International Journal of Mining & Geo-Engineering
Volume:55 Issue: 2, Summer-Autumn 2021

The mill shell liner type, rotation speed and the amount of its loading are the key factors influencing the charge behavior, consequently the comminution mechanism. In this paper, milling operation of industrial ball mills using Discrete Element Method (DEM) is investigated. First, an industrial scale ball mill with a Smooth liner type is simulated. Then, by changing liner type, i.e. Wave, Rib, Ship-lap, Lorain, Osborn, and Step liners, six other independent simulations are performed. Effects of mill shell liner type on charge shoulder, toe, impact, and head points, also on head height and impact zone length as well as on creation of cascading, cataracting, and centrifuging motions for balls at two different mill speeds, i.e. 70% and 80% of its critical speed (NC) are evaluated. Also, in order to validate simulation results, a laboratory scale mill is simulated. The results indicate that the charge heads are respectively about 240.13, 283.40, 306.47, 278.12, 274.42, 274.42, and 278.12 cm at the simulations performed with Smooth, Wave, Rib, Ship-lap, Lorain, Osborn, and Step liners at 70% of NC. The corresponding values at 80% of NC are as follows: 256.08, 264.56, 313.54, 298.45, 313.54, 311.60, and 283.40 cm. On the other hand, the impact zone lengths are respectively about 33.14, 22.11, 38.63, 35.86, 38.63, 38.63, and 49.59 cm at the simulations performed with above-mentioned liners at 70% of NC. The corresponding values for impact zone lengths at 80% of NC are as follows: 35.86, 27.63, 49.59, 38.63, 33.14, 52.32, and 41.38 cm. Comparison of the simulations related to the laboratory scale mill with experimental results demonstrates a good agreement which validates the DEM simulations and the software used.

The effect of physical parameters such as type of filtration media, solids percent, pressure drop, and pH on resistance to filter cloth (R), specific cake resistance (α), moisture content and cake formation rate were investigated in this paper. Experiments were performed using Vacuum Top-Feed method and during the experiments, no chemicals (flocculants, coagulants, etc.) were used. The optimal response for each factor was considered as the minimum values of the resistance to filter cloth (R), specific cake resistance (α), moisture content and maximum cake formation rate. The results showed that the Cloth A7 (Fiber: Polyester, Weave: Twill) and Cloth A12 (Fiber: Polyester, Weave: Plain) have the best performance among 16 types of filters media. With increasing solid content from 45 to 65%, the resistance to filter cloths of A7 and A12 increase from 26.29 (1/m×〖10〗^10) to 101.39 (1/m×〖10〗^10) and from 25.38(1/m×〖10〗^10) to 245.67 (1/m×〖10〗^10), respectively. The highest rate of cake formation in 65% solids for both cloths was 0.077 (mm/s) for cloth A7 and 0.059 (mm/s) for cloth A12. Also, it was found that the compressibility factor is the same for each cloths, so the difference in the compressibility coefficient of cake depends on the inherent properties of the raw material.

Heavy metal concentrations were investigated for 30 sediments collected from different regions of Mighan playa/lake. The means of Cr, Cu, Ni, Pb, Zn and Cd in sediments of playa/lake were much lower than the soil guideline values of Iran and background values of region (BVR). However, the maximum concentrations of Cr, Cu, Ni, Pb, Zn and Cd were higher than BVR. Only 7% of Cr, Cu, Zn, 27% of Ni, 14% of Pb and 38% of Cd concentration exceeded the BVR. The heavy metal Cr, Zn, Ni and Cd are the most important metals in different land use. About 11% of the samples in the lake land use contain Cr, Ni, Pb and Zn has concentration higher than BVR. The concentration of Cu and Pb in 33% and 67% samples is exceeded the BVR in Tail of Mineral Salts Company. The spatial distribution patterns of Cr, Cu, Ni, Pb, Zn and Cd were generally similar and increase from Mighan playa/lake to the Arak city and mainly affected by anthropogenic sources. Among the six types of land use, the concentrations of Cr, Ni, Zn and Cd in the range land and wastewater sludge were significantly higher than those in the other land use (p <0.05). In factor analysis, Cr, Ni, Zn in factor1, Cd in factor2, Pb, Zn in factor3 were originated from the municipal sewage, industrial plants activities and Arak urban traffic.

It is one of the important tasks to select a suitable mining method for economic and safely extraction of the specific ore deposit. The selection of individual mining methods depends on multiple factors like dip, shape, thickness, depth, grade distribution, RMR (rock mass rating) of ore and adjacent strata, and RSS (rock substance strength) of ore and adjacent strata. The present study aims to analyse the role of two extrinsic factors (safety and capital) in the selection of underground metal mining method. A fuzzy-AHP decision making model is developed to analyse the possible changes in the mining method with different levels of safety and capital. The study considers seven alternatives or mining methods (block caving, sublevel stoping, sublevel caving, room and pillar mining, shrinkage stoping, cut and fill stoping and square set stoping) in the model. The results revealed that the preference level or ranking of different mining method in a particular condition like low safety (SAL), medium safety (SAM), high safety (SAH), low capital (CL), medium capital (CM), and high capital (CH) remains same for different decision-making attitude and uncertainty level.

Ventilation network design is done in manual and computerized methods. Computerized method is based on mathematical approximate methods. Several algorithms were presented in mathematical approximate methods for analyzing of water distribution and ventilation networks. Hardy Cross method is the most commonly model of mathematical approximate method for analyzing of ventilation networks in mine. For faster convergence to at the final result of Hardy Cross method were presented other models such as Wang model, conflation model and Newtonian models (First, third and sixteenth). In this paper is performed an initial review of Hardy Cross method and its modified models. Then first, third, and sixteenth modified models of Newtonian are presented for more accurate analysis of ventilation networks in mines. Finally, second conflation model will be presented as the fastest modified model of Hardy Cross method to achieve at the final result.

Nowadays, Tunnel Boring Machines (TBM) are widely used around the world on account of their high rate of excavation, little impact on the surrounding rock and their high safety standards. The rock mass boreability is considered as one of the main parameters in evaluating the TBMs performance in jointed rock masses .Boreability is a parameter reflecting the interaction between the rock mass and cutting tools. This paper aims to render an account of the effect of Joints Geometrical Parameters on the boreability by use of a database prepared utilizing the data (TBM operation and geological parameters) collected from Kerman Water Conveyance Tunnel projects in Iran. For this purpose, the joint parameters (orientation, spacing, persistence) affecting the boreability have initially been investigated. Then, the total fracturing factors (Bruland) and Persistence classification were used to investigate the effects of all three parameters on the borability. The results showed that the boreability is also increased by increasing the joint persistency. Besides, the effect of fracturing factor ( ) on boreability increases by increasing the joint persistency. In this paper, a new parameter called "Rock Joint Index"(RJI) is also presented according to the analysis performed on the database. The boreability value estimated based on the RJI shows a good agreement with the actual penetration rates.

In recent years, using of the resilience concept has been increased in order to evaluate the response of systems against the failures. Resilience depicts the system ability to return to its normal operational status after failure accruing. According to the literature survey, there are various studies, which have been done in the field of engineering and non-engineering systems, and there is no study about applying resilience concept in the field of mining industry. In this paper, at first, resilience concept has been introduced and then the resilience of the mining fleet of Sungun copper mine has been estimated. Systems performance indicators include reliability; maintainability and supportability have been used in order to resilience estimation. The results showed that the resilience of the entire system for one hour of its function is equal to 83.1% and this value decreases to 37.1% after 10 hours. This means if there is a failure in the system; it will have 83.1% and 37.1% probabilities to be resilience against the failure event after 1 hour and 10 hours of system function.

The Sarcheshmeh copper complex flotation circuit of plant No.1 consists of two identical north and south sections where each includes four rougher (each bank consists of 14 cells), two cleaners (each bank consists of 8 cells), two recleaners (each bank consists of 2 cells), and two scavenger banks (each bank consists of 10 cells). The reduction of feed grade along with a change in the mineralogical composition is the main reason of current lower concentrate grade (24%) compared with the design concentrate grade (32%). Because of a lower feed grade, the amount of rougher concentrate has decreased which in turn has significantly reduced the feed rate to the cleaner, recleaner, and scavenger banks. This has increased the mean residence time of the material in the cleaner section resulting in a lower final concentrate grade. A laboratory study showed that the final concentrate grade can be increased by 2-4% if one cleaner stage is added to the flotation circuit. In this research, based on the laboratory results, one cleaning stage was added to the current flotation circuit. In order to make this modification instrumentally possible in the plant, the final concentrate was gravity transported to the Mo-Cu thickeners. This released two pumps and associated tanks which made the addition of one cleaning stage practicable. Finally, a part of the cleaner and scavenger cells was used as the third cleaning stage. This decreased the residence time in the cleaner and scavenger banks. After implementation of one cleaning stage in the south section of the plant, the performance of the circuit compared with the identical north section. It was found that at the same recovery, the concentrate grade of the south section increased by 2.5%. The promising results led to the implementation of adding one cleaning stage in all sections of the flotation circuit.

Lack of the existence of known mineral prospects in the preliminary stages of mineral exploration is the main problem of data-driven mineral potential modeling methods. On the other hand, applying the expert’s knowledge and judgment in different stages of mineral potential modeling, is the main difficulty of knowledge-driven mineral potential modeling methods. In addition, other difficulties in these methods can be mentioned such as determination of important variables, weighting to various classes of maps or information layers, and so on. Hence, the accuracy of the results of the knowledge-driven modeling methods is highly dependent on the amount of knowledge and experience of the expert. In this study, the principal component analysis (PCA) has been introduced as a knowledge-driven method with the least reliance on the expert’s knowledge for mineral potential modeling. In this method, the expert’s knowledge is only used in the interpretation of the results obtained from the modeling, and is not considered in the first stages of mineral potential modeling and definition of the conceptual model. In the introduced method, the interpretation of the results is conducted based on the positive and negative coefficients of variables in the eigenvalues table. Using these coefficients, it is determined that each principal component (PC) is associated with what type of mineralization. An advantage of this introduced method is to identify various types of mineralization in the area of interest using just one modeling effort. In order to evaluate the efficiency of this method, a region including two geological maps of Kadkan and Shamkan in the south of Neyshabur, northeast of Iran was selected. Two mineralization types including podiform chromite and epithermal gold-antimony mineralization types have been identified using the proposed method that presents more precise results than those of conventional univariate and multivariate geochemical studies.

This study serves the purpose of generating a geochemical Fe-bearing potential map. Stream sediment geochemical survey was employed by collecting 843 samples for analyzing 19 elements and oxides. Taking preprocessing of data (e.g. outlier correction and data normalization) into consideration, a Concentration–Number (C-N) fractal model was used to separate different geochemical populations of Fe2O3, TiO2, V and the main multi-element factor in close spatially association with the Fe targeting. A prediction-area (P-A) plot was drawn for each variable to determine the weight of each geochemical indicator. Results indicate that the main geochemical factor with an ore prediction rate of 73%, has occupied 27% of the Esfordi area as favorable zones for further mining propsectivity. The Esfordi as a favorable Fe-bearing zone is of special interest in the NE of the Bafq mining district that hosts important “Kiruna-type” Magnetite-Apatite deposits. In addition, a synthesized indicators map was prepared through implementing a data-driven multi-class index overlay in a similar fashion to the previous version of the method, upon which geochemical potential zones were mostly in the NE part of the Esfordi, intimately linked with intense fault density map. The significance of this study lies in localizing of the most geochemical favorable zones through simultaneous consideration of the C-N and P-A plots accompanied with the incorporation of known active mines and prospects to determine indicator weight. Of note is that the Mineral Potential Mapping (MPM) has higher efficiency over each geochemical indicator with an ore prediction rate of 78% and area occupation of 22%.

As conventional hydrocarbon reserves are running out, attention is now being paid to unconventional hydrocarbon resources and reserves such as tight sands and hydrocarbon shales for future energy supplies. To achieve this, the identification of tight sand facies is based on zones containing mature hydrocarbons in priority. Organic geochemical methods are the commonest methods to evaluate the quality of these reservoirs. In this study, using a deep learning approach and using petrophysical logs, a suitable classification model for facies quality is presented. Moreover, the proposed method has been compared with two common methods multilinear regression and multilayer perceptron neural network. The results indicated that the accuracy of facies classification using these three methods is about 63%, 71%, and 84% for linear multilinear regression, perceptron multilayer neural network and, deep learning, respectively. Finally, the accuracy of the deep learning networks was optimized using two gravitational search and whale optimization algorithms. It has been shown that the accuracy of deep learning was increased from 84% to 87% and 90.5% using the gravitational search algorithms and whale algorithms, respectively.

The Recovery of nickel from lateritic ores as the main oxide resources has been always debated. Since it consists of 1.74% Ni, 0.14% Co and 40.8% Fe, co-dissolution of iron occurred by using common lixiviation like sulfuric acid. Therefore, some leaching agents should be sought due to promoting a high dissolution of nickel/cobalt and a negligible iron recovery. This research investigates the effect of using organic acids such as gluconic, lactic and citric acid along with sulfuric acid on recoveries of Ni/Co from an iron-rich laterite ore. The results showed that adding sulfuric acid to the optimal combined ratio of the organic acids (gluconic: lactic: citric= 1: 2: 3) to obtain the combined ratio of 6 : 1: 2: 3 (sulfuric: gluconic: lactic: citric acid), simultaneously increasing the temperature from 60 to 90 °C, and increasing the final combined concentration of the acids from 3.5 M to 5 M, significantly increased nickel and cobalt recoveries by 80.4 and 68.7%, respectively, and slightly increased iron extraction by 5.05% all when compared to using the optimal combined ratio of organic acids. The use of 5 M sulfuric acid alone as a leaching agent, at 90 ° C, resulted in an 81.11% increase in iron dissolution than the 6: 1: 2: 3 combination. The results obtained indicated that the reaction rate was controlled by the chemical reaction, and the activation energies of 42.71 kJ/mol for nickel and 84.57 kJ/mol for cobalt were consistent with this conclusion.