Journal of Mining and Environement
Volume:11 Issue: 1, Winter 2020

Estimation of the possible instability that may be encountered in the excavation slope(s) during the planning and application steps of the rock excavation processes is an important issue in geoengineering. In this paper, a modelling method is presented for assessing the probability of wedge failure involving new permanent or temporary slope(s) along the planned excavation direction. The geostructural rock slopes including wedge blocks are determined geometrically in the first step. Here, a structural data analysis system that includes a series of filterings, sortings, and linear equations used to reveal the necessary geometric conditions for the wedge form is developed and used. The second step involves the 3D visualization and Factor of Safety (FS) using the limit equilibrium analysis of wedges on both the actual and planned new excavation surfaces. The last step is the Monte Carlo simulation, which is used in assessing the instabilities on the actual and planned new excavation surfaces. These new slope surfaces that have not yet been excavated are called the virtual structures. As a result of this work, the mean and probabilistic FS variations in the planned excavation direction are obtained as profiles. We suggest the preliminary guidelines for the mean and probability of the wedge failure in the excavation direction. The model is tested on a motorway cut slope. The FS results obtained from the Monte Carlo simulation calculations are compared with the mean results and the changes are revealed with the reasons.

Truck and shovel are the most common raw material transportation system used in the cement quarry operations. One of the major challenges associated with the cement quarry operations is the efficient allocation of truck and shovel to the mining faces. In order to minimize the truck and shovel operating cost, subject to quantity and quality constraints, the mixed integer linear programing (MILP) model for truck and shovel allocation to mining faces for cement quarry is presented. This model is implemented using the optimization IDE tool GUSEK (GLPK under SciTE Extended Kit) and the GLPK (GNU Linear Programming Kit) standalone solver. The MILP model is applied to an existing cement quarry operation, the Kohat cement quarry located at Kohat (Pakistan) as a case study. The analysis of the results of the relating case study reveals that significant gains are achievable through employing the MILP model. The results obtained not only show a significant cost reduction but also help in achieving a better coordination among the quarry and quality department.

Rock burst is the most attractive and hot research area in geomechanics, mining, and civil engineering due to the increasing depth of mines and construction of deep underground structures. It has also been a severe problem in ground control measures in the last few decades. Many studies have been done by different researchers in order to minimize the hazards of rock burst and to provide a safe mining/working environment. It is important to review the current advancement of rock burst prediction and its preventive measures. This paper reviews the experimental progress of rock burst warning, prediction, control measures, and potential damage measures. Different effective methods of rock burst prediction and control are also described.

Identification and mapping of the significant alterations are the main objectives of the exploration geochemical surveys. The field study is time-consuming and costly to produce the classified maps. Therefore, the processing of remotely sensed data, which provide timely and multi-band (multi-layer) data, can be substituted for the field study. In this study, the ASTER imagery is used for alteration classification by applying two new methods of machine learning, including Random Forest and Support Vector Machine. The 14 band ASTER and 19 derivative data layers extracted from ASTER including band ratio and PC imagery, are used as training datasets for improving the results. Comparison of analytical results achieved from the two mentioned methods confirmed that the SVM model has sufficient accuracy and more powerful performance than RF model for alteration classification in the study area.

Recognition of ore deposit genesis is still a controversial challenge for economic geologists. Here, this task was addressed by the virtue of Bayesian data fusion (BDF) implementing available proofs: semi-schematic examples with two (Cu and Pb + Zn) and three (Cu, Pb + Zn and Ag) evidences. The data, in current paper are just concentrations of indicated elements, were collected from Angouran’s deposit in Iran at prospecting and general exploration stages. BDF was used for discrimination between three geneses of Massive Sulfide, Mississippi and SEDEX types. Better genesis recognition with clear discrimination between the geneses was achieved by BDF as compared with earlier studies. The results showed that uncertainties were reduced from 50% to less than 30% and deposit recognition was improved greatly. Furthermore, we believe that using more properties can have a beneficial effect on the overall outcome. The comparison made between 2 and 3 properties showed that the amount of probable belonging values to any type of deposit was greater in 3 properties. It was also confirmed that using the completed information from the various stages of exploration progress can be amplified and be used for genesis recognition via BDF.

Ensuring the stability and integrity of underground gas storage salt caverns is a very complicated subject due to the non-linear and time-dependent behavior of rock salts under complicated thermal and mechanical loading conditions. For this reason, pressure and temperature fluctuations in the caverns and their surrounding strata must be integrated into the analysis and the numerical tools that are used for this purpose. LOCAS, a 2D axisymmetric finite-element code, dedicated to the stability analysis of underground salt spaces, was applied to assess the effects of various operating and geometrical parameters on the cavern behavior. In this paper, we aimed to give an overall assessment of the behavior of the salt caverns used for natural gas storage. In this work, some specific loading scenarios were considered first, followed by thorough parametric and sensitivity analyses to reveal the impacts of the geometrical parameters and operational parameters involved on the behavior of salt caverns using the modern stability criteria. The findings showed that the onset of dilation was more likely to happen within the first cavern life cycle when pressure dropped to the minimum level. As for the potential of tension occurrence in the surrounding rock, this is more likely to happen by increasing the number of operation cycles, especially in the upper one-third of the cavern wall. Finally, it was seen that the cavern depth and minimum cavern internal pressure had even more important influences than the others on the salt cavern behavior.

The Urumieh-Dokhtar Magmatic Arc (UDMA) is recognized as an important porphyry, disseminated, vein-type and polymetallic mineralization arc. The aim of this study is to identify and subsequently determine geochemical anomalies for exploration of Pb, Zn and Cu mineralization in Mial district situated in UDMA. Factor analysis, Concentration-Number (C-N) fractal model and Local Linear Model Tree (LOLIMOT) algorithm used for this purpose. Factor analysis utilized in recognition of the correlation between elements and their classification. This classified data used for training the LOLIMOT algorithm based on relevant elements. The results of the LOLIMOT algorithm represent anomalies in areas with no lithogeochemical samples. Although, the C-N log-log plot for target elements were generated based on stream sediment and lithogeochemical samples which could be delineated mineral potential maps of the target elements. Results obtained by the LOLIMOT and fractal modeling show that the SW and the Eastern parts of the area are proper for further exploration of Cu, Pb, and Zn.

In the recent decades, water scarcity has become a major challenge for many reasons, especially the inadequate use of water resources. The mineral processing plant is among the most important water-consuming industries. Filtration, as one of the important processes in water recovery, is a process in which the solid-suspended particles are removed from the liquid. In the present work, the effect of the additives affecting the filtration process upon the responses including the resistance to filter cloth (R), specific cake resistance (α), moisture content, water recovery rate, and cake formation rate by the vacuum top-feed method is investigated. The experiments are performed by two methodologies: one-factor-at-a-time and statistical analysis. The additives are the flocculant, coagulant, surfactant, and filter aid. According to the one-factor-at-a-time methodology, the optimal type and dosage of the variables are as follow: flocculant A25 with a concentration of 15 g/L, perlite as the filter aid with an amount of 2.5%, surfactant cop 20-101 with a concentration of 3 cc/L, and the coagulant CaCl2.2H 2O with a concentration of 2.5 g/L. The usage of the flocculant, surfactant, and filter aid at the same time is also statistically analyzed with the aim of maximizing the cake formation rate and minimizing the moisture content of the filter cake. Under the optimal conditions and taking into account 11.68 g/t of the flocculant A25, 3.8% of perlite as the filter aid, and2.92 cc/L of the surfactant cop 20-101, the cake formation rate and the moisture content were obtained to be 0.297 mm/s and 12.7 %, respectively.

This work presents the application of a geostatistical-based modeling approach for building up electrical properties acquired from a geophysical electrical tomography survey deployed for the purpose of porphyry Cu exploration at the Takht-e-Gonbad deposit, in the central domain of Iran. Electrical data were inverted in 2D along several profiles across the main favorable zones of Cu-bearing mineralization to image electrical resistivity and chargeability properties. Upon tight spatial correlation of these geophysical properties and Cu mineralization (i.e. Cu grade), electrical models were constructed in 3D through geostatistical interpolation of 2D inverted data to provide insights into the geometry of probable ore mineralization. Anomalous geophysical zone that was coincident simultaneously with higher values of electrical chargeability and resistivity, was in accordance with the main body of high Cu grades generated from exploratory drillings. It reveals that the porphyry-type Cu mineralization system in this area has strong geophysical footprints controlled mainly by rock types and alterations. Note that these physical models supply valuable pieces of information for designing the layout of further exploratory drillings, constructing geological characteristics, separating non-mineralized form mineralized zones, and resource modeling.

One of the most effective parameters in economics of open-pit mines is the pit slope angle, so that the slope angle more than the optimum value increases the probability of a large failure in the pit wall and the slope angle less than the optimum value leads to increasing stripping ratio and reducing net present value of mine. Therefore, in this paper, considering the limit equilibrium methods of modified Bishop and modified Janbu and numerical models of the slope stability analysis, the effect of overall slope angle on the Economics of open pit mines was investigated. In addition, it was shown that selecting the overall slope angle less than the optimum value leads to reducing the depth of open-pit mining (the ultimate pit depth) and consequently, reducing the net present value of mine. Finally, in homogenous and Isotropic media, the results of Bishop and Janbu and numerical modeling are close together.

The Mighan playa/lake is characterized as a closed catchment. In the recent years, the rapid industrialization and urbanization has resulted in a pollution area in the city of Arak. In this work, we focus on six regions around the playa/lake to study the distribution of heavy metals in the waters and their contamination risk. A total of 32 water samples are analyzed to determine the contamination degree of heavy metals, i.e. Hg, As, Cd, Cr, Cu, Pb, and Zn. The heavy metal pollution index, heavy metal evaluation index, and degree of contamination are utilized to assess the pollution extent of these metals. The spatial distribution patterns reveal that the waters in different areas of playa/lake are in a good condition. The island, lake in playa, and the Wastewater Mineral Salts Company are most seriously polluted with Pb, being higher than the standard of drinking water quality limit. Water in the wastewater treatment plant is polluted with Hg and As. The correlation matrix, factor analysis, and cluster analysis are used to support the idea that Pb may be mainly derived from the atmospheric input, and As and Hg from the wastewater treatment plant, agricultural lands, and domestic waste. Many native and migratory birds live in the Mighan playa, which is exposed to heavy metals. Therefore, it is required to monitor heavy metals in the Arak playa and to manage the municipal, industrial, and agricultural activities around it and to reduce them.

Truck-Shovel fleet, as the most common transportation system in open-pit mines, has a significant part of mining costs, for which optimal management can lead to substantial cost reductions. Among the available dispatch mathematical models, the multi-stage approach is well suited for allocating trucks to respected shovels in a dynamic dispatching program. However, with this kind of modeling sequencing of the allocated trucks is not possible though it is important to find out the best solution so that getting the minimum accrued cost. To comply with the shortcoming of the traditional model, in this paper, a new hybrid model is developed and applied in Copper Mine of Iran, in which for each truck an allocation matrix is considered as input to the genetic algorithm implemented to determine the best solution. According to the obtained results, the optimal sequencing of the trucks can result in a significant (31%) cost reduction in a shift.

Determination of the borehole and fracture initiation positions is the main aim of a borehole stability analysis. A wellbore trajectory optimization with the help of the mud pressure may be unreasonable since the mud pressure can only reflect the degree of difficulty for the initial damage to occur at the wellbore rather than the extent of the wellbore damage. In this work, we investigate the failure extension in different arbitrary inclination boreholes under different in-situ stress regimes. Assuming the plane strain condition, the Mohr-Coulomb, Mogi-Coulomb, and Modified Lade rock failure criteria are utilized. We present an analytical equation to determine the optimum drilling trajectory of an Iranian oilfield. In order to predict the degree of wellbore damage, the initial shear failure location, failure width, and failure depth of arbitrary wellbores are determined. Then a new model is derived to calculate the initial failure area of a directional wellbore because it is more efficient in a wellbore stability analysis. The results obtained show that in the target oilfield, the vertical and low-deviated direction is the optimum drilling path. According to the results of this work, optimization of the wellbore trajectory based on the estimated failure zone is a reasonable method if a considerable failure zone takes place around the borehole wall.

The flotation circuit in Sungun copper plant consists of two column flotation cells as cleaner, having fixed-spargers system. To achieve the expected aims in flotation step, there are serious operational challenges such as: fast choking of the static mixers, boiling problem, burping phenomena and pulp overflow to concentrate lander, maintenance and control problems. An attempt was exerted by implementing new helical static mixer in one of cleaner cells instead of old elliptical type to overcome the challenges. The changes resulted in proper performance of the column whereas burping phenomena due to choking was eliminated, finer bubbles were produced, and the boiling and overflow problems were solved. Also, the static mixers life time increased to 7 months in helical column cells from one month in elliptical column cells. In addition to 40% air consumption reduction and 20% solid percent increase in final product, the grade of Cu and Mo increased by helical static mixer replacement up to about 18.7% from 16.8% (11%) and to 511.1 ppm from 263 ppm (94%) in the cleaner step, respectively. Recovery of Cu and Mo were increased about 1.5% and 0.2%, respectively. Finally, the results proved the effectiveness of finer bubble generation on grade improvement is depend on minerals hydrophobicity as Mo grade increased more than Cu.

Bedrock unconfined compressive strength (UCS) is a key parameter in designing thegeosciences and building related projects comprising both the underground and surface rock structures. Determination of rock UCS using standard laboratory tests is a complicated, expensive, and time-consuming process, which requires fresh core specimens. However, preparing fresh cores is not always possible, especially during the drilling operation in cracked, fractured, and weak rocks. Therefore, some attempts have recently been made to develop the indirect methods, i.e. intelligent predictive models for rock UCS estimation, which require no core preparation and laboratory equipment. This work focuses on the application of new combinations of intelligent techniques including adoptive neuro-fuzzy inference system (ANFIS), genetic algorithm (GA), and particle swarm optimization (PSO) in order to predict rock UCS. These models were constructed based on the collected laboratory datasets upon 93 core specimens ranging from weak to very strong rock types. The proposed hybrid model results were compared with each other, and the real data and multiple regression (MR) results. These comparisons were made using coefficient of correlation, mean of square error, mean of absolute error, and variance account for indices. The comparison results proved that the ANFIS-GA combination had a relatively higher accuracy than the ANFIS-PSO combination, and both had a higher capability than the MR model. Furthermore, the ANFIS-GA and ANFIS-PSO model results were completely in accordance with the UCS laboratory test, and they were more accurate than the previous single/hybrid intelligent models. Lastly, a parametric study of the suggested models showed that the density and Schmidt hammer rebound had the highest influence, and porosity had the lowest influence on the output (UCS).

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.

In this work, two clay-based composites are prepared for the adsorptive removal of the chloride ions from aqueous solutions. These composites are characterized through Fourier transform-infrared spectroscopy, scanning electron microscopy, X-ray fluorescence spectroscopy, and X-ray diffraction analysis. The effects of different parameters such as the contact time, amount of adsorbent, chloride concentration, temperature, and pH are studied by batch experiments. Also the isotherm, kinetic, and thermodynamic of the adsorptive removal of the chloride ions from these two composites are investigated. According to the results obtained, the adsorptive removal of chloride ions is initially rapid, and the equilibrium time is reached after 30 min. The optimal pH value is 7.0 for a better adsorption, and the maximum capacity can be achieved, which is 60.2 mg/g with 1000 mg/L of the initial chloride concentration. The Langmuir, Freundlich, Temkin, and Dubinin-Radushkevich adsorption models are applied to describe the equilibrium isotherms at different chloride concentrations. According to the equilibrium isotherms and the correlation coefficients (R2CDC: 0.9424, R2LDC: 0.996), the process can be described by the Langmuir model, and exhibits the highest removal rate of 97.24% (24.31 mg/g) with 250 mg/L of the initial chloride concentration. The pseudo-first-order and pseudo-second-order, intra-particle diffusion, and mass transfer kinetics models are used to identify the mechanism of the adsorptive removal of the chloride ions. The pseudo-second order model due the correlation coefficients (R2CDC: 0.9217-0.9852, R2LDC: 0.9227-0.9926) can be fitted to the kinetic calculations, and it is applicable for the adsorptive removal of chloride ions by the adsorbents. The thermodynamic calculations show that in a low chloride concentration, the sorption is spontaneous, associative, and endothermic; and in a high concentration, it is unspontaneous, dissociative, and endothermic. The calculated value of free energy (E) for adsorption onto the adsorbents suggests that the reaction rate controls the adsorptive removal of the chloride process rather than diffusion. It can be concluded that these two composites can be used as effective and applicable adsorbents for the adsorptive removal of chloride ions.

The use of blasting cost (BC) prediction to achieve optimal fragmentation is necessary in order to control the adverse consequences of blasting such as fly rock, ground vibration, and air blast in open-pit mines. In this research work, BC is predicted through collecting 146 blasting data from six limestone mines in Iran using the artificial neural networks (ANNs), gene expression programming (GEP), linear multivariate regression (LMR), and non-linear multivariate regression (NLMR) models. In all models, the ANFO value, number of detonators, Emolite value, hole number, hole length, hole diameter, burden, spacing, stemming, sub-drilling, specific gravity of rock, hardness, and uniaxial compressive strength are used as the input parameters. The ANN model results in the test stage indicating a higher correlation coefficient (0.954) and a lower root mean square error (973) compared to the other models. In addition, it has a better conformity with the real blasting costs in comparison with the other models. Although the ANNs method is regarded as one of the intelligent and powerful techniques in parameter prediction, its most important fault is its inability to provide mathematical equations for engineering operations. In contrast, the GEP model exhibits a reliable output by presenting a mathematical equation for BC prediction with a correlation coefficient of 0.933 and a root mean square error of 1088. Based on the sensitivity analysis, the spacing and ANFO values have the maximum and minimum effects on the BC function, respectively. The number of detonators, Emolite value, hole number, specific gravity, hardness, and rock uniaxial compressive strength have a positive correlation with BC, while the ANFO value, hole length, hole diameter, burden, spacing, stemming, and sub-drilling have a negative correlation with BC.

One of the main issues involved during tunnel construction with tunnel boring machines is the tail gap grouting. This gap is between the external diameter of tunnel lining and the excavation boundary that is filled with high-pressure grouting materials. In this work, three different approaches of gap grouting modeling in the FLAC3D software are investigated with a special attention to the influence of the grout material hardening process. In the first approach, the grout is modeled as a liquid during injection, and considering the TBM advancement and its hardening time, the grout characteristics are changed to the properties of the solid grouting. In the second approach, the grouting material from the beginning of injection is considered with the properties of solid grouting in the model, and the liquid phase is ignored. In the third approach, without considering the back-filled grouting area in the model geometry, only the injection pressure is applied to the end of the shield and behind the installed segments. The validity of the approaches is evaluated with respect to the maximum ground surface settlement. All the three approaches estimate different surface settlement but the result of the first approach is closer to the monitoring data. Also as a sensitivity analysis, in this work, we investigate the effect of the elastic modulus of liquid and solid grouting materials on the amount of surface settlement that can help to gain a more accurate insight into the effect of grout mixture.

Spontaneous combustion of coal is one of the most horrifying hazards in coal industries, especially in underground coal mines. Thus having a prior knowledge about the occurrence of this phenomenon in underground coal mines is of crucial importance in preventing this process, loss of life, huge economic loss, and environmental pollution. The aim of this work is to determine the spontaneous combustion of coal potential in the Tabas Parvadeh coal mines in Iran in order to assess the effect of coal intrinsic characteristics on its occurrence. For the purpose of this investigation, the coal samples were collected from Parvadeh I to IV, and the coal intrinsic characteristics of the samples were tested. In order to determine the spontaneous combustion of coal propensity in this case study, the Crossing Point Temperature (CPT) test was used. Then the relation between the coal intrinsic characteristics and the CPT test values was determined. The results obtained showed that the B1 seam in Parvadeh II and C1 seam in Parvadeh III had a high potential of spontaneous combustion of coal potential. These results also show that an increase in the moisture, volatile matter, pyrite, vitrinite, and liptinite contents enhance the spontaneous combustion of coal tendency in these mines. The results obtained have major outcomes for the management of this phenomenon in the Tabas Parvadeh coal mines. Therefore, evaluation of the spontaneous combustion of coal hazards in coal mines should start in the first stage of design and carried on during their whole lifecycle, even after mine closure.