Exploitation
R. Razzaghzadeh; R. Shakoor Shahabi; A. Nouri Qarahasanlou
Abstract
The appropriate operating of mining machines is affected by both the executive and environmental factors. Considering the effects and the related risks lead to a better understanding of the failures of such machines. This leads to a proper prediction of the reliability parameters of such machines. In ...
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The appropriate operating of mining machines is affected by both the executive and environmental factors. Considering the effects and the related risks lead to a better understanding of the failures of such machines. This leads to a proper prediction of the reliability parameters of such machines. In this research work, the reliability and maintainability analysis of the loading and haulage machines in the Sungun Copper Mine, considering the repair condition as multiple repairable units, was performed. For this purpose, the data necessary for the loading and haulage equipment including 2 loaders and 8 dump trucks for a 15-month period was collected and categorized in 10 operational units after the system and sub-systems of the department were determined. Initially, the time between failures (TBFs) and time to repair (TTR) for each unit was calculated. Then 20 sub-systems were developed. Primarily, the Stata software was utilized to carry out the heterogeneity test for all the sub-systems. In consequence, most of the sub-systems were regarded as the heterogeneous ones, except for 7 of them including the dump truck units 1, 2, 3, 4, 5, 7, and 8 in TBFs. Hence, "PHM" that is a covariate-based model displayed the heterogeneous group. Its reliability function was also estimated. For the next step, the trend tests were done on the non-heterogeneous sub-systems by means of the Minitab software. The homogeneous sub-systems with failure trend were modeled by “NHPP”. Afterwards, the non-trended sub-systems formed the data group. Later, the correlation tests were modeled by “HPP”. Finally, the reliability and maintainability functions were calculated with the 95% confidence level.
Exploitation
Moslem Jahantigh; Hamidreza Ramazi
Abstract
Various methods have been used for clustering big data. Pattern recognition methods are suitable methods for clustering these data. Due to the large volume of samples taken in the drilling of mines and their analysis for various elements, this category of geochemical data can be considered big data. ...
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Various methods have been used for clustering big data. Pattern recognition methods are suitable methods for clustering these data. Due to the large volume of samples taken in the drilling of mines and their analysis for various elements, this category of geochemical data can be considered big data. Examining and evaluating drilling data in the Lar copper mine in Sistan and Baluchistan province located in the southeast of Iran requires the use of these methods. Therefore, the main goal of the article is the clustering of the drilling data in the mentioned mine and its zoning of the geochemical data. To achieve this goal, 3500 samples taken from drilling cores have been used. Elemental analysis for six elements has been done using the ICP-Ms method. Pattern recognition methods including SOM and K-MEANS have been used to evaluate the relation between these elements. The silhouette method has been used to determine and evaluate the number of clusters. Using this method, 4 clusters have been considered for the mentioned data. According to this method, it was found that the accuracy of clustering is higher in the SOM method. By considering the 4 clusters, 4 zones were identified using clustering methods. By comparing the results of the two methods and using the graphical method, it was determined that the SOM method has a better performance for clustering geochemical data in the studied area. Based on that, zones 2 and 4 were recognized as high-grade zones in this area.
Rock Mechanics
Mohsen Khanizadeh Bahabadi; Alireza Yarahamdi Bafghi; Mohammad Fatehi Marji; Hossein Shahami; Abolfazl Abdollahipour
Abstract
Complexity of geomaterial’s behavior is beyond the capabilities of conventional numerical methods alone for realistically model rock structures. Coupling of numerical methods can make the numerical modeling more realistic. Discontinuous Deformation Analysis (DDA) and Displacement Discontinuous ...
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Complexity of geomaterial’s behavior is beyond the capabilities of conventional numerical methods alone for realistically model rock structures. Coupling of numerical methods can make the numerical modeling more realistic. Discontinuous Deformation Analysis (DDA) and Displacement Discontinuous Method (DDM) are hybridized for modeling block displacement and crack propagation mechanism in a blocky rock mass. DDA is used to compute the displacements of the blocks, and DDM is used to predict the crack propagation paths due to the specified boundary conditions. The displacements obtained from DDA are converted into stress and considering Kelvin's solution of the problem the crack propagation mechanism within each block is investigated. Boundary stresses are updated due to crack propagation and new stress boundary conditions in DDA. This cycle continued until crack propagation stopped or a new block formed. Numerical solutions of the experimental rock samples including two random cracks with crack 1 fixed and crack 2 created with different angles and one crack with a slope angle of 30 degrees are compared with the existing experimental and numerical results. This comparison validates the accuracy and effectiveness of the proposed procedure because crack propagation paths predicted are in good agreement with the corresponding experimental results of rock samples.
H. Rasouli; K. Shahriar; H. Madani
Abstract
When longwall mining involves total extraction, it includes the overlying strata movements. In order to better control these movements, the height of fracturing (HoF) must be determined. HoF includes both the caved and continuous fractured zones, and represents the region of the broken ground whereby ...
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When longwall mining involves total extraction, it includes the overlying strata movements. In order to better control these movements, the height of fracturing (HoF) must be determined. HoF includes both the caved and continuous fractured zones, and represents the region of the broken ground whereby a hydraulic connection to the mined seam occurs. Among the various empirical models for predicting HoF, the Ditton's geometry and geology models are widely used in the Australian coalfields. This work uses a case-based reasoning (CBR) method in order to predict HoF. The model's variables, including the panel width (W), cover depth (H), mining height (T), key stratum thickness (t), and its distance from the mined seam (y), are selected via the Buckingham's p-theorem. The data set consisting of 31 longwall panels is partitioned into the training and test subsets using the W/H ratio as the primary classifier of a semi-random partitioning method. This partitioning method overcomes the class imbalance and sample representativeness problems. A new CBR model presents a linear mathematical equation to predict HoF. The results obtained show that the presented model has a high coefficient of determination (= 0.99) and a low average error (AE = 8.44 m). The coefficient of determination for the CBR model is higher than that for the Ditton’s geometry (= 0.93) and geology (= 0.97) models. Contrary to the Ditton's models, the performance of the CBR model is consistent regarding the average and standard errors (AE and SE) of the training and test stages. The proposed model has an acceptable performance for all the width to depth ratios to predict HoF.
M.A. Chamanzad; M. Nikkhah
Abstract
Drilling and blasting have numerous applications in the civil and mining engineering. Due to the two major components of rock masses, namely the intact rock matrix and the discontinuities, their behavior is a complicated process to be analyzed. The purpose of this work is to investigate the effects of ...
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Drilling and blasting have numerous applications in the civil and mining engineering. Due to the two major components of rock masses, namely the intact rock matrix and the discontinuities, their behavior is a complicated process to be analyzed. The purpose of this work is to investigate the effects of the geomechanical and geometrical parameters of rock and discontinuities on the rock mass blasting using the UDEC software. To this end, a 2D distinct element code (DEM) code is used to simulate the stress distribution around three blast holes in some points and propagation of the radial cracks caused by blasting. The critical parameters analyzed for this aim include the normal stiffness (JKN) and shear stiffness (JKS), spacing, angle and persistence of joint, shear and bulk modulus, density of rock, and borehole spacing. The results obtained show that the joint parameters and rock modulus have very significant effects, while the rock density has less a effect on the rock mass blasting. Also the stress level has a direct relationship with JKN, JKS, bulk modulus, and the shear modulus has an inverse relationship with the rock density. Moreover, the stress variation in terms of spacing and joint angle indicates sinusoidal and repetitive changes with the place of target point with respect to the blast hole and joint set. Also with a decrease in the JKN and JKS values, the radial cracked and plastic zones around a blast hole show more development. With increase in the joint persistence, the plastic zones decrease around a blast hole.
Elahe Ghaemmaghami; Mohamad Reza Samadzadeh Yazdi; Mohammad Amin Darvishi; Ali akbar Sadati; Abbas Najafi
Abstract
As the mass ratio of alumina to silica (A/S ratio) in bauxite decreases, the cost of alumina production by the Bayer process sharply increases. With the increasingly fierce competition in the alumina industry and the gradual reduction in bauxite grade, when the A/S ratio drops to 3-4, the Bayer process ...
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As the mass ratio of alumina to silica (A/S ratio) in bauxite decreases, the cost of alumina production by the Bayer process sharply increases. With the increasingly fierce competition in the alumina industry and the gradual reduction in bauxite grade, when the A/S ratio drops to 3-4, the Bayer process is challenging to meet the market competition and production requirements. In such cases, the alumina production by sintering method has a vast development prospect and application potential for low-grade bauxite ores. The low A/S ratio and the high iron oxide content are the difficulties in the alumina production by the sintering process. This work adopts the lime-soda sinter process for extracting alumina from bauxite samples (A/S ratio = 1.34 and 20.80% Fe2O3) of the Semirom mine in Iran. The effects of sintering parameters are investigated. The maximum alumina extraction (88%) was obtained by a CaO/SiO2 molar ratio of 1.2, Na2O/Al2O3 molar ratio of 0.9, and sintering temperature at 1250 °C for 80 min. Also 83% of alumina is extracted by decreasing the N/A ratio to 0.66, to decrease the sodium carbonate consumption for a more economical process. The sintered materials are leached with sodium carbonate solution, and aluminum hydroxide [Al(OH)3] is precipitated. Finally, pure alumina (Al2O3) is obtained with a purity of 98 % after calcination at 1200 °C for 2 hours.
Mineral Processing
Nooshin Navi; Mohammad Karamoozian; Mohammad Reza Khani
Abstract
Red mud is an important solid tailing with strong alkalinity that is obtained during the extraction of alumina in the Bayer process. The global reserve of red mud is more than 4 billion tons, and its disposal as tailing has always been a serious environmental problem. This tailing is considered as a ...
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Red mud is an important solid tailing with strong alkalinity that is obtained during the extraction of alumina in the Bayer process. The global reserve of red mud is more than 4 billion tons, and its disposal as tailing has always been a serious environmental problem. This tailing is considered as a potential source, due to its high content of valuable metal compounds including iron. In this research work, the extraction of iron in red mud is investigated by the method of reduction roasting. The main influencing factors are also investigated. These methods include reduction in muffle and tube furnace, and temperature, reduction agent, and additive type are as important factors. Reduction roasting of the samples in a tube furnace, with Argon gas and vacuum, a mixture of red mud, graphite, and sodium carbonate at 700–1000 °C results in the formation of Fe3O4. Magnetic measurements indicate that saturation magnetization increases from 0.239 to 38.205 emu/g due to the formation of Fe3O4. Applying the magnetic field intensity of about 1000 Gauss results in the iron recovery of 89.9%.
Exploitation
Abbas Khajouei Sirjani; Farhang Sereshki; Mohammad Ataei; Mohammad Amiri Hossaini
Abstract
The most significant detrimental consequence of blasting operations is ground vibration. This phenomenon not only causes instability in the mine walls but also extends its destructive effects to various facilities and structures over several kilometers. Various researchers have proposed equations for ...
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The most significant detrimental consequence of blasting operations is ground vibration. This phenomenon not only causes instability in the mine walls but also extends its destructive effects to various facilities and structures over several kilometers. Various researchers have proposed equations for predicting Peak Particle Velocity (PPV), which are typically based on two parameters: the charge per delay and the distance to the blast site. However, according to different studies, the results of blasting operations are influenced by several factors, including the blast pattern, rock mass properties, and the type of explosives used. Since artificial intelligence technology has not yet been fully assessed in the mining industry, this study employs linear and nonlinear statistical models to estimate PPV at Golgohar Iron Ore Mine No. 1. To achieve this goal, 58 sets of blasting data were collected and analyzed, including parameters such as blast hole length, burden thickness, row spacing of the blast holes, stemming length, the number of blast holes, total explosive charge, the seismograph's distance from the blast site, and the PPV recorded by an explosive system using a detonating fuse. In the first stage, ground vibration was predicted using linear and nonlinear multivariate statistical models. In the second stage, to determine the objective function for optimizing the blast design using the shuffled frog-leaping algorithm, the performance of the statistical models was evaluated using R², RMSE, and MAPE indices. The multivariate linear statistical model, with R² = 0.9247, RMSE = 9.235, and MAPE = 12.525, was proposed and used as the objective function. Ultimately, the results showed that the combination of the statistical model technique with the shuffled frog-leaping algorithm could reduce PPV by up to 31%.
Mineral Processing
Alireza Javadi
Abstract
The main and economic mineral of antimony is stibnite or antimony sulfide, and the research and processes in the world are based on it, and oxide minerals are not considered among the economic and important reserves of antimony due to the difficulty of processing and the lack of optimal efficiency of ...
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The main and economic mineral of antimony is stibnite or antimony sulfide, and the research and processes in the world are based on it, and oxide minerals are not considered among the economic and important reserves of antimony due to the difficulty of processing and the lack of optimal efficiency of the flotation method. On the other hand, taking into account that a large part of the antimony reserve of Sefidabeh is made up of low-grade oxidized ore; this research on the method of economic extraction and the possibility of recovering this type of reserve will be important due to the strategic nature of antimony metal. According to the experiments conducted in this research, the effective parameters for flotation include: pH, collector concentration, activator concentration, depressant concentration, activator type, and humic acid concentration. DX7 software was used for statistical modeling of experiments. Based on the above parameters, the design of the experiment was carried out using a partial factorial method and finally the number of 16 experiments was determined for the effect of the above factors on the grade and weight recovery of the sample. Antimony ore flotation with a grade of 4.32% was carried out in a two-stage method. In this method, in the first stage, flotation of antimony sulfur (stibnite, Sb2S3) was performed at a specific pH by adding the activator of copper sulfate or lead nitrate and the depressant together, potassium amyl xanthate collector and MIBC. In the second stage of flotation, the tailings of the first stage of flotation for antimony oxides were treated with a sodium oleate collector (with determined concentrations) at a specific pH by adding copper sulfate or lead nitrate activator, sodium oleate collector and humic acid and MIBC frother agent. The interaction between pH and activator concentration (BD) has a direct effect on the amount of concentrated antimony, with an increase in pH from 6 to 8 antimony when using an activator concentration of 300 g/t, and a decrease when using an activator concentration of 500 g/t. Flotation was done. In the best conditions, with two-stage flotation of antimony, 68.99% recovery and 13.32 grade were obtained.
Rock Mechanics
Farhad Mollaei; Ali Moradzadeh; Reza Mohebian
Abstract
The important aspects of this study are to estimate the mechanical parameters of reservoir rock including Uniaxial Compressive Strength (UCS) and friction (FR) angle using well log data. The aim of this research is to estimate the UCS and FR angle (φ) using new deep learning (DL) methods including ...
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The important aspects of this study are to estimate the mechanical parameters of reservoir rock including Uniaxial Compressive Strength (UCS) and friction (FR) angle using well log data. The aim of this research is to estimate the UCS and FR angle (φ) using new deep learning (DL) methods including Multi-Layer Perceptron (MLP), Long Short-Term Memory (LSTM), Convolutional Neural Network (CNN), and CNN + LSTM (CL) by well log and core test data of one Iranian hydrocarbon field. As only 12 UCS and 6 FR core tests of single well in this field were available, they were firstly calculated, and then generalized to other depths using two newly derived equations and relevant logs. Next, the effective input logs' data for predicting these parameters have been selected by an auto-encoder DL method, and finally, the values of UCS and φ angle were predicted by the MLP, LSTM, CNN, and CL networks. The efficiency of these four prediction models was then evaluated using a blind dataset, and a range of statistical measures applied to training, testing, and blind datasets. Results show that all four models achieve satisfactory prediction accuracy. However, the CL model outperformed the others, yielding the lowest RMSE of 1.0052 and the highest R² of 0.9983 for UCS prediction, along with an RMSE of 0.0201 and R² of 0.9917 for φ angle prediction on the blind dataset. These findings highlight the high accuracy of deep learning algorithms, particularly the CL algorithm, which demonstrates superior precision compared to the MLP method.
Mineral Processing
Dorna Pirouzan; Reza Parvareh; Ziaeddin Pourkarimi; Mehdi Rahimi; Javad Moosavi; Hossein Habibi
Abstract
In our country, a massive volume of slag is generated annually from steel production facilities, amounting to about 20 percent of the total steel produced. This slag is an important and valuable source for extracting vanadium, with 67 percent of the world's vanadium production sourced from slag. Iran ...
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In our country, a massive volume of slag is generated annually from steel production facilities, amounting to about 20 percent of the total steel produced. This slag is an important and valuable source for extracting vanadium, with 67 percent of the world's vanadium production sourced from slag. Iran ranks among the top five countries that possess this vital metal; however, vanadium extraction from slag has not been carried out to date. Moreover, due to the unstable quality of the slag, its utilization in other industries has not been feasible. To prevent the environmentally harmful effects of accumulating slag and the inability to utilize it in various industries, it is essential to implement an economic solution for recovering the components present in steel-making slag. In the present project, after sampling from the stored slag deposits at Mobarakeh Steel Company, comprehensive laboratory and pilot-scale studies were conducted on the representative samples. Through processes involving roasting with sodium carbonate, acid leaching with 2 M sulfuric acid, iron cementation, solvent extraction using DEHPA, stripping, and scrubbing, we successfully extracted pentoxide vanadium with high purity suitable for producing ferrovanadium.
Exploitation
Alireza Afradi; Arash Ebrahimabadi
Abstract
Rock-fragmentation is generally regarded as a crucial indicator within the mining industry for evaluating the effects of blasting operations. In this work, a database was primarily constructed using field data to predict rock fragmentation in the mines of Anguran and Sarcheshmeh. The datasets comprised ...
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Rock-fragmentation is generally regarded as a crucial indicator within the mining industry for evaluating the effects of blasting operations. In this work, a database was primarily constructed using field data to predict rock fragmentation in the mines of Anguran and Sarcheshmeh. The datasets comprised the input parameters such as Burden (m), spacing (m), powder factor (kg/m³), and stemming (m), with fragmentation (cm) as the output parameter. The analysis of these datasets was conducted using the Ant Lion Optimizer (ALO) and Crow Search Algorithm (CSA) methodologies. To assess the predictive models' accuracy, metrics including the coefficient of determination (R²), Variance Accounted For (VAF), and Root Mean Square Error (RMSE) were employed. The application of ALO and CSA to the database yielded results indicating that for ALO, R² = 0.99, RMSE = 0.005, and VAF (%) = 99.38, while for CSA, R² = 0.98, RMSE = 0.02, and VAF (%) = 98.11. Ultimately, the findings suggest that the predictive models yield satisfactory results, with ALO demonstrating a greater level of precision.
Negar Saeidi; Dariush Azizi; Mohammad Noaparast; Soheila Aslani; R Ramadi
Abstract
In this paper, iron ore sample from the Chadormalu was investigated to determine some comminution properties. Chadormalu deposit is one of the largest iron ore mine in Iran, which is located in Yazd province. The representative ore sample contained 57%Fe, 0.9%P and 0.17%S. The sample was crushed; afterward, ...
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In this paper, iron ore sample from the Chadormalu was investigated to determine some comminution properties. Chadormalu deposit is one of the largest iron ore mine in Iran, which is located in Yazd province. The representative ore sample contained 57%Fe, 0.9%P and 0.17%S. The sample was crushed; afterward, it was ground in various grinding times according to the Bond Ball mill approach to specify the work index values. Based on different grinding times and the obtained results, a new work index equation was then simulated through which grinding time was considered as the main variable. The relationships between work index, the work input and P80 were then concluded. In addition, the results of tests were then used to estimate the selection function parameter. A new equation was applied to determine energy efficiency which could be implemented for energy consumption calculation. Two equations for EB and EB/Elimit were then obtained, where EB is the efficiency of comminution, and the ELimit is the maximum limiting energy efficiency for particle fracture under compressive loading. These equations could estimate the parameters of the iron ore would be precisely estimated. Indeed, by means of work index value; some crushing and grinding characteristics of the taken sample were assessed by which comminution circuit would be designed much better.
Environment
B. Shokouh Saljoughi; A. Hezarkhani; E. Farahbakhsh
Abstract
The most significant aspect of a geochemical exploration program is to define and separate the anomalous values from the background. In the past decades, geochemical anomalies have been identified by means of various methods. Most of the conventional statistical methods aiming at defining the geochemical ...
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The most significant aspect of a geochemical exploration program is to define and separate the anomalous values from the background. In the past decades, geochemical anomalies have been identified by means of various methods. Most of the conventional statistical methods aiming at defining the geochemical concentration thresholds for separating anomalies from the background have limited the efficiency in the areas with complex geological settings. In this work, three methods including the Concentration-Area (C-A) and Spectrum-Area (S-A) fractal models, and the U-statistic method are applied to identify the geochemical anomalies in Avanj porphyry system due to a complex geological and tectonic setting. The results obtained show that the S-A and U-statistic methods present more acceptable outputs than the C-A method. The C-A model acts well to identify the geochemical anomalies within a region including a simple geochemical background; however, the model has limitations within a region including a complex geological setting, where each sub-area is characterized by different geochemical fields. The U-statistic method, by considering the location of sampling points, their spatial relation, and radius of influence for each point in the estimation of anomaly location, overcomes the limitations of the C-A model. The S-A model is a powerful tool to decompose mixed geochemical patterns into a geochemical anomaly map and a varied geochemical background map. The output of this method shows the analysis of geochemical data in the frequency domain, which can provide new exploratory information that may not be revealed in the spatial domain. Eventually, it can be pointed out that the accuracy of the S-A fractal model for determining the thresholds is higher than the other two methods mentioned.
A. Agah; N. Falahati
Abstract
In this research work, the potential capability of nano-clay and tonsil, as low-cost and domestic adsorbents, for the elimination of a cationic dye, (CR18) from contaminated water is investigated. The surface properties of the adsorbents are studied by means of the scanning electron microscopy (SEM) ...
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In this research work, the potential capability of nano-clay and tonsil, as low-cost and domestic adsorbents, for the elimination of a cationic dye, (CR18) from contaminated water is investigated. The surface properties of the adsorbents are studied by means of the scanning electron microscopy (SEM) and X-ray diffraction techniques. The effects of the initial dye concentration, pH, stirring speed, contact time, and adsorbent dosage are investigated at 25 . The results obtained show that the dye adsorption data from the nano-clay and tonsil experiments fit well to the Langmuir and Freundlich isotherms, respectively. The results of dye adsorption kinetics demonstrate that the adsorption system follows a pseudo-second-order model with a satisfactory correlation value (R=99%).The adsorption thermodynamics is also studied, concluding that the adsorption process is spontaneous and physically controlled. Under the optimum conditions (pH of 7, stirring speed of 200 rpm, CR18 concentration of 30 ppm and contact time of 30 min), the adsorption capacities of the mixed adsorbents show the maximum adsorption efficiency at the tonsil:nano-clay weight ratio of 1:2.
Rock Mechanics
R. Shafiei Ganjeh; H. Memarian; M. H. Khosravi; M. Mojarab
Abstract
Dynamic slope stability in open-pit mines still remains a challenging task in the computational mining design. Earthquake and blasting are two significant sources of dynamic loads that can cause many damages to open-pit mines in active seismic areas and during exploitation cycles. In this work, the effects ...
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Dynamic slope stability in open-pit mines still remains a challenging task in the computational mining design. Earthquake and blasting are two significant sources of dynamic loads that can cause many damages to open-pit mines in active seismic areas and during exploitation cycles. In this work, the effects of earthquake and blasting on the stability of the NW slope of Chadormalu mine are compared by a numerical modeling method. The dynamic results show that the maximum displacement under earthquake and blasting loads within the slope are 844 mm and 146 mm, respectively. According to the shear strain results, both the earthquake and blasting waveforms are destructive, while the earthquake waveforms cause more damages to the slope. Moreover, the deterministic and probabilistic seismic hazard analyses are carried out to assess the seismicity of the mine area. The experimental results indicate that the maximum values for the vertical and horizontal accelerations are 0.55 g and 0.75 g, respectively. The maximum calculated acceleration is then scaled to the selected earthquake accelerograms. In order to show the effective impact of the established scale, the model is executed using the original accelerograms. The results obtained show that the established scale prevents overestimation and underestimation of the displacement and strain. Therefore, applying scaled accelerograms in a dynamic slope stability analysis in mine slopes leads to more reliable and robust results. The overall results show that a strong earthquake causes plenty of damages to the slope, and consequently, interrupts the mining cycle. Hence, the seismic study and dynamic slope stability should be considered as a part of the computational mining design.
Exploitation
M. Hosseini; H. Madani; K. Shahriar
Abstract
The main purpose of this work is modeling the dispersion of the sarin gas in a subway station in a hypothetical scenario. The dispersion is modeled using the CFD approach. In the analysis of the environmental conditions of the underground spaces, the only factor that draws a distinction between a subway ...
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The main purpose of this work is modeling the dispersion of the sarin gas in a subway station in a hypothetical scenario. The dispersion is modeled using the CFD approach. In the analysis of the environmental conditions of the underground spaces, the only factor that draws a distinction between a subway station and other spaces is the train piston effect. Therefore, the present research work models the sarin dispersion in the two general cases of with and without a train in the subway system. About 0.5 L of sarin is assumed to be released through the main air handling unit (AHU) of the station. The results obtained show that in the case with no train service in the station, after 20 minutes of sarin release, the concentration and dose of sarin in the station will be 8.9 mg/m3 and 80 mg minute/m3, respectively, and these values are highly dangerous and lethal, and would have severely adverse effects on many individuals, and lead to death. This is highly important, especially when the effect of ventilation chambers at the ground level is taken into consideration. The results obtained also show that the train piston effect reduces the concentration and dose of sarin in the station so that when train arrival at and departure from the station, the sarin dose considerably reduces to 25 mg min/m3 after the release, and contributes to lower casualties. Finally, the results obtained show that time is a key factor to save lives in the management of such incidents.
Rock Mechanics
H. Sarfaraz; M. Amini
Abstract
One of the most important instabilities of rock slopes is toppling failure. Among the types of toppling failure, block-flexural failures are more common instability which occurs in nature. In this failure, some rock blocks break because of tensile stresses, and some overturn under their weights, and ...
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One of the most important instabilities of rock slopes is toppling failure. Among the types of toppling failure, block-flexural failures are more common instability which occurs in nature. In this failure, some rock blocks break because of tensile stresses, and some overturn under their weights, and next to all of them topple together. Physical and theoretical modeling of this failure is studied by Amini et al. in 2015. Due to the complexity of this failure mechanism, no appropriate numerical model has been proposed so far. In this research, first, a literature review of toppling failure is summarized. Then, using UDEC software as distinct element method (DEM), the experimental models were analyzed numerically, and Voronoi joint model was applied to simulate the failure. The results of numerical simulations are compared with the outcomes of physical models and analytical solution. The comparison illustrates that numerical modeling has good agreement with corresponding experimental tests and theoretical approach. Also, the results show that although the mechanism of block-flexural toppling failure is complicated, the numerical code is well capable to analyze of this failure.
Enayatallah Emami Meybodi; Syed Khaliq Hussain; Mohammad Fatehi Marji
Abstract
In this research work, X-ray diffraction (XRD) tests and petrographic studies are performed to analyze the mineral composition and lamination in the shale rock specimens. Afterward, point load (PL) and uniaxial compressive strength (UCS) tests are carried out on the anisotropic laminated shale rock. ...
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In this research work, X-ray diffraction (XRD) tests and petrographic studies are performed to analyze the mineral composition and lamination in the shale rock specimens. Afterward, point load (PL) and uniaxial compressive strength (UCS) tests are carried out on the anisotropic laminated shale rock. Based on the macro-mechanical properties of these tests, the discrete element method implemented in a two-dimensional particle flow code (PFC2D) is adjusted to numerically simulate the shale rock specimens. The aim of this work is to validate the numerical models by failure process, stress-strain curves, and peak failure strengths of the shale samples. Therefore, point load test is used for assessing the pattern failure mechanism, and uniaxial compressive strength test is performed for obtaining the stress-strain curves and peak strength failure points in the laboratory shale rock samples. Validation of peak strengths criteria provides the best results; the determination coefficient values for lab and numerical modeling with (R2 = 0.99). Several numerical models are prepared for estimating the mechanical behavior of shale rocks in PFC2D. The smooth joint model (SJM) is used for preparing the consistent and appropriate constitutive models for simulating the mechanical behavior of laminated shale. It is concluded that SJM provides more reasonable results for laminated shale rock that can be used for several petroleum engineering projects, especially in the central geological zone of Iran.
Exploration
Moslem Jahantigh; Hamid Reza Ramazi
Abstract
Fuzzy c-means (FCM) is an unsupervised machine learning algorithm. This method assists in integrating airborne geophysics data and extracting automatic geological map. This paper tries to combine airborne geophysics data consisting of aeromagnetic, potassium, and thorium layers to classify the lithological ...
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Fuzzy c-means (FCM) is an unsupervised machine learning algorithm. This method assists in integrating airborne geophysics data and extracting automatic geological map. This paper tries to combine airborne geophysics data consisting of aeromagnetic, potassium, and thorium layers to classify the lithological map of the Shahr-e-Babak area, a world-class porphyry area in the south of Iran. The resulting clusters with FCM show appropriate coincidence with the geological map of the study area. The clusters are adapted with high magnetic anomalies corresponding to the mafic volcanic rocks and the clusters with high radiometric signature associated with igneous rocks. The cluster is associated with low magnetic anomaly and low radioelements concentration representing sedimentary rocks. some clusters are associated with two or more lithological formations due to similar signatures of geophysics properties. The fuzzy score membership in all clusters is above 0.71 indicating a high correlation between geological signatures and multigeophysical data. This study shows geophysical signatures analyzed with the machine learning method can reveal geological units.
Rock Mechanics
Taha Ansari; Hamid Chakeri; Mohammad Darbor; sadegh Amoun; Hadi Shakeri
Abstract
There is no acceptable method for investigating the tool wear phenomenon in soft grounds. In this article, first, a new equipment made at Sahand University of Technology is introduced, which is used for simulation of TBM tunneling mechanism. Next, the effect of various soil grading parameters such as ...
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There is no acceptable method for investigating the tool wear phenomenon in soft grounds. In this article, first, a new equipment made at Sahand University of Technology is introduced, which is used for simulation of TBM tunneling mechanism. Next, the effect of various soil grading parameters such as D10, D30, and D60 (which indicate the corresponding diameters on the soil grading diagram where 10, 30, and 60% of the grains are smaller than these values, respectively), coefficient of gradation, uniformity coefficient, sorting coefficient and effective size on the cutting tools wear. The initial studies show that in soils with fine grains greater than 10%, by increase in the values of D10, D30, D60, and effective size, the tool wear increases. However, in soils with fine grains less than 10%, by increase in the above-mentioned parameters, the soil abrasiveness reduces. Also in soils with more than 10% fine grains, by increase in the coefficient of gradation value, the soil abrasiveness reduces. But in soils with fine grains less than 10%, by increase in the value of this parameter, the tool wear increases. The results of experiments show that sorting coefficient could be a good criterion for investigating the soil abrasiveness.
Exploitation
Masoud Monjezi; Morteza Baghestani; Peyman Afzal; Ali Reza Yarahmadi Bafghi
Abstract
Blasting is an essential operation in mining projects, significantly affecting the particle-size distribution, which is critical for subsequent processes such as loading, hauling, and milling. Effectiveness of the blasting operations rely on accurate rock characterization, especially when dealing with ...
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Blasting is an essential operation in mining projects, significantly affecting the particle-size distribution, which is critical for subsequent processes such as loading, hauling, and milling. Effectiveness of the blasting operations rely on accurate rock characterization, especially when dealing with different rock types. Proper rock and fragmentation characterization allows for tailored blast designs and also can lead to precise predictions of fragmentation quality. Various characterization techniques exist. This paper examines the application of fractal analysis to classify fragmentation quality and rock types, utilizing the Choghart iron mine in Iran as a case study. Extensive fieldwork collected data on rock properties (uniaxial compressive strength and density) and fragmentation outcomes during blasting. The fractal modeling revealed distinct breakpoints for classification, followed by Logratio analysis to assess relationships among the identified classes. Finally, mathematical models were established to predict fragmentation features based on the relevant rock attributes. The models demonstrated improved predictive accuracy as compared to the prior classifications.
M Mohammadiun; B. Dahrazma; Seyed F. Saghravani; A. Khodadadi Darban
Abstract
Use of nanotechnology has proven to be a promising approach toward remediation of all phases of environment. The aim of this work is to investigate the effects of different parameters on using iron III oxide nanoparticles in a continuous flow configuration for the removal of Cd2+ ionsfrom contaminated ...
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Use of nanotechnology has proven to be a promising approach toward remediation of all phases of environment. The aim of this work is to investigate the effects of different parameters on using iron III oxide nanoparticles in a continuous flow configuration for the removal of Cd2+ ionsfrom contaminated soils. Also selective sequential extraction tests are carried out to evaluate the nanoparticle tendency to remove cadmium from different fractions of soils. In order to achieve this goal, a specific flow rate of a nanoparticle solution was passed through a soil sample in a column with 3 cm diameter and 4 cm height. Up to 100% of cadmium removal was achieved by providing a nano-fluid concentration of 500 ppm, pH of 6.5, treatment duration of 24 hours, and flow rate of 0.5 mL/min. Evaluation of the results obtained showed that the tendency of the iron oxide nanoparticles to remove cadmium from different fractions of contaminated soil was in the order of exchangeable > carbonates > oxides and hydroxides > organic matter > residual. The results obtained from this work can be used to develop an appropriate remediation protocol for contaminated soils.
F. Sharifi; A.R. Arab Amiri; A. Kamkar Rouhani
Abstract
The generalized effective-medium theory of induced polarization (GEMTIP) is a newly developed relaxation model that incorporates the petro-physical and structural characteristics of polarizable rocks in the grain/porous scale to model their complex resistivity/conductivity spectra. The inversion of the ...
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The generalized effective-medium theory of induced polarization (GEMTIP) is a newly developed relaxation model that incorporates the petro-physical and structural characteristics of polarizable rocks in the grain/porous scale to model their complex resistivity/conductivity spectra. The inversion of the GEMTIP relaxation model parameter from spectral-induced polarization data is a challenging issue because of the highly non-linear dependency of the observed data on the model parameter and non-uniqueness of the problem. To solve these problems as well as scape the local minima of the highly complicated cost function, the genetic algorithm (GA) can be applied but it has proven to be time-intensive computationally. However, this drawback can be resolved by incorporating a faster algorithm, e.g. particle swarm optimization (PSO). The aim of this work is to investigate whether recovering the model parameter of the ellipsoidal GEMTIP model from SIP data using the combined GA and PSO algorithms is possible. To achieve this aim, we set the best calculated individuals using GA as the search space of PSO, and then the best location achieved by PSO in each iteration is assigned as the updated model parameters. The results of our research work reveal that the model parameters can effectively be recovered using the approach proposed in this paper but the time constant of a noisy data that arises from the adverse dependency of this parameter on the ellipticity of a polarizable grain. Moreover, the execution time of the ellipsoidal GEMTIP modeling of complex resistivity data can be significantly improved using the proposed algorithm.
H. Ebadi; P. Pourghahramani; B. Nemati akhgar
Abstract
Structural changes of mechanically-activated ilmenite during milling by a planetary mill are monitored and determined as a function of the milling time. The maximum specific BET surface area of 10.76 m2/g is obtained after 150 min of milling. The results obtained indicate that agglomeration of the particles ...
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Structural changes of mechanically-activated ilmenite during milling by a planetary mill are monitored and determined as a function of the milling time. The maximum specific BET surface area of 10.76 m2/g is obtained after 150 min of milling. The results obtained indicate that agglomeration of the particles occurs after 45 min of milling. The maximum X-ray amorphization degree of ca. 95% has been calculated after 150 min of milling. Estimation of the stored energy reveals that the X-ray amorphization degree has a dominant contribution to the excess enthalpy of the activated materials. The surface-weighted crystallite size in the ground ilmenite reaches 4.45 nm, which corresponds to the volume-weighted crystallite size of 8 nm and 11.18 nm obtained by the Williamson-Hall and Rietveld methods, respectively. After 150 min of mechanical activation, the root mean square strain, , increases to 0.78%, which corresponds to the strains of 1.43% and 1.04% obtained from the Williamson-Hall and Rietveld methods, respectively. Reduction in the crystallite size leads to the contraction of the ilmenite unit cell after 150 min. The reaction rate constant of the ilmenite dissolution increases by over 58 times after 150 min of milling. Activation energy of the dissolution reaction decreases from 57.45 kJ/mol to 41.09 kJ/mol after 150 min of milling.
