Journal of Mining and Environment
https://jme.shahroodut.ac.ir/
Journal of Mining and Environmentendaily1Fri, 01 Apr 2022 00:00:00 +0430Fri, 01 Apr 2022 00:00:00 +0430Ore Deposit Boundary Modification in Afghanistan Aynak Central Copper Deposit using Sequential Indicator Simulation and Indicator Kriging
https://jme.shahroodut.ac.ir/article_2400.html
The Aynak copper deposit is the most important strata-bound copper reserve in Afghanistan. The main purpose of this work is the ore deposit boundary modification and reserve estimation of the Aynak central copper deposit using the geostatistical methods. The ordinary kiging (OK), indicator kriging (IK) and sequential indicator simulation (SIS) methods were used to modify the optimum ore deposit boundary and ore reserve estimation. Then the results, accuracy and efficiency of these three methods are compared. Before the ore reserve estimation, the pre-processing, &nbsp;statistical and geostatistical analysis of the sampled data are performed. For a precise estimation process, it is necessary to modify the optimum ore body boundary as an estimation space. Therefore, the IK and SIS methods are applied to revise the conventional ore deposit boundary and estimation space. At the first stage, the ore body wireframe and solid model are obtained using the conventional cross-section method. The block model is created covering the mineralization space of the ore body, and firstly constrained by the conventional model (solid model). Consequently, the ore body model is adapted and bounded using the IK and SIS geostatistical methods. Finally, the log-kriging method that is basically unbiased and guarantees the minimum estimation error is used to estimate the Cu concentration in each block, and after back-transformation, the grade-tonnage curves are plotted. The total tonnage of the deposit is calculated based on different cut-off grades. Assuming the cut-off grade of 0.2% for Cu, the tonnage of ore reserve based on the conventional OK method, IK method, and SIS constrained ore body model are estimated as 453.4, 459.1, and 467.7 million tons with an average grade of 1.077%, 1.08%, and 1.05%, respectively. The proximity of the obtained reserve estimation results using different implemented methodologies is due to the low-grade variability and genetical regularity in the Aynak staratabound copper deposit and guarantees the accuracy of the results obtained in the ore reserve evaluation.Improvement of small-scale dolomite blasting productivity: Comparison of existing empirical models with image analysis software and artificial neural network models
https://jme.shahroodut.ac.ir/article_2507.html
Assessment of blast results is a significant approach for the improvement of mining operations. The different procedures for investigating rock fragmentation have their limitations, causing different variation prediction errors. Thus every technique is site-explicit, and applicable for a few explicit purposes. This work evaluates the existing empirical blast fragmentation model predictions in the case study of small-scale dolomite quarries. An attempt is made to compare the prediction accuracy of the modified Kuz-Ram model, Lawal 2021 model, and Kuznetsov-Cunningham-Ouchterlony (KCO) model with the WipFrag&copy; analysis result and proposed artificial neural network (ANN) models. The prediction error analysis of the current models and that of the new proposed ANN models is evaluated using the three model assessment indices. The assessment indices uncover that the KCO model when compared to the modified Kuz-Ram model has the least error for most blast round percentage passing size predicted. However, the proposed artificial neural network models show high prediction exactness in predicting blast fragment mean size than the existing empirical models. Therefore, the proposed ANN models can be used to improve the productivity of small-scale dolomite blasting operation results for practical purposes.Evaluating Microscale Failure Response of Various Weathering Grade Sandstones Based on Micro-Scale Observation and Micro-Structural Modelling Subjected to Wet and Dry Cycles
https://jme.shahroodut.ac.ir/article_2447.html
The significance of rock failure can be found from the fact that microfracture genesis and coalescence in the rock mass results in macroscale fractures. Rock may fail due to an increase in the local stress, natural fractures, weathering inducing micro-crack genesis, coalescence, and propagation. Therefore, a comprehensive understanding of the micro-scale failure mechanism of various weathering grade sandstones based on micro-level observation and microstructure-based simulation is essential. The microscale failure response of various weathering grade sandstones is studied under the wet and dry cycles. Each sample is tested for the micro-structure and micro-fracture characteristics using the image analysis. Furthermore, the micrographs obtained are also used to create the microstructure-based models, which are then simulated in the ANSYS software. The findings indicate that the moderately weathered sandstones indicate less weight reduction than the slightly weathered sandstone. The results obtained also demonstrate that the wet and dry cycles have little effect on the particle shape and size. However, variation in the particle shape and size implies that this is a result of the prevailing interaction of rock and water particle. The microscale simulation reveal that both UCS and BTS decrease from 37 MPa to 19 MPa and 9 MPa to 4 MPa as the density of the micro-structure increases. The results reveal that the primary fracture deviation from the loading axis increases with increasing density in the micro-structural micro-structures, although this effect reduces with further increasing density in the micro-structures.Real-scale numerical analyzing the dynamic process of the TBM boring in the jointed rock, a case study
https://jme.shahroodut.ac.ir/article_2509.html
One of the important cost items in mechanized tunneling is the cost of repairing or replacing the disc cutters that have suffered from normal wear during the boring of the hard abrasive rocks. For inspecting the health of the disc cutters, the boring operation shall be stopped, and after checking, the worn disc cutters may be replaced. In this work, the dynamic process of the TBM boring in the jointed rocks is simulated using a real-scale numerical analysis based on the rock fracturing factor using the discrete element method (DEM). The stress distributions induced within the disc cutters as well as the development of the plastic zones in the rock are investigated and compared with the actual results recorded in the Kerman water conveyance tunnel (KWCT). The numerical results indicate that the increase in the rock fracturing causes a decrease in the induced stresses and an increase in the size of the plastic zone. In other words, a higher penetration rate as well as more lifetime for disc cutters can be achieved in highly fractured rocks. Moreover, the average von Misses stress in the disc cutters in the highly fractured rocks is predicted about 16-23% less than stress induced in the slightly fractured rocks. Due to the TBM tunneling, the volume of the plastic zone as well as the actual penetration depth in the highly fracturing rocks are also about 40% and 42% higher than in the slightly fractured rocks under applying the same TBM parameters, respectively.Suitable Mining Method Selection using HFGDM-TOPSIS Method: a Case Study of an Apatite Mine
https://jme.shahroodut.ac.ir/article_2456.html
Mining Method Selection (MMS) is the first and the most critical problem in mine design, and depends on some parameters such as the geo-technical and geological features and economic factors. The factors affecting MMS are determined by some mining experts, and the most suitable mining method is selected using the hesitant fuzzy group decision-making (HFGDM) and technique for order performance by similarity to the ideal solution (TOPSIS) method. These factors include the type of deposit, slope of deposit, thickness of orebody, depth below the surface, grade distribution, hanging wall Rock Mass Rating (RMR), footwall RMR, ore body RMR, recovery, capital cost, mining cost, annual productivity, and environmental impact. Firstly, we propose the group decision-making (GDM) method to determine the weights of multi-attributes based on the score function with the decision-makers&rsquo; weights, in which the n-dimensional hesitant fuzzy environment take the form of hesitant fuzzy sets (HFS). Then we calculate the weights of these factors using the HFGDM method. A simple case study is also presented in order to illustrate the competence of this method. Here, we compare the seven mining methods for an Apatite mine, and select the optimal mining method using the TOPSIS method. Finally, the sub-level stope mining method is selected as the most suitable method to this mine.Slope stability analysis and preventive actions for a landslide location along NH-05 in Himachal Pradesh, India.
https://jme.shahroodut.ac.ir/article_2500.html
The Himalayan mountain range is susceptible to slope instability in numerous areas due to its complicated topography, because of the existing natural conditions and human influence and intervenes. National Highway-05 is considered in this work. The area under investigation located in Rampur, district Shimla, Himachal Pradesh is evaluated for slope stability. The primary purpose of this work is to maintain the slope's stability in order to protect NH-05 and the neighboring three-sided residential structures. Following the site visit, the geotechnical investigations in the form of bore holes and laboratory tests are conducted. Analysis of slope stability is commenced after interpreting the geotechnical study report. For an analytic slope stability, the studied area is divided into three sections, labelled A1-A1', B1-B1', and C1-C1'. Taking into account the geotechnical aspects of the specified research region, the mitigation design parameters for the area and the circular slip failure are calculated using the numerical modeling techniques. The software computes the safety factor for both the static and dynamic situations. As a result, preventative measures and a few improvements are suggested.Developing New Models for Flyrock Distance Assessment in Open-Pit Mines
https://jme.shahroodut.ac.ir/article_2405.html
In this research work, a comprehensive study is conducted to predict flyrock as a typical and undesirable phenomenon occurring during the blasting operation in open-pit mining. Despite the availability of several empirical methods for predicting the flyrock distance, the complexity of flyrock analysis has resulted in the low performance of these models. Therefore, the statistical and robust artificial intelligence techniques are applied for flyrock prediction in the Sungun copper mine in Iran. For this purpose, the linear multivariate regression (LMR), imperialist competitive algorithm (ICA), adaptive neuro-fuzzy inference system (ANFIS), and artificial neural network (ANN) methods are applied to predict flyrock with effective parameters including the blasthole diameter, stemming, burden, powder factor, and maximum charge per delay. According to the attained results, the ANN model with the structure of 5-8-1, Levenberg-Marquardt as the learning algorithm, and log-sigmoid (logsig) as the transfer functions are selected as the optimal network with the RMSE and R2 values of 5.04 m and 95.6% to predict flyrock, respectively. Also it can be concluded that the ICA technique has a relatively high capability in predicting flyrock, with the LMR and ANFIS models placed in the next. Finally, the sensitivity analysis reveal that the powder factor and blasthole diameters have the most importance on the flyrock distance in the present work.Comparison of Efficiencies of Neutralizing Agents for Heavy Metals Removal from AMD
https://jme.shahroodut.ac.ir/article_2519.html
The treatment of acid mine drainages is usually based on two basic technologies, active and passive treatment technologies. Whichever acid mine drainage (AMD) treatment method is employed, a neutralizing procedure that raises the water's pH over 7.0 using alkaline agents is required prior to discharge. A comparison of eight different agents (BaCO3, Na2CO3, NaOH, KOH, K2CO3, MgO, CaCO3, and Ba(OH)2) was performed in order to choose the most effective neutralizing agent for acid mine drainage treatment. The experiments were performed using a multi-component synthetic aqueous solution with an initial concentration of 10 mg/L of the Cu, Mn, Zn, Fe, and Pb ions and an initial pH value of 1.9. According to the research, the most effective neutralizing agent for the removal of heavy metals from a multi-component aqueous solution is MgO, while the least effective agent was Na2CO3. The obtained series of effective neutralizing agents for the removal of heavy metals from a multi-component aqueous solution are presented in the work. The effect of the studied concentration of neutralizing agents depends on the neutralizing agents and heavy metals that are used. The percentage of heavy metals removed from aqueous solutions increases along with rising pH values. The consumption of the neutralizing agent decreases as the concentration of the neutralizing agent is increased. In addition, the time taken to achieve pH depends on the agent concentration. In particular, as the concentration of the neutralizing agent increases, the time to reach the pH decreases.Prediction of Fly-rock using Gene Expression Programming and Teaching–learning-based Optimization Algorithm
https://jme.shahroodut.ac.ir/article_2445.html
This paper attempted to estimate the amount of flyrock in the Angoran mine in Zanjan province, Iran using the gene expression programming (GEP) predictive technique. The input data, including flyrock, mean depth of the hole, powder factor, stemming, explosive weight, number of holes, and booster were collected from the mine. Then, using GEP, a series of intelligent equations were proposed to predict flyrock distance. The best GEP equation was selected based on some well-established statistical indices in the next stage. The coefficient of determination for training and testing datasets of the GEP equation were 0.890 and 0.798, respectively. The model obtained from the GEP method was then optimized using teaching&ndash; learning-based optimization algorithm (TLBO). Based on the results, the correlation coefficient of training and testing data increased to 91% and 89%, which increased the accuracy of the Equation. This new intelligent equation could forecast flyrock resulting from mine blasting with a high level of accuracy. The capabilities of this intelligent technique could be further extended to the other blasting environmental issues.An Experimental-intelligent Method to Predict the Noise Value of Drilling in Dimension Stone Industry
https://jme.shahroodut.ac.ir/article_2517.html
The noise of drilling in the dimension stone business is unbearable for both the workplace and the people who work there. In order to reduce the negative effects drilling has on the health of the environment, the drilling noise has to be measured, assessed, and controlled. The main purpose of this work is to investigate an experimental-intelligent method to predict the noise value of drilling in the dimension stone industry. For this purpose,135 laboratory tests are designed on five types of rocks (four types of hard rock and one type of soft rock), and their results are measured in the first step. In the second step, due to the unpredicted and uncertain issues in this case, artificial intelligence (AI) approaches are applied, and the modeling is conducted using three intelligent systems (IS), namely an adaptive neuro-fuzzy inference system-SCM (ANFIS-SCM), an adaptive neuro-fuzzy inference system-FCM (ANFIS-FCM), and the radial basis function network (RBF) neural network. 75% of the samples are considered for training, and the rest for testing. Several models are constructed, and the results indicate that although there is no significant difference between the models according to the performance indices, the proposed construction of ANFIS-SCM can be considered as an efficient tool in the evaluation of drilling noise. Finally, several scenarios are designed with different input modes, and the results obtained prove that the types of rock and the drill bits are more important than the operational characteristics of the machine.Interaction between One Internal Hole and Two Neighboring Joints under Uniaxial Compression using an Experimental Test and a Numerical Simulation
https://jme.shahroodut.ac.ir/article_2222.html
The interaction between an internal hole and two surrounded joints under a uniaxial compression are examined using the experimental and discrete element procedures. Inside the concrete sample, two notches and an internal hole are created. The joint angle change from 0&deg; to 90&deg; with an increment of 30&deg;. The distances between the joint and the internal hole are 2 cm and 3 cm. Also the numerical models are provided. The joint angle change from &nbsp;0&deg; to 90&deg; with an increment of 15&deg;. The distances between the joint and the internal hole are 2 cm, 3 cm, and 4 cm. The compressive strength is 7.2 MPa. The rate of loading is 0.005 mm/s. The experiment indicates that the failure process is significantly dependent on the notch angle and the joint distance from the hole. The pattern of fracture and mechanism of failure of joints affect the shear strengths of the samples. The models with joint angles of 30&deg; and 60&deg; have a less compressive strength since the pure tensile failure occurs in these configurations. The model strength decreases with decrease in the join spacing. In fact, in the case that the joint spacing is 2 cm, the interaction between the hole and the neighboring joint is so strong. Consequently, the compressive strength is declined. In both approaches of the numerical simulation and experimental methods, the pattern and strength of failure are identical.Risk Assessment in Quarries using Failure Modes and Effects Analysis Method (Case study: West-Azerbaijan Mines)
https://jme.shahroodut.ac.ir/article_2511.html
Iran is one of the countries with the largest number of quarry mines in the world. Diamond cutting wire is usually used in quarries to cut dimension stone cubes, which is accompanied by hazardous events. Therefore, detecting and investigating the possible quarry risks is crucial to have a safe and sustainable mining operation. In mine exploitation, maintaining the safety of vehicles and increasing the knowledge of personnel regarding safety issues can considerably mitigate the number or radius of effect of hazards. Hence, the incidents and risks in the West-Azerbaijan quarries in Iran are investigated in this work. To do so, a list of the hazards and their descriptions are first prepared. Then the hazard risk rating is conducted using the Failure Modes and Effects Analysis (FMEA) method. The number of priorities is calculated for each incident based on probability, intensity, and risk detection probability. Finally, the main causes of risks in the studies quarries are identified. The results obtained show that the most likely dangers in dimensional stone mines in West Azerbaijan are diamond cutting wire breaking, rock-fall, and car accidents, with the priority numbers of 216, 180, and 135, respectively. These hazards can be mitigated by applying some preservative activities such as timely cutting wire replacement, utilizing an intelligent system for cutting tool control, necessary personal training, and considering some preservative points.Mechanism of Zinc Complexation by Alkaline Ligands: A Molecular Modelling Study
https://jme.shahroodut.ac.ir/article_2407.html
In this work, the mechanism of zinc hydroxide and ammine complexation in caustic and ammonia leaching is investigated by molecular modelling using the density functional theory method. The speciation of zinc complexes is defined based on the thermodynamic data and Pourbiax diagrams. The mechanism of Zn+2 complexation by hydroxide and ammine ligands is simulated by molecular modeling. The structure of reactants in the form of individual clusters is modelled using the density function theory. In order to compare the hydroxide and ammine species structures, the geometry studies are carried out as well. The ammoniacal salt effectiveness to improve the dissolution and stability of the ammine species is studied. The ligand single molecule interaction with a smithsonite molecule is done for a better understanding. Molecular modeling show that the zinc hydroxide species are more stable based on the higher reaction free energies. The reaction free energies decrease by adding the OH- and NH3 ions to the complexes from -30.12 kcal/mol to -16.943 kcal/mol, and -22.590 kcal/mol to 66.516 kcal/mol, respectively. The Zn-OH bonds are shorter than Zn-NH3, and the ammine species show more regular structures in comparison with the hydroxide structures. The change of free energies in the presence of ammoniacal salts indicate that the sulfate ions can significantly improve the dissolution of zinc oxide in ammonia. The smithsonite interaction with ammonia and hydroxide reveal that hydroxide ions lead to a higher interaction energy than ammonia (-36.396 vs. -28.238), which is consistent with the higher stability of hydroxide species. The results obtained well-explain the experimental results obtained before, and can be effectively used to optimize the alkaline leaching of zinc oxide ore.&nbsp;Experimental investigation on deformation behavior of circular underground opening in hard soil using a three-dimensional physical model
https://jme.shahroodut.ac.ir/article_2492.html
In this work, the mechanical behavior of strata deformation due to drilling and surface loading is investigated using a 3D physical model. For this purpose, a scaled-down physical model is first designed. Then the tunnel drilling and support system are built. The subsidence experiments performed due to tunnel excavation and loading in a very dense and loose soil are performed. Soil is clayey sand (SC), and the percentages of its components are as sand (S = 1. 41%), gravel (G = 25%), and clay (C = 9.33%). Unstable tunnel support experiments are also carried out using physical simulation. Finally, deformations of soil surface and subsidence of strata are observed and recorded. In the tunnel with segmental support, 18.75% more load is applied than in the unsupported tunnel, and the total subsidence of the strata is reduced by 36.2%. The area of the deformed inner layers is decreased by 74.2%, and the length of the affected area in the largest layer is decreased by 48%. The depth of the cavity created at the surface is 46.66% less.A New 3D Model for Shear Wave Velocity by Utilizing Conventional Petrophysical Logs and Geostatistical Method
https://jme.shahroodut.ac.ir/article_2410.html
Shear wave velocity (Vs) is considered as a key parameter in determination of the subsurface geomechanical properties in any hydrocarbon-bearing reservoir. During a well logging operation, the magnitude of Vs can be directly measured through the dipole shear sonic imager (DSI) logs. On a negative note, this method not only is limited to one dimensional (1D) interpretation, it also appears to be relatively costly. In this research work, the magnitude of Vs is calculated using one set of controversial petrophysical logs (compressional wave velocity) for an oil reservoir situated in the south part of Iran. To do this, initially, the pertinent empirical correlations between the compressional (Vp) and shear wave velocities are extracted for DSI logs. Then those empirical correlations are deployed in order to calculate the values of Vs within a series of thirty wells, in which their Vp values are already recorded. Afterwards, the Kriging estimator along with the Back Propagation Neural Network (BPNN) technique are utilized to calculate the values of Vs throughout the whole reservoir.&nbsp; Eventually, the results obtained from the two aforementioned techniques are compared with each other. Comparing those results, it turns out that the Kriging estimation technique presents more accurate values of Vs than the BPNN technique. Hence, the supremacy of the Kriging estimation technique over the BPNN technique must be regarded to achieve a further reliable magnitude of Vs in the subjected oil field. This application can also be considered in any other oil field with similar geomechanical and geological circumstances.Determining the priority of taking into account risk factors in the technological zones of longwalls
https://jme.shahroodut.ac.ir/article_2514.html
The studies of risk factors on which the safety of miners depends are relevant. These factors include temperature and air velocity within roadways, relative air humidity, dust, noise and vibration, lighting, clutter, limited working space, the difficulty of work, and the collapse of roof rocks. Their greatest concentration is in the technological zones of longwalls, so it is important to determine the priority of taking into account the risk factors in certain zones for planning measures for labor protection in underground coal mining. Therefore, a matrix of priority of risk factors for technological zone longwalls is proposed. The matrix is based on a survey of experienced and well-informed scientists and engineers of coal mines (experts). Fifty experts are involved in the survey.The matrix assesses the priority of risk factors, and considers the technological zones of the longwalls for the planning labor protection measures. The zones of operation of the excavation machines and the end-sections of longwalls are defined as the most safety-critical. Less safety-critical, but also dangerous, are the zones of protection means and the zones of connection of the longwalls with the roadways. The level of a certain risk factor is determined for each zone. The highest priority should be given to the collapse of roofs, dust, clutter of the working space, and the severity of the miners' work. For each risk factor included in the matrix, the technical and organizational measures for labor protection are proposed to reduce the level of injuries for miners.Estimation of Pb and Zn Elements using Adaptive Neuro-Fuzzy Inference System (Case study: Gerde Kooh area, north of Yazd)
https://jme.shahroodut.ac.ir/article_2453.html
In the recent years, according to the difficulty of accurately measuring parameters and demarcation of earth sciences, attempts have been made to simplify the natural events for better investigation using geo-modelling. Modeling with intelligent methods is one of the new methods that has been considered in this field in the recent years. In this work, the intelligent method of adaptive neural-fuzzy inference system (ANFIS) is used to predict the elements of lead and zinc located in the Guard Kooh area, north of Yazd province in Iran. Descriptive statistics of data and correlation matrices of studied elements are obtained using the SPSS software. After the data is standardized, imported to the MATLAB software, and the lead and zinc elements are predicted using the ANFIS-SCM method. In this method, 70% of the data (175 samples) are set as the training data, and the rest (75 samples) are set as the test data, which are randomly selected. Using the obtained results, it is found that the grade of the estimated elements in the studied area has a good accuracy and a high correlation with the grade of the analyzed elements. As a result, the ANFIS-SCM intelligent method is a useful and accurate method for estimating the lead and zinc elements.Assessment of slope stability and its remedies in Palampur, Himachal Pradesh
https://jme.shahroodut.ac.ir/article_2520.html
The complex geography of the Himalayan mountain range, along with the natural circumstances that already exist and the ways in which people have influenced and intervened in the region- makes various regions of the range vulnerable to slope instability. The slope stability of the area that is the subject of this work is evaluated in Palampur, which is in the Kangra district of Himachal Pradesh. The primary objective of this work is to ensure that the slope remains stable so that the nearby three-sided residential structures and the highway remain protected. After the site visit, the geo-technical studies, which include testing in the form of bore holes and in the laboratory, are carried out. After evaluating the geo-technical technical report, the next step in the process is to begin the analysis of the slope's stability. In order to do an analytical analysis of the slope stability, the area has been subdivided into three portions, and labelled A-A, B-B, and C-C, respectively. Using the numerical modelling approaches, the mitigation design parameters for the area and the circular slip failure are computed. These calculations are based on the geo-technical characteristics of the studied area that have been specified. The factor of safety is calculated for both the natural and stable scenarios by the program. Because of this, some preventative steps and a few improvements are suggested.&nbsp;Application of Machine Learning Models for Predicting Rock Fracture Toughness Mode-I and Mode-II
https://jme.shahroodut.ac.ir/article_2434.html
In this work, the machine learning prediction models are used in order to evaluate the influence of rock macro-parameters (uniaxial compressive strength, tensile strength, and deformation modulus) on the rock fracture toughness related to the micro-parameters of rock. Four different types of machine learning methods, i.e. Multivariate Linear Regression (MLR), Multivariate Non-Linear Regression (MNLR), copula method, and Support Vector Regression (SVR) are used in this work. The fracture toughness of mode I and mode II (KIC and KIIC) is selected as the dependent variable, whereas the tensile strength, compressive strength, and elastic modulus are considered as the independent variables, respectively. The data is collected from the literature. The results obtained show that the SVR model predicts the values of KIC and KIIC with the determination coefficients (R2) of 0.73 and 0.77. The corresponding determination coefficient values of the MLR model and the MNLR model for KI and KII are R2 = 0.63, R2 = 0.72, and R2 = 0.62,0.75, respectively. The copula model predicts that the value of R2 for KI is 0.52, and for KII R2=0.69. K-fold cross-validation testing method performs for all these machine learning models. The cross-validation technique shows that SVR is the best-designed model for predicting the fracture toughness mode-I and mode-II.The Finite Difference Analysis of Empirical Tunnel Support Design in High Stress fractured rock mass Environment at the Bunji Hydropower Project, Pakistan
https://jme.shahroodut.ac.ir/article_2513.html
Support design is the main goal of the Q and rock mass rating (RMR) systems. An assessment of the Q and RMR system application in tunnelling involving high-stress ground conditions shows that the first system is more appropriate due to the stress reduction factor. Recently, these two systems have been empirically modified for designing the excavation support pattern in jointed and highly stressed rock-mass conditions. This research work aims to highlight the significance of the numerical modelling, and numerically evaluate the empirically suggested support design for tunnelling in such an environment. A typical horse-shoe-shaped headrace tunnel at the Bunji hydropower project site is selected for this work. The borehole coring data reveal that amphibolite and Iskere Gneiss are the main rock mass units along the tunnel route. An evaluation of the proposed support based on the modified empirical systems indicate that the modified systems suggest heavy support compared to the original empirical systems. The intact and mass rock properties of the rock units are used as the input for numerical modelling. From numerical modelling, the axial stresses on rock bolts, thrust bending moment of shotcrete, and rock load from modified RMR and Q-systems are compared with the previous studies. The results obtained indicate that the support system designed based on modified version of the empirical systems produce better results in terms of tunnel stability in high-stress fractured rock mass conditions.Selective Recovery of Pt, Pd, and Rh from Spent Catalysts by Functionalized Magnetite Nanoparticles
https://jme.shahroodut.ac.ir/article_2460.html
Selective recovery of platinum group metals including Pt, Pd, and Rh from the spent automobile catalysts is investigated by functionalized magnetite nanoparticles as a novel adsorbent. Magnetite nanoparticles are synthesized by co-precipitation of ferrous and ferric salts with ammonium hydroxide, and then coated with a tetraethyl orthosilicate to form well-dispersed silica-coated magnetite nanoparticles. The silica-coated nanoparticles are then functionalized with three different types of organosilane ligands including monoamine (FeSiORA), ethylenediamine (FeSiORDA), and diphenylphosphino (FeSiORP). The effects of initial pH, amount of adsorbent, contact time, and chloride concentration in a multi-component leaching solution are examined in batch tests on [PdCl4]2-, [PtCl4]2-, [PtCl6]2-, and [RhCl6]3-. Among the different types of organosilane ligands examined, the FeSiORA nanoparticles and FeSiORDA, for selective sorption of PGM from the leaching solution, are unsuccessful. It is found that FeSiORPs can effectively adsorb Pt and Pd but exhibit no affinity towards Rh and base metal ions. Under the optimum conditions, the adsorption rates of Pt, Pd, and Rh are estimated 97.5%, 97.0%, and 15.0%, respectively.A Deep Neural Network for Classification of Land Use Satellite Datasets in Mining Environments
https://jme.shahroodut.ac.ir/article_2526.html
Land use (LU) is one of the most imperative pieces of cartographic information used for monitoring the mining environment. The extraction of land use data sets from remotely sensed satellite images has garnered significant interest in the mining region community. However, classification of LUs from satellite images remains a tedious task due to the lack of availability of efficient coal mining related datasets. Deep learning methods provide great leverage to extract meaningful information from high-resolution satellite images. Moreover, the performance of a deep learning classification approach significantly depends on the quality of the datasets. The present work attempts to demonstrate the generation of satellite-based datasets for the performance analysis of different deep neural network (DNN)-based learning algorithms in the LU classifications of mining regions. The mining regions are broadly classified into distinct regions based on visual inspection, namely barren land, built-up areas, waterbody, vegetation, and active coal mines. In our experimental work, a patch of 100 spatial samples for each of the five features is generated on three scales, as [1 &times; 1 &times; 3], [5 &times; 5 &times; 3], and [10 &times; 10 &times; 3]. Moreover, the effects of different scalabilities of the dataset on classification performances are also analyzed. Furthermore, this case study is implemented for the large-scale benchmark of satellite image datasets for mining regions. In the future, this work can be used to classify LU in the relevant study regions in real time.CFD Modeling of Impact of Gas Content Uncertainty on Methane Distribution in Underground Coal Mine Roadways
https://jme.shahroodut.ac.ir/article_2461.html
Methane has been known as a safety risk for the coal mining activities. Accordingly, one can mitigate this risk, and hence, the level of hazard to which the mining workers are exposed, by predicting the possible exceedance of allowable methane dosage should be provided with a reliable information on the distribution of methane across the working face considering the uncertainties associated with the gas content of such deposits. In this work, the gas content uncertainty in a coal seam is first investigated using the geo-statistical simulation. Then a method is proposed in order to predict methane gas emission based on the Monte Carlo random simulation method. Next, the results obtained are introduced into a 3D Computational Fluid Dynamics (CFD) model to estimate the methane distribution considering the uncertainty associated with the gas content. Defined as zones where the methane concentration is so high that an explosion is much likely to occur, the elevated methane zones (EMZs) are delineated across the working faces. The results obtained show that UGC has an impact on the ventilation parameters and EMZs. The proposed method could be carried out in order to guide the ventilation design in improving safety.Two-dimensional simulation of the dynamic transportation of volatile hydrocarbons in the vadose zone of Tehran Oil Refinery and Industrial area of Ray, Tehran, Iran
https://jme.shahroodut.ac.ir/article_2512.html
This work investigates the reactive transport of volatile hydrocarbons in the unconfined aquifer system of Tehran oil refinery and the industrial area of Ray, Tehran. A 2D finite volume model is presented to predict the soil gas contamination caused by LNAPL traveling on the phreatic surface through the vadose zone of the aquifer incorporating physical, chemical, and biological processes. A multi-purpose commercial software called PHOENICS is modified by incorporating extra codes to solve the model equations numerically. The model predictions closely agree with the field measurements, showing that the LNAPL migration is typically affected by the volatilization process. LNAPLs represent a potential long-term source of soil and groundwater contamination in the studied site. A comparison of the simulation results in a time step of 36 years with the results of field studies shows that the presented numerical model can simulate the reaction transfer of evaporated hydrocarbons in the unsaturated region. The concentrations have decreased in the time step of 36 years compared to the values shown in the time step of 50 years. This decrease in the hydrocarbon gas-phase concentrations in the unsaturated zone is due to excavations at the site for field studies. Through these excavations, a significant volume of the gaseous phase trapped below the earth's surface is released into the atmosphere, which reduces the accumulation of volatile gases beneath the earth's surface.Delineation of Iron Alteration Zones using Spectrum-Area Fractal Model and TOPSIS Decision-Making Method in Tarom Metallogenic Zone, NW Iran
https://jme.shahroodut.ac.ir/article_2462.html
Signal analysis approaches are a powerful and widely used tool in processing multi-spectral satellite images for detection of alteration zones. The main goal of this work is application of the spectrum-area fractal methodology based on the Landsat 8 OLI satellite images&rsquo; data for separation alteration zones for iron oxides at the Tarom region (NW Iran). These alteration zones, Normalized Difference Vegetation Index (NDVI), and Normalized Difference Water Index (NWDI) are detected using the band-ratio and band combination methods. Then the calculated values are categorized by Spectral Angle Mapper (SAM), k-means, and S-A fractal model. Considering a positive correlation of iron oxides alterations along with magnetite mineralization as an index of mineralization at the studied region, the promising areas are classified by a decision-making model using the TOPSIS method with an acceptable accuracy for presenting in the exploration models.Fractal modeling of geochemical mineralization prospectivity index (GMPI) based on CLR transformed data for geochemical targeting: a case study of Cu porphyry mineralization
https://jme.shahroodut.ac.ir/article_2516.html
This work aims to investigate the geochemical signatures of the Cu porphyry deposit in the Dalli area using the geochemical soil samples. At the first step, the geochemical data was opened using the Centered Log-Ratio (CLR) transform method. Then those outlier samples that reduce the accuracy of the geochemical models were detected and removed using the Mahalanobis Distance (MD) method. We applied the Principal Component Analysis (PCA) and Geochemical Mineralization Prospectivity Index (GMPI) methods on the cleaned transformed geochemical dataset. The PCA method identified five principal components (PCs), from which PC1 including Cu, Au, and Mo, are specified as the mineralization factor (MF). The GMPI approach can improve the multivariate geochemical signature in geochemical mapping. Hence, the GMPI values of the samples were calculated based on the score values of MF (Cu, Au, Mo). The results convey that the large values of GMPI (MF) (Cu, Au, Mo) strongly correlate with the quartz diorite porphyry rocks and potassic alteration zones. The GMPI (MF (Cu, Au, Mo)) index was modeled using the Concentration-Number (C-N) fractal method. The C-N fractal model identified four geochemical populations based on the different fractal dimensions. The geochemical anomaly map of GMPI (MF) (Cu, Au, Mo) was delineated using these classified populations. The obtained promising areas were validated adequately by more detailed exploration works and deep drilled boreholes as well. The Cu-Au mineralization potential parts are appropriately mapped by this hybrid method. The results obtained demonstrate that this scenario can be adequately used for geochemical mapping on local scales.Adsorptive Study of Cadmium Removal from Aqueous Solution Using a Coal Waste Loaded with Fe3O4 Nanoparticles
https://jme.shahroodut.ac.ir/article_2446.html
A coal waste sample loaded with Fe3O4 nanoparticles is employed as an efficient adsorbent to remove Cd from synthetic wastewater. The synthesized nanocomposite is characterized using the Fourier transform-infrared (FT-IR), X-ray diffraction (XRD), and transmission electron microscopy (TEM) techniques. The visual analysis of the microscopic image shows that the mean size of the magnetite nanoparticles is about 10 nm. The effects of the operating variables of the initial solution pH (3-11) and nanocomposite to pollutant ratio (7-233) are evaluated using the response surface methodology on cadmium adsorption. The process is also optimized using the quadratic prediction model based on the central composite design. The statistical analysis reveals that both factors play a significant role in Cd adsorption. The maximum Cd removal of 99.24% is obtained under optimal operating conditions at pH 11 and nanocomposite/cadmium ratio of 90 after 2 h of equilibrium contact time. A study of the adsorption kinetics indicates that the maximum removal could be attained in a short time of about 2 min following a first-order model. The isotherm investigations present that the Cd adsorption on the Fe3O4/coal waste nanocomposite has a linearly descending heat mechanism based on the Temkin isotherm model with the minor applicability parameters than the other isotherm models. The overall removal behaviour is attributed to a two-step mechanism including a rapid adsorption of cadmium ion onto the active sites at the surface of nanocomposite followed by a slow cadmium hydroxide precipitation within the pores over the nanocomposite surface.modeling, optimizing, and characterizing the elimination process of cyanide ion from an industrial wastewater of gold mine by Caro’s acid method
https://jme.shahroodut.ac.ir/article_2508.html
The present work is aimed to examine the elimination of cyanide ions from the wastewater derived from the Agh-Darreh gold mine using the Caro&rsquo;s acid method. The response surface modeling is utilized to evaluate and optimize the influential parameters such as the sulfuric acid/hydrogen peroxide ratio, pH, Caro&rsquo;s acid concentration, and contact time on the elimination process. The results obtained indicate that the increase in the Caro&rsquo;s acid concentration and contact time has a positive impact on the elimination of the free cyanide ions, while the increment in the weight ratio of sulfuric acid/hydrogen peroxide and pH higher than 9.5 demonstrate a negative impact. Also it is found that the quadratic effect of pH has the highest influence on the removal of cyanide ion, and the linear effect of the ratio of sulfuric acid/hydrogen peroxide has the lowest degree of importance. Additionally, the optimization process is carried out, and about 96.4% of the cyanide ions is eliminated from the wastewater under the optimal conditions including 2 g/L Caro&rsquo;s acid concentration, 9.3 pH, 8 min contact time, and sulfuric acid to hydrogen peroxide (weight) ratio of 2.A Practical Comparison between Gaussian and Direct Sequential Simulation Algorithms using a 3D Porosity Dataset
https://jme.shahroodut.ac.ir/article_2442.html
The geo-statistical simulation algorithms for continuous spatial variables have been used widely in order to generate the statistically-honored models. There are two main algorithms doing the continuous variable simulation, Sequential Gaussian Simulation (SGS) and Direct Sequential Simulation (DSS). The main advantage of the DSS algorithm against the SGS algorithm is that in the DSS algorithm no Gaussian transformation of the original data is made. In this work, these two simulation algorithms are explained, and their applications to a 3D spatial dataset are deeply investigated. The dataset consists of the porosity values of 16 vertical wells extracted from an actual cube obtained by a seismic inversion process. One well data is excluded from the simulation process for the blind well test. Comparison between the histograms show that the histogram reproduction is slightly better for the SGS algorithm, although the population reproductions are the same for both SGS and DSS results. The DSS algorithm reproduce the mean of input data closer to the mean of well data compared to that of the SGS algorithm. Considering one realization from each simulation algorithm, the RMS error corresponding to all simulated cells against the real values is approximately equal for both algorithms. On the other hand, the error show a slightly less value when the mean of 100 realizations of the DSS result is considered.Compressional and shear interval velocity modeling to determine formation pressures in an oilfield of SW Iran
https://jme.shahroodut.ac.ir/article_2493.html
In the seismic methods, estimation of the formation pressures is obtained by converting the seismic velocity to the pore pressure, and comparing it with the effective pressure during the well-test program. This work is a new challenge regarding the velocity study domain in an oil field in SW Iran. The reservoir generally consists of carbonate rocks, and contains no shale interbeds. Here, 23 well information, seismic data interpretation, compressional (Vp), and shear velocity (Vs) models are implemented. The models are determined from the combined geo-statistical methods, and the results obtained are compared with the fractal models. The final Vs cube is modeled in order to determine the formation fracture pressure using the exploratory well cores and dipole sonic imager (DSI) Vs logs with a correlation coefficient of 0.95 for the Vs data obtained from the porosity, lithology, and primary DSI data. The vertical seismic profiling (VSP) data introduce a maximum interval velocity of 2760-2900 m/s in the field related to the Gotnia formation. The final amounts of seismic acoustic impedance inversion (AI) at the bottom of the field are mostly in the range of 8000-15000 [(m/s)*(g/cm3)], which can be related to the calcareous formations. Based on the Logratio matrix obtained from the fractal velocity-volume (Vp-V) model, the maximum overall accuracy (OA) in the dominant limestone intervals is 0.74. It indicates a high correlation of the Vp cube model obtained from the combination of sequential Gaussian simulation (SGS) and co-kriging models with AI. The uncertainty studies of Vp model in blind wells&nbsp;are about 50%, which is acceptable considering the large well numbers.Effect of Glass and Polypropylene Hybrid Fibers on Mode I, Mode II, and Mixed-Mode Fracture Toughness of Concrete Containing Micro-Silica and Limestone Powder
https://jme.shahroodut.ac.ir/article_2439.html
Fracture toughness is an important concrete property that controls crack extension and concrete fracture. Concrete is the most widely used material in civil engineering containing the most conventional and cheapest materials. Accordingly, cracks and fractures may cause irreparable damages. To this end, fibre-reinforced concretes have been recently constructed in order to overcome the aforementioned weaknesses. Crack propagation and fracture toughness of various concrete specimens are analyzed by the straight notched Brazilian disc (SNBD) test. The specimens are conventional concrete lacking micro-silica and limestone powder, and those containing various volume percentages of fibers including the concrete specimens containing 0.35% individual polypropylene (PP) fibers, 0.35% individual glass fibers, concrete specimens containing 0.17% PP and 0.18% glass fibers, and concrete fibers containing 0.1% PP and 0.25% glass fibers. Micro-silica has replaced 10 wt% cement in all fiber-reinforced concrete specimens, and limestone has replaced 5 wt% cement. Crack extension from the pre-existing cracks in the specimens and mode I, mode II, and mixed-mode fracture toughness are calculated. The BD test is performed on the specimens at the crack inclination angles of 0&deg;, 15&deg;, 28.83&deg;, 45&deg;, 60&deg;, 75&deg;, and 90&deg;. The experimental results show the initiation of wing cracks at angles less than 60&deg; (0 &lt; &alpha; &lt; 60&deg;) from the tip of the pre-existing cracks. The crack growth and propagation path approach the loading direction by continuing loading. However, the cracks are initiated at a distance of d from the crack tip at angles larger than 60&deg;. The observed distance is larger in the fiber-less specimens than in the fiber-reinforced specimens. The concrete specimens reinforced by 0.17% PP and 0.18% glass hybrid fibers containing micro-silica and limestone powder showed the highest mode I, mode II, and mixed-mode fracture toughness compared to the other concrete specimens.An Investigation into Bench Health Monitoring under Blast Loading in Hoek-Brown Failure Criterion using the Finite Difference Method
https://jme.shahroodut.ac.ir/article_2515.html
Blast and stress release create cracks, fractures, and excavation damage zone in the remaining rock mass. Bench health monitoring (BHM) is crucial regarding bench health and safety in blast dynamic loading. Several empirical criteria have been proposed for a quick estimation of different parameters of a rock mass in the zone damaged by the blast. This work estimates the rock mass properties behind the blast hole based on the generalized Hoek-Brown failure criterion and quantitative disturbance factor (D). Considering a constant D value, either zero or one, for the entire rock mass, remarkably alters its strength and stability, resulting in very optimistic or very conservative analyses. Therefore, D is considered based on the elastic damage theory, and numerical simulation is conducted based on the finite difference software FLAC to investigate the vibration and damage threshold by monitoring the peak particle velocity (PPV) in the bench domain with different geometries. According to the numerical simulation, as the depth behind the blast hole increases, the value of D decreases from one to zero almost non-linearly, resulting in a non-linear reduction in the Hoek-Brown behavioral model properties. It is found that using various parameters of rock mass in the blast-induced damage zone behind the hole leads to thoroughly different PPV values than the constant parameters. Accordingly, the approach to using the quantified values of parameter D is of great importance in the estimation of various properties of a rock mass in the blast-induced zone, as well as calculation of the vibration.Cavability Assessment of Rock Mass in Block Caving Mining Method based on Numerical Simulation and Response Surface Methodology
https://jme.shahroodut.ac.ir/article_2468.html
The present work aims at implementing Response Surface Methodology (RSM) in order to generate a statistical model for Minimum Required Caving Span (MRCS) and estimate both the individual and mutual effects of the rock mass parameters on rock mass cavability. The adequate required data is obtained from the result of numerical modeling. In this work, various arrays of numerical simulations (480 models) are carried out using the UDEC software in order to study the rock mass cavability thoroughly. The effect of each individual parameter and their mutual effect on MRCS are investigated by means of ANOVA. ANOVA indicates that all the chosen parameters (depth, dip of the joint, number of joints, angle of friction of the joint surface, and joint spacing) highly affect MRCS. In other words, the results of ANOVA are in high agreement with the results of the conventional sensitivity analysis. Moreover, a combination of joint spacing and joint inclination has the highest mutual effect on MRCS, and a combination of undercut depth and joint spacing has the lowest effect on MRCS.The Role of Functional Groups in Selective adsorption of Gold over Copper Cyanocomplexes by Activated Carbon: A DFT Study
https://jme.shahroodut.ac.ir/article_2518.html
The adsorption of gold and copper cyanide complexes on the activated carbon is investigated using the Density Functional Theory (DFT). In order to represent the activated carbon, two fullerene-like model (presenting structural defect sites) and a simple graphene layer containing different functional groups (presenting chemical active sites) are employed. The structural defect sites show a much lower adsorption tendency toward all the cyano complexes comparing to the chemical active sites. The interaction energy for all of the complexes with structural defect sites (concave) is very low. However, the graphene layer with unsaturated active sites displays the highest level of interaction almost for all the complexes except Cu(CN)4-3. The effect of oxygen functional groups on the graphite edges shows a crucial role in the selectivity of gold adsorption over copper complexes. It has increased adsorption energy for Cu(CN)2- in the presence of OH and COOH, and has decreased adsorption energy for Au(CN)2- by OH and increased by COOH. The study results elucidate the lower selectivity for adsorption of gold over copper cyanides by high oxygen content activated carbon. The energy levels of the HOMO and LUMO orbitals show adsorption of unpaired cyanide anions on the activated carbon surface occurs by electron transfer from the complex to the adsorbent and adsorption onto the activated carbon edges by transferring electrons from the absorbent to the complex. The result has clearly demonstrated that the functional groups increase the adsorption tendency for both the gold (only COOH) and copper complexes (OH and COOH) but deteriorate the selectivity of gold over copper cyanides.Cavity Growth in Underground Coal Gasification Method by Considering Cleat Length and Inclination of Coal with Elasto-Brittle Behavior
https://jme.shahroodut.ac.ir/article_2467.html
The in-situ coal is converted to the synthetic gas in the process of underground coal gasification (UCG).&nbsp; 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.Simulation of crack propagation mechanism in porous media using the modified linear element displacement discontinuity method
https://jme.shahroodut.ac.ir/article_2527.html
In this work, an effective methodology is introduced for simulation of the crack propagation in linear poroelastic media. The presence of pores and saturated cracks that can be accompanied by fluid flow makes the use of poroelastic media inevitable. In this work, involvement of the time parameter in crack propagation is of particular importance. The order of doing the work is such that first, derives the fundamental solutions of a poroelastic higher order displacement discontinuity method (PHODDM). Then will be provided a numerical formulation and implementation for PHODDM in a code named linear element poroelastic DDM (LEP-DDM). Analytical solutions use different times to check the correctness and validity of the proposed solution and the newly developed code. The numerical results show a good agreement and coordination with the analytical results in time zero and 5000 seconds . The code is able to pursue crack-propagation in time and space. This topic is introduced and shown in an example.