deemed more suitable for UCS testing. These results can improve the accuracy of assessing the mechanical properties of tunneling materials, particularly those used in subsurface construction in urban roads and highways.
Rock Mechanics
Sadegh Amoun; Hamid Chakeri
Abstract
This study is an attempt to design and manufacture a tunnel boring machine (TBM) simulator to better understand the interaction between soil and cutting tools, due to the lack of an accepted method for this issue. In this paper, Sahand Soil Abrasion Test (SSAT) is introduced, which is built by the Sahand ...
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This study is an attempt to design and manufacture a tunnel boring machine (TBM) simulator to better understand the interaction between soil and cutting tools, due to the lack of an accepted method for this issue. In this paper, Sahand Soil Abrasion Test (SSAT) is introduced, which is built by the Sahand University of Technology. The experimental and real results of tool wear are presented. The results firstly demonstrate that the cutting tools wear in the coarse-grained soils can be less than in the fine-grained ones in the real conditions. However, in the soils with fine grains higher than 10%, the wear of cuttings tools increase in the laboratory condition when grading parameters increase. In soils with fine grains less than 10%, the wear of tools decreases by increasing the grading parameters. Also the results reveal that the coefficient of gradation depend on the amount of silt and clay in the soil samples. The investigations show that sorting is another good criterion for investigating the power of soil abrasively. Furthermore, it indicates that the cutting tools wear increases when the moisture content of the soil structure in the dense condition approaches the optimal moisture content. Finally, the results indicate that the wear and torque of the cutterhead could be reduced by 58% and 34%, respectively, when the excavated materials have the appropriate conditioning.
G. Jozanikohan; M. Nosrati Abarghooei; H. Sedighi
Abstract
The most extensive Iranian coal-bearing basin is located in an area of 30000 km2, situated approximately 75 km from the Tabas county, south Khorasan Province, Iran. In this work, the Tabas coal ash is studied and investigated for the purpose of determination of the rare earth elements (REE) content, ...
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The most extensive Iranian coal-bearing basin is located in an area of 30000 km2, situated approximately 75 km from the Tabas county, south Khorasan Province, Iran. In this work, the Tabas coal ash is studied and investigated for the purpose of determination of the rare earth elements (REE) content, and the identification of the distribution patterns of trace elements. The elemental and phase analysis experiments were conducted using the X-ray diffraction (XRD), inductively-coupled plasma spectroscopy (ICP-MS), wet chemical analysis, and field emission scanning electron microscopy equipped with energy dispersive X-ray spectroscopy (FE-SEM/EDS) techniques. The XRD results showed that the phases in the Tabas coal ash were quartz, clay minerals, alkali feldspar, magnetite, and pyrite in order of abundance. The elemental analysis showed that the major elements were Si, Al, K, Fe, Mg, S, and Na, which was in good accordance with the chemical composition of the recognized minerals by the XRD method. The concentration of REEs was varied from 0.10 ppm (for Tm) to 68.48 ppm (for Ce), with an arithmetic mean of 14.19 ppm. The abundance of 16 REE elements was or even below the average of the earth crust abundances. Only one rare earth element (Samarium) was about 4.4 and 2.2 times more abundant than in the earth crust and in the world coking coal ashes. In order to further assess the occurrence states of REEs in each of detected mineral, the Fe-SEM/EDX method was used. The SEM/EDS analysis showed that REEs were mainly concentrated in the clay minerals.
B. Shokouh Saljoughi; A. Hezarkhani
Abstract
In this paper, we aim to achieve two specific objectives. The first one is to examine the applicability of wavelet neural network (WNN) technique in ore grade estimation, which is based on integration between wavelet theory and Artificial Neural Network (ANN). Different wavelets are applied as activation ...
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In this paper, we aim to achieve two specific objectives. The first one is to examine the applicability of wavelet neural network (WNN) technique in ore grade estimation, which is based on integration between wavelet theory and Artificial Neural Network (ANN). Different wavelets are applied as activation functions to estimate Cu grade of borehole data in the hypogene zone of porphyry ore deposit, Shahr-e-Babak district, SE Iran. WNN parameters such as dilation and translation are fixed and only the weights of the network are optimized during its learning process. The efficacy of this type of network in function learning and estimation is compared with Ordinary Kriging (OK). Secondly, we aim to delineate the potassic and phyllic alteration regions in the hypogene zone of Cu porphyry deposit based on the estimation obtained of WNN and OK methods, and utilize Concentration–Volume (C–V) fractal model. In this regard, at first C–V log–log plots are generated based on the results of OK and WNN. The plots then are used to determine the Cu threshold values of the alteration zones. To investigate the correlation between geological model and C-V fractal results, the log ratio matrix is applied. The results showed that, Cu values less than 1.1% from WNN have more overlapped voxels with phyllic alteration zone by overall accuracy (OA) of 0.74. Spatial correlation between the potassic alteration zones resulted from 3D geological modeling and high concentration zones in C-V fractal model showed that the alteration zone has Cu values between 1.1% and 2.2% with OA of 0.72 and finally have an appropriate overlap with Cu values greater than 2.2% with OA of 0.7. Generally, the results showed that the WNN (Morlet activation function) with OA greater than OK can be can be a suitable and robust tool for quantitative modeling of alteration zones, instead of qualitative methods.
Vahab Sarfarazi; Hadi Haeri; Fereshteh Bagheri; Erfan Zarrin ghalam; Mohammad Fatehi Marji
Abstract
The tensile strengths of geomaterials such as rocks, ceramics, concretes, gypsum, and mortars are obtained based on the direct and indirect tensile strength tests. In this research work, the Brazilian tensile strength tests are used to study the effects of length and inclination angle of T-shaped non-persistent ...
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The tensile strengths of geomaterials such as rocks, ceramics, concretes, gypsum, and mortars are obtained based on the direct and indirect tensile strength tests. In this research work, the Brazilian tensile strength tests are used to study the effects of length and inclination angle of T-shaped non-persistent joints on the mechanical and tensile behaviors of the geomaterial specimens prepared from concrete. These specimens have a thickness of 40 mm and a diameter of 100 mm, and are prepared in the laboratory. Two T-shaped non-persistent joints are made within each Brazilian disc specimen. The Brazilian disc specimens with T-shaped non-persistent joints are tested experimentally in the laboratory under axial compression. Then these tests are simulated in the two-dimensional particle flow code (PFC2D) considering various notch lengths of 6, 4, 3, 2, and 1 cm. However, different notch inclination angles of 0, 30, 60, 90, 120, and 150 degrees are also considered. In this research work, 12 specimens with different configurations are provided for the experimental tests, and 18 PFC2D models are made for the numerical studies of these tests. The loading rate is 0.016 mm/s. The results obtained from these experiments and their simulated models are compared, and it is concluded that the mechanical behavior and failure process of these geomaterial specimens are mainly governed by the inclination angles and lengths of the T-shape non-persistent joints presented in the samples. The fracture mechanism and failure behavior of the specimens are governed by the discontinuities, and the number of induced cracks when the joint inclination angles and joint lengths are increased. For larger joints when the inclination angle of the T-shaped non-persistent joint is around 60 degrees, the tensile strength is minimum but as it is closed to 90 degrees, the compressive strengths are maximum. However, an increase in the notch length increase the overall tensile strength of the specimens. The strength of samples decreases by increasing the joint length. The strain at the failure point decreases by increasing the joint length. It is also observed that the strength and failure process of the two sets of specimens and the corresponding numerical simulations are consistence.
Exploration
Mohammadjafar Mohammadzadeh; Majid Mahboubiaghdam; Moharram Jahangiri; Aynur Nasseri
Abstract
Most machine learning-monitored algorithms used to create mineral potential prediction maps require noise-free data to achieve high performance and reliable results. Unsupervised clustering methods are highly effective for uncovering a dataset’s hidden structures. Therefore, this study attempts ...
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Most machine learning-monitored algorithms used to create mineral potential prediction maps require noise-free data to achieve high performance and reliable results. Unsupervised clustering methods are highly effective for uncovering a dataset’s hidden structures. Therefore, this study attempts a combination of supervised and unsupervised methods employing training and testing data to generate a highly accurate potential map of the Sonajil copper-gold deposit located in the NW of Iran. Here, a semi-supervised Bayesian algorithm is used to map the mineral landscape. Initially, ten raster layers of exploratory features are prepared. Then based on the copper concentration, 27 exploratory drilled boreholes are divided into four classes, C1 to C4, and from each class, two boreholes are selected, and 100-meter buffering is performed around these boreholes to extract 1113 training data based on the behavioral pattern of boreholes and surface samples. Subsequently, the existing data is clustered using the FCM method, and the total dataset and the clustering data are entered into the Bayesian algorithm to evaluate the accuracy of the Bayesian classifier method across five distinct clusters. The results show increased average accuracy when using clustered data instead of whole data for MPM mapping. Notably, the Bayesian semi-supervised algorithm achieved an impressive accuracy rate of 96% when cluster five data is excluded. To validate the Bayesian semi-supervised method, boreholes data that is not used in training were employed, which confirm the credibility of generated MPM. Overall results highlight the value of the Bayesian semi-supervised algorithm in improving the accuracy and reliability of mineral prospectivity mapping via the application of the FCM clustering method that efficiently organize the data, enabling the Bayesian algorithm to evaluate the accuracy of the Bayesian classifier method across different clusters and providing a successful optimal result in detecting blind ores in areas without exploratory boreholes and delineating more mineralization targets in the Sonajil and adjoining areas.
Mineral Processing
Mohammad Jahani Chegeni; Sajad Kolahi; Asghar Azizi
Abstract
Consumed energy is the most important issue and concern in industrial ball mills, and includes a major part of the costs of mineral processing plants. By using suitable liners and the optimal lifter count, the energy of the mill is properly transferred to the balls. In Part 1 of this research work, five ...
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Consumed energy is the most important issue and concern in industrial ball mills, and includes a major part of the costs of mineral processing plants. By using suitable liners and the optimal lifter count, the energy of the mill is properly transferred to the balls. In Part 1 of this research work, five types of liners, i.e. Lorain, Osborn, Rib, cuboid, and Hi-lo, are examined. These liners all have separate lifters with the same volume. Their difference is in the width, height, and type of lifter profile. First, all types of liners are simulated with four lifters using the Discrete Element Method (DEM). Then the lifter count is increased four by four to fill the entire wall of the mill with lifters. Based on this, Lorain liner from 4 to 24 lifters, Osborn liner from 4 to 120 lifters, Rib liner from 4 to 40 lifters, and cuboid and Hi-lo liners from 4 to 64 lifters are simulated. For the first time, the kinetic (KE) and potential (PE) energies as well as the sum of these two energies (TE) of all the balls are calculated, and compared in the entire duration of the simulation from 0–13s for all the liner types and lifter counts mentioned above. Finally, by using data related to KE, PE, and TE for each type of liner, the optimal lifter count is obtained. Accordingly, 16 to 20 lifters are recommended for the Lorain liner, 64 to 76 lifters for the Osborn liner, 24 to 32 lifters for the Rib liner, 44 lifters for the cuboid liner, and 36 to 44 lifters for the Hi-lo liner.
Exploration
Moslem Jahantigh; Hamid Reza Ramazi
Abstract
The present paper gives out data-driven method with airborne magnetic data, airborne radiometric data, and geochemistry data. The purpose of this study is to create a mineral potential model of the Shahr-e-Babak studied area. The studied area is located in the south-eastern of Iran. The various evidential ...
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The present paper gives out data-driven method with airborne magnetic data, airborne radiometric data, and geochemistry data. The purpose of this study is to create a mineral potential model of the Shahr-e-Babak studied area. The studied area is located in the south-eastern of Iran. The various evidential layers include airborne magnetic data, airborne radiometric data (potassium and thorium), lineament density map, cu geochemistry signature, and multi-variate geochemistry signature (PC1). High magnetic anomalies, lineament structures, and alteration zones (K/Th) were derived from airborne geophysics data. Geochemistry signatures (Cu and PC1) were derived from stream sediment data. The principal Component Analysis (PCA) as an unsupervised machine learning method and five evidential layers were used to produce a porphyry prospectivity model. As a result of this combination, mineral prospectivity model was produced. Then a plot of cumulative percent of the studied area versus pca prospectivity value was used to discrete high potential areas. Then to evaluate the ability of this MPM, the location of known cu indications was used. The results confirm an acceptable outcome for porphyry prospectivity modeling. Based on this model high-potential areas are located in south southwestern and eastern parts of the studied area.
Rock Mechanics
Shahla Miri Darmarani; Erfan Khoshzaher; Hamid Chakeri
Abstract
Shotcrete is used as a component of the support system in tunnels, and one of the methods to enhance its mechanical properties is by incorporating fibers. Fibers can significantly improve the mechanical properties of shotcrete, including compressive and tensile strength. This leads to savings in time, ...
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Shotcrete is used as a component of the support system in tunnels, and one of the methods to enhance its mechanical properties is by incorporating fibers. Fibers can significantly improve the mechanical properties of shotcrete, including compressive and tensile strength. This leads to savings in time, cost, and post-installation maintenance. In recent years, due to the environmental pollution caused by the production of synthetic fibers, there has been increasing interest in using recycled materials, mainly recycled steel fibers from worn tires. The present study is a laboratory-based research program investigating the feasibility of using recycled fibers to improve the mechanical properties of shotcrete. In this study, recycled steel fibers from worn tires and shaves of basalt stone were used to create laboratory samples. The laboratory samples included cubic (10×10 cm) and cylindrical (15×30 cm) specimens with five different mix designs: ordinary shotcrete, shotcrete containing 0.5%, 1%, 1.5%, and 2% recycled fibers. These fibers were categorized into three length groups: coarse, mixed, and fine. The laboratory tests included compressive and tensile (Brazilian) strength tests at 3-day intervals. The results of the laboratory studies indicated that recycled fibers from worn tires could significantly enhance the mechanical properties of shotcrete, with a two-fold increase in compressive strength observed when the fiber content was increased by 2%. Moreover, the inclusion of basalt stone shaves not only improved the compressive strength of the samples but also had a substantial effect on enhancing the tensile strength.
Hassan Bakhsandeh Amnieh; Alireza Mohammadi; M Mozdianfard
Abstract
Ground vibrations caused by blasting are undesirable results in the mining industry and can cause serious damage to the nearby buildings and facilities; therefore, controlling such vibrations has an important role in reducing the environmental damaging effects. Controlling vibration caused by blasting ...
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Ground vibrations caused by blasting are undesirable results in the mining industry and can cause serious damage to the nearby buildings and facilities; therefore, controlling such vibrations has an important role in reducing the environmental damaging effects. Controlling vibration caused by blasting can be achieved once peak particle velocity (PPV) is predicted. In this paper, the values of PPV have been predicted and compared using the artificial neural network (ANN), multivariate regression analysis (MVRA) and empirical relations. The necessary data were gathered from 11 blast operations in Sarcheshmeh copper mine, Kerman. The neural network input parameters include distance from blast point, maximum charge weight per delay, spacing, stemming and the number of drill-hole rows in each blasting operation. The network is of the multi-layer perception (MLP) type with 24 sets of training data including 2 hidden layers, 1 output layer with the network architecture of {5-11-12-1}, and Sigmoid tangent and linear transfer functions. To insure the training accuracy, the network was tested by 6 data sets; the determination coefficient and the average relative error were found to be 0.977 and 8.85%, respectively, showing the MLP network’s high capability and precision in estimating the values of the PPV. To predict these values, MVRA and empirical relations were analyzed. The results have revealed that these relations have low capability in estimating the PPV parameter.
Mineral Processing
M. B. Fathi; B. Rezai; E. K. Alamdari; R. D. Alorro
Abstract
The effects of the functional groups and structures of two different resins, weak base/macroporous and strong base/gel type, Purolite A170 and Dowex 21K on the adsorption properties of Re(VII) ions were investigated experimentally and described by the isotherm, kinetic, and thermodynamic modeling. In ...
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The effects of the functional groups and structures of two different resins, weak base/macroporous and strong base/gel type, Purolite A170 and Dowex 21K on the adsorption properties of Re(VII) ions were investigated experimentally and described by the isotherm, kinetic, and thermodynamic modeling. In this regard, four widely used adsorption isotherm models including Langmuir, Freundlich, Temkin, and Dubinin-Radushkevich (D-R) were subjected to the sorption data in order to describe the reactions involved. Evaluating the correlation coefficients showed that the Freundlich and D-R isotherm models provided the best fit. The Langmuir isotherm capacities (qm) indicated that the perrhenate ion (ReO4-) adsorption was higher for the weak base/macroporous type resin rather than the others (166.67 mg/g and 142.86 mg/g, respectively). Moreover, the results of the EDX studies were in agreement with the previous results. Furthermore, the adsorption kinetics was demonstrated through fitting the data into different mechanisms, among which the pseudo-second-order mechanism was found to be successful for both resins; however, in the case of Dowex 21K, the rate of perrhenate ion uptake was more rapid than that for Purolite A170. Evaluation of the thermodynamic parameters also showed that the reaction mechanism was different for each case and that the adsorption of rhenium on Dowex 21K became more feasible with increase in temperature due to negative values for ΔH.
P. Tahmasebizadeh; S. Javanshir
Abstract
In this work, zinc extraction from an industrial leach solution was investigated by saponified di(2-ethylhexyl)phosphoric acid (D2EHPA). The solution obtained was from a bioleaching process of a low-grade lead-zinc sulfide ore that contained 50 g/L of zinc and 6.3 g/L of iron. The selective and high ...
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In this work, zinc extraction from an industrial leach solution was investigated by saponified di(2-ethylhexyl)phosphoric acid (D2EHPA). The solution obtained was from a bioleaching process of a low-grade lead-zinc sulfide ore that contained 50 g/L of zinc and 6.3 g/L of iron. The selective and high Zn(II) extraction yield were obtained by modification of D2EHPA in a proposed two-step process. Firstly, a significant amount of iron (87%) was removed as sodium-jarosite via precipitation from the pregnant leaching solution (PLS) prior to zinc extraction, and secondly, the effective parameters involved in zinc extraction including the contact time, saponification degree, type of saponifier, stirring speed, pH, temperature, D2EHPA concentration, and phase ratio (A:O) were investigated. The results obtained showed that 98.4% of zinc could be extracted under the optimum conditions, i.e. 20% D2EHPA, 15% saponification degree, 650 rpm, pH 2, and an A:O ratio of 1:1 at the ambient temperature (25 ± 2 °C) during 90 s; it was 25% higher than using non-saponified D2EHPA under the same conditions. Moreover, while one theoretical step was required for the complete extraction of zinc by saponified D2EHPA, the required number of steps using D2EHPA was about three. Therefore, the advantages of the process would be two-fold: reducing the number of extraction stages and no need for neutralizing the raffinate in every extraction stage.
Rock Mechanics
M. Hosseini; A. R. Khodayari
Abstract
In an era of continued economic development around the globe, numerous rock-related projects including mining and gas/oil exploration are undertaken in regions with cold climates. Winters in the Iranian western and northwestern provinces are characterized by a high precipitation rate and a cold weather. ...
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In an era of continued economic development around the globe, numerous rock-related projects including mining and gas/oil exploration are undertaken in regions with cold climates. Winters in the Iranian western and northwestern provinces are characterized by a high precipitation rate and a cold weather. Under such conditions, rocks are exposed to long freezing periods and several freeze-thaw (F-T) cycles. It is thus necessary to examine the impact of these cycles on the physical and mechanical properties of rocks. Considering the abundant sandstone resources in Iran, in this work, we focused on the Lushan sandstone by investigating the effects of F-T cycles and freezing temperatures on the uniaxial and triaxial compressive strengths, cohesion, internal friction angle, and elastic modulus of the rocks. To study the impact of the number of F-T cycles on the strength of rocks, the specimens frozen at -16 °C were subjected to 1, 4, 8, 16, and 32 F-T cycles. Similar tests were also carried out on the specimens frozen at -24 °C. Furthermore, a number of tests were undertaken at the ambient temperature (25 °C) on specimens that did not undergo an F-T cycle. According to the results obtained, an increase in the number of F-T cycles and freezing temperatures reduced the uniaxial and triaxial compressive strengths, cohesion, internal friction angle, and elastic modulus due to the growth of the existing cracks and the nucleation of new cracks in the rock. Consequently, the effective porosity increased, whereas the dry specific gravity decreased with more F-T cycles and lower freezing temperatures.
H. Sarfaraz; A.R. Bahrami; R. Samani
Abstract
A common instability in the rock slopes is a toppling failure. If this type of slope failure occurs due to another kind of failure, it is considered as the secondary toppling failure. A type of secondary toppling failure is the slide-head-toppling failure. In this instability, the upper portion of the ...
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A common instability in the rock slopes is a toppling failure. If this type of slope failure occurs due to another kind of failure, it is considered as the secondary toppling failure. A type of secondary toppling failure is the slide-head-toppling failure. In this instability, the upper portion of the slope is toppled, and the pressure caused by the overturning of rock blocks leads to a semi-circular sliding in the soil mass at the slope toe. This instability is examined through the theoretical analysis and physical modelling. Firstly, the failure mechanism mentioned above is described. Next, the slide-head-toppling failure is studied through seven numerical simulations. The Phase2 and UDEC softwares, as the finite element and distinct element methods, respectively, are used in this work. Different kinds of slide-head-toppling failure are modelled such as the blocky, block-flexural, and flexural toppling failures. The numerical modelling results are compared with the existing physical tests and theoretical approaches. This comparison illustrates that the safety factor is underestimated due to the plane strain supposition in numerical modelling. However, the side-friction in the physical models has violated this assumption. The results obtained demonstrate that the distinct element method has an acceptable accuracy compared to the finite element method. Thus this numerical code can be used in order to examine the mentioned failure.
Mine Economic and Management
R. Bastami; A. Aghajani Bazzazi; H. Hamidian Shoormasti; K. Ahangari
Abstract
The use of blasting cost (BC) prediction to achieve optimal fragmentation is necessary in order to control the adverse consequences of blasting such as fly rock, ground vibration, and air blast in open-pit mines. In this research work, BC is predicted through collecting 146 blasting data from six limestone ...
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The use of blasting cost (BC) prediction to achieve optimal fragmentation is necessary in order to control the adverse consequences of blasting such as fly rock, ground vibration, and air blast in open-pit mines. In this research work, BC is predicted through collecting 146 blasting data from six limestone mines in Iran using the artificial neural networks (ANNs), gene expression programming (GEP), linear multivariate regression (LMR), and non-linear multivariate regression (NLMR) models. In all models, the ANFO value, number of detonators, Emolite value, hole number, hole length, hole diameter, burden, spacing, stemming, sub-drilling, specific gravity of rock, hardness, and uniaxial compressive strength are used as the input parameters. The ANN model results in the test stage indicating a higher correlation coefficient (0.954) and a lower root mean square error (973) compared to the other models. In addition, it has a better conformity with the real blasting costs in comparison with the other models. Although the ANNs method is regarded as one of the intelligent and powerful techniques in parameter prediction, its most important fault is its inability to provide mathematical equations for engineering operations. In contrast, the GEP model exhibits a reliable output by presenting a mathematical equation for BC prediction with a correlation coefficient of 0.933 and a root mean square error of 1088. Based on the sensitivity analysis, the spacing and ANFO values have the maximum and minimum effects on the BC function, respectively. The number of detonators, Emolite value, hole number, specific gravity, hardness, and rock uniaxial compressive strength have a positive correlation with BC, while the ANFO value, hole length, hole diameter, burden, spacing, stemming, and sub-drilling have a negative correlation with BC.
Mahsa Khoshfarman Borji; Ahmad Reza Sayadi; Ehsan Nikbakhsh
Abstract
The iron and steel industry is one of the most resource-intensive and pollutant industries that creates the highest value across all mining and metal industries. While the recent studies provide recommendations to improve sustainable development in this industry, the complexity of the socio-environmental ...
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The iron and steel industry is one of the most resource-intensive and pollutant industries that creates the highest value across all mining and metal industries. While the recent studies provide recommendations to improve sustainable development in this industry, the complexity of the socio-environmental impacts of activities in this industry due to its multi-tier and multi-supply chain structures has given rise to the problem of sustainable steel supply chain network design. This work proposes a new multi-objective mixed-integer linear programming model to integrate sustainability factors with managerial and technical restrictions. The total economic profitability is maximized, while environmental pollution is minimized. There is also a focus on the social and environmental compliance. Accordingly, a novel sustainability assessment system is proposed. The managerial restrictions are also satisfied by maximizing the demand fulfillment priority using a new method. The augmented ε-constraint method is applied to tackle the mathematical problem under study. Finally, a real case study is used. The results obtained 35% and 41% reductions in CO2 and particulate matter emissions, respectively, while the total profit decreases up to 15%. A sensitivity analysis is also performed. In addition, several managerial insights are discussed based on the results.
Exploitation
Mohammad Hossein Jalalian; Raheb Bagherpour; Mehrbod Khoshouei; S. Najmedin Almasi
Abstract
Diamond wire cutting is a common method to extract dimension stones, which depends on various factors, including the mechanical and physical properties of the stone, cutting specifications, and operational characteristics. Specific energy, production rate, efficiency, and wear of diamond beads are some ...
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Diamond wire cutting is a common method to extract dimension stones, which depends on various factors, including the mechanical and physical properties of the stone, cutting specifications, and operational characteristics. Specific energy, production rate, efficiency, and wear of diamond beads are some of the criteria that influence economic and environmental optimization of diamond wire cutting operations. In this study, the specific energy of the diamond wire cutting process was measured for 11 samples of Granite stones. By analyzing the impact of parameters such as stone density, porosity, and cutting rate on energy consumption, a linear regression model was developed with a correlation coefficient (R2) of 0.944 to predict specific energy for different types of stones. Statistical analyses, including ANOVA, have confirmed that the model accurately predicts specific energy values. Data from three new stone samples were used to validate the model, and their predicted energy values were compared with actual values. The model presented achieved an R2 value of 0.827, demonstrating its high accuracy. The results indicate that energy consumption in dimension stone cutting operation can be accurately predicted and characterized indirectly using high precision stone properties and operational parameters. This method can accurately and indirectly monitor energy consumption and cutting machine performance during the dimension stone cutting operation and can be used to optimize economic and environmental aspects of this process.
Mine Economic and Management
Hadi Fattahi; Hossein Ghaedi
Abstract
The maximum energy consumption of stone cutting machines is one of the important cost factors during the process of cutting construction stones. Accurately predicting and estimating the maximum energy consumption performance of the cutting machine, along with estimating the cutting costs, can help approach ...
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The maximum energy consumption of stone cutting machines is one of the important cost factors during the process of cutting construction stones. Accurately predicting and estimating the maximum energy consumption performance of the cutting machine, along with estimating the cutting costs, can help approach the optimal cutting operating conditions to reduce energy consumption and minimize machine depreciation. However, due to the uncertainty and complexity of building stone textures and properties, determining the maximum energy consumption of the device is a difficult and challenging task. Therefore, this paper employs the rock engineering system method to solve the aforementioned problem. To this end, 120 test samples were collected from a marble factory in the Mahalat region of Iran, representing 12 types of carbonate rocks. The input parameters considered for the analysis were the Mohs hardness, uniaxial compressive strength, Young's modulus, production rate, and Schimazek’s F-abrasiveness factors. In the study, 80% of the collected data, equivalent to 96 data points, were utilized to construct the model using the rock engineering system-based method. The obtained results were then compared with other regression methods including linear, power, exponential, polynomial, and multiple logarithmic regression methods. Finally, the remaining 20 percent of the data, comprising 24 data points, were used to evaluate the accuracy of the models. Based on the statistical indicators, namely root mean square error, mean square error, and coefficient of determination, it was found that the rock engineering system-based method outperformed other regression methods in terms of accuracy and efficiency when estimating the maximum energy consumption.
Exploitation
M. Jahangiri; Seyed R. Ghavami Riabi; B. Tokhmechi
Abstract
Bearing in mind that lack of data is a common problem in the study of porphyry copper mining exploration, our goal was set to identify the hidden patterns within the data and to extend the information to the data-less areas. To do this, the combination of pattern recognition techniques has been used. ...
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Bearing in mind that lack of data is a common problem in the study of porphyry copper mining exploration, our goal was set to identify the hidden patterns within the data and to extend the information to the data-less areas. To do this, the combination of pattern recognition techniques has been used. In this work, multi-layer neural network was used to estimate the concentration of geochemical elements. From 1755 surface and boreholes data available, analyzed by ICP, 70% was used for training, and the rest for testing. The average accuracy of estimators for 22 geochemical elements when using all data was equal to 75%. Based on validation, the optimal number of clusters for the total data was identified. The Gustafson-Kessel (GK) clustering was used to design the estimator for the geochemical element concentrations in different clusters, and the clusters were selected for estimation. The results obtained show that using GK, the estimator's average accuracy increase up to 84%. The accuracy of the elementsZn, As, Pb, Mo, and Mn with low accuracies of 0.51, 0.62, 0.64, 0.65, and 0.68 based on all data were developed to 0.76, 0.86, 0.76, 0.80, and 0.71 with the clustered data, respectively. The mean square error using all the data was 0.079, while in the case of hybrid developed method, it decreased to 0.048. There were error reductions in Al from 0.022 to 0.012, in As, from 0.105 to 0.025, and from 0.115 to 0.046 for S.
M. Samadi; S. Torbati; S. Alipour
Abstract
Heavy metal(loid) contamination in the environment of mining areas has become an important problem. Cheshemeh-Konan is one of the main copper deposits in NW Iran that is currently abandoned. In the present work, the intensity of some metal(loid) pollutions in the soil of the mining area was assessed ...
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Heavy metal(loid) contamination in the environment of mining areas has become an important problem. Cheshemeh-Konan is one of the main copper deposits in NW Iran that is currently abandoned. In the present work, the intensity of some metal(loid) pollutions in the soil of the mining area was assessed using three reliable indices. In addition, the potential of Sonchus oleraceus L., as the dominant plant grown in the area, in the uptake of some metal(loid)s from the soil was evaluated. The plant and soil samples were collected from the mining area and analyzed by inductively coupled plasma-mass spectrometry (ICP-MS). The results obtained revealed that the soil of the studied mining area was considerably contaminated by As (CF = 3.1), Cr (CF = 3.8), and Ni (CF = 4.07). It was confirmed that S. oleraceus had a good ability to accumulate Cd (0.74 mg/kg), Mo (0.67 mg/kg), Sr (285.80 mg/kg), Sn (161.10 mg/kg), and Sc (30.35 mg/kg) when mean concentrations of these metals in the soil were 0.14, 0.12, 161.05, 1.94, and 17.9 mg/kg, respectively. The plant biological absorption coefficient for these 5 elements was more than 1. The correlations between the Mo and Sr contents in the soil and plant were significantly positive. According to the results obtained, the present work provides some geochemical findings about the substrate, and leads to the increasing information about the relationship between the element concentrations in the plants and different soils.
M. Azadi; M. Abedi; Gh. H. Norouzi Baghkameh
Abstract
< p>Attenuation of the signal received from sources causing anomalies and reduction of data resolution are the negative features of airborne measurements. Using a stable downward continuation method is a practical way to address these shortcomings. In this study, we investigated the efficiency ...
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< p>Attenuation of the signal received from sources causing anomalies and reduction of data resolution are the negative features of airborne measurements. Using a stable downward continuation method is a practical way to address these shortcomings. In this study, we investigated the efficiency of various stabilizers in achieving stable downward continued data. The purpose of this study is to select the most appropriate stabilizer(s) for this operation. We examined the various stabilizing functions by introducing them into the Tikhonov regularization problem. The results of research on synthetic airborne gravity and magnetic data showed that βL1 (the other definition of L1 norm) and SM (the smoothest model) stabilizers have the potential to be used in the stable implementation of the downward continuation method. These stabilizers performed better than the other in the three comparisons, including visual, quantitative (RMS error), and graphical comparisons. Also, by examining the airborne magnetic data related to the Esfordi district in Yazd province (Iran), it was found that in general the βL1 stabilizer is more suitable than the other stabilizing functions studied in this research.
M. Hosseini; H. Madani; K. Shahriar
Abstract
Stations are the main components of the subway systems. Despite the progress in the construction and maintenance, stations have always been exposed to the natural and man-made disasters. In such incidents, the station’s evacuation capability has a direct relation with a passenger's life. Various ...
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Stations are the main components of the subway systems. Despite the progress in the construction and maintenance, stations have always been exposed to the natural and man-made disasters. In such incidents, the station’s evacuation capability has a direct relation with a passenger's life. Various factors affect the station's evacuation capability. Investigation of these factors and evaluation of the station’s evacuation capability have important roles in protecting a passenger's life. For this purpose, the catastrophic events that lead to the evacuation of a station and the factors affecting the evacuation of the station are identified. Due to the difference in the catastrophic event probabilities at each station, the risk of catastrophic events is evaluated. Then the station score is calculated according to the value and weight of the evacuation factors and the wighted influence of the catastrophic events. Accordingly, the proposed model is implemented in the Tehran subway. Based on the results obtained, uncrowded stations, even though served by a small number of passengers, may also have a low evacuation capacity and lead to casualties in an emergency situation. This is due to the lack of emergency management and safety facilities. Also by assessing the risk of catastrophic events at stations and equipping stations on its basis, the degree of safety and evacuation capability can be improved more effectively. The sensitivity analysis of the evacuation factors show that the most effective way to increase the station’s evacuation capability is to improve its status in management factors. Using the proposed model to evaluate the station's evacuation capability is an appropriate method for identifying the stations that have a poor evacuation capability.
M.R. Shahbazi; M. Najafi; M. Fatehi Marji; A. Abdollahipour
Abstract
The in-situ coal is converted to the synthetic gas in the process of underground coal gasification (UCG). In order to increase the rate of in-situ coal combustion in the UCG process, the contact surfaces between the steam, heat, and coal fractures should be raised. Therefore, the number of secondary ...
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The in-situ coal is converted to the synthetic gas in the process of underground coal gasification (UCG). In order to increase the rate of in-situ coal combustion in the UCG process, the contact surfaces between the steam, heat, and coal fractures should be raised. Therefore, the number of secondary cracks should be increased by raising the heat and existing steam pressure during the process. This paper emphasises on the secondary crack growth mechanism of the pre-existing cracks in the coal samples under different loading conditions. Different geometric specifications such as the length of the pre-existing cracks (coal cleats) and their inclinations are considered. The numerical modeling results elucidate that the first crack growths are the wing cracks (also called the primary or tensile cracks) formed due to unbonding the tensile bonds between the particles in the assembly. Ultimately, these cracks may lead to the cleat coalescences. On the other hand, the secondary or shear cracks in the form of co-planar and oblique cracks may also be produced during the process of crack growth in the assembly. These cracks are formed due to the shear forces induced between the particles as the initial cleat length is increased and exceed the dimension of coal blocks. The cavity growth rate increases as the secondary cracks grow faster in the coal blocks. In order to achieve the optimum conditions, it is also observed that the best inclination angle of the initial coal cleat changes between 30 to 45 degrees with respect to the horizon for the coal samples with the elasto-brittle behavior.
Ali Nouri Qarahasanlou; Abbas Barabadi; Meisam Saleki
Abstract
Implementing maintenance protocols for industrial machinery is essential since a well-thought-out plan may support and improve machinery dependability, production quality, and safety precautions. Implementing a maintenance plan that considers the equipment's actual functional behavior and the effects ...
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Implementing maintenance protocols for industrial machinery is essential since a well-thought-out plan may support and improve machinery dependability, production quality, and safety precautions. Implementing a maintenance plan that considers the equipment's actual functional behavior and the effects of failures will be easier and more practical. Engineers must consider environmental conditions when studying in hostile environments such as mine. The major goal of this study is to create a mining equipment maintenance program that is as effective as possible while incorporating risk and performance indicators and taking environmental factors into account. The study uses the “reliability-centered maintenance” method, which combines the reliability operating index and risk. The Cox model also includes the risk factors associated with environmental conditions in the reliability analysis. The proposed approach was implemented in a 5-758 Komatsu dump-truck case study at the Sungun copper mine in Iran. The reliability-centered maintenance approach is implemented for dump-truck in three scenarios based on risk factors: 1- baseline, 2- First semi-annual, cheap maintenance, and 3- second semi-annual, expensive maintenance. All failure modes are low-risk, making corrective maintenance appropriate. In Scenario 1, electrical-electrical, electrical-start, mechanical, and pneumatic-related failures are low-risk, making corrective maintenance suitable. In Scenario 2, corrective maintenance is recommended for pneumatic-related failure. In Scenario 3, the fuel-related failure has a high criticality number and failure intensity, indicating a high-risk situation. Time-based preventive maintenance is the most appropriate strategy for this scenario.
