فهرست مطالب

Mining and Environement - Volume:9 Issue: 2, Spring 2018

Journal of Mining and Environement
Volume:9 Issue: 2, Spring 2018

  • تاریخ انتشار: 1397/03/28
  • تعداد عناوین: 21
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  • M. Anselme Kamga *, S. Nzali, C. O. Olatubara, A. Adenikinju, E. A. Akintunde, M. P. Kemeng, F. W.D. Nguimatsia, E. A. Ndip, C. Fuanya Pages 293-309
    Cameroon has a strong geological potential for a number of mineral resources that, if well managed, could support economic growth. The country contains potentially large deposits of iron ore, gold, bauxite, diamond, limestone, nickel, and gemstones, and indices of other numerous minerals and precious metals. Despite its geological wealth, mining has never played a major role in Cameroon’s economic development. A study on the state of sustainable development and environmental challenges in the Cameroon mining sector permits the identification of key points for improvement in order to position the country towards achieving a sustainable mining industry in the future. This paper reviews the mining potential, stakeholder participation, legislation, and mining policy in Cameroon mining industry. The methodology involves a single case study focused on the review of sustainable development in the Cameroon mining industry up to date. It includes scientific studies, and reports of ministries and support organizations, national laws, and regulations related to the area of study. Also the corporate sustainability reports of mining companies and mining stakeholders are analyzed. This research work covers the latest developments in terms of the institutional and regulatory frameworks for mining and the environment in the country, history of mining in Cameroon, and evolution and issues of the Environmental and Social Impact Assessment (ESIA) system in the mining sector until 2016. The work concludes with an identification of the current challenges of implementing sustainable development in mining as well as future directions that research works on this area should take.
    Keywords: Mineral Resources, Economic Development, Mining Policy, Environmental, Social Impact Assessment, Sustainable Development
  • R. Solis-Rdoriguez, S. Bello-Teodoro, A. Moreno-Baez, J. I. Galvan-Tejada, J. G. Arceo-Olague, H. Luna-Garcia, O. Alonso-Gonzalez * Pages 311-317
    Precious metals are currently associated with selenium (naumannite, Ag2Se) and tellurium (calaverite, AuTe2; sylvanite, (Au,Ag)2Te4) to form species refractory to cyanidation. The aim of this preliminary work was to study the use of the solvent extraction technique to recover tellurium and selenium ions from a synthetic solution similar to the cyanidation effluents to recycle the free cyanide back to the process. For the extraction of the Se and Te anions, the use of quaternary amines as extractants was evaluated (tallow trimethyl ammonium chloride, Quartamin TPR; hexadecyl trimethyl ammonium chloride, Amine F; and trioctyl methyl ammonium chloride, Aliquat 336) employing nonylphenol as a modifier in the organic phase (iso-octane). The results obtained showed that the extraction was strongly affected by the pH and that it was possible to recover up to 83% of Se and 10% of Te with Quartamin TPR from two synthetic solutions containing 23 mg/L of Te and 20 mg/L of Se with a molar cyanide:metal ratio of 1:4 at pH 11, a ratio of aqueous/organic (A/O) = 1 (V/V) and an extractant concentration of 0.022 mol/L. A maximum distribution coefficient (D) of 4.97 was obtained at pH 11. The McCabe-Thiele diagram indicates that two theoretical extraction stages are necessary to obtain a good extraction of Se complexes using Quartamin TPR.
    Keywords: Solvent Extraction, Tellurium Extraction, Selenium Extraction
  • U. Yenial *, G. Bulut Pages 319-330
    Two common waste materials, red mud and fly ash, were used to produce a new nano-hybrid adsorbent by heat treatment with alkali addition. The new zeolitic structure formation of the hybrid adsorbent was revealed using the BET surface area, XRD, and SEM analyses. This hybrid adsorbent was utilized to remove arsenic from synthetic and real waste waters by batch and column adsorption experiments. The parameters such as the pH, contact time, and effect of the co-existing ions were investigated. Slightly acidic media favored arsenic adsorption by the hybrid adsorbent, the same as the individual use of fly ash and red mud. The effects of ions such as Fe3, Cu2, Cl-, SO42-, and PO43- were investigated as the co-existing ions. It was found that arsenic adsorption increased with cationic ions and decreased with anionic ions according to their valance charge. The intra-particle diffusion model showed that adsorption took place at three different rates depending on time. The hybrid adsorbent was formed as a pellet and utilized in a column for treatment of arsenic containing real waste water. The hybrid adsorbent derived from mineral wastes was more successful than their individual usages.
    Keywords: Red Mud, Fly Ash, Wastewater, Arsenic, Hybrid
  • J. Gholamnejad *, A. Azimi, M.R. Teymouri Pages 331-338
    Stockpiling and blending play a major role in maintaining the quantity and quality of the raw materials fed into processing plants, especially the cement, iron ore and steel making, and coal-fired power generation industries that usually require a much uniformed feed. Due to the variable nature of such materials, they even come from the same source and the produced ores or concentrates are seldom homogeneous enough to be directly fed to the processing plant ore furnaces. Processing plants in iron ore mines need uniform feed properties in terms of each variable (in this work, iron phosphorous ratio and Fe content in magnetite phase) grade of ore, and therefore, homogenization of iron ore from different benches of an open pit or ore dumps has become an essential part of modern mine scheduling. When ore dumps are considered as an ore source, the final grade of the material leaving the dump to the blending bed cannot be easily determined. This difficulty contributes to mixing the materials of different grades in a dump. In this work, the ore dump elements were treated as normally distributed random variables. Then a stochastic programming model was formulated in an iron ore mine in order to determine the optimum amount of ore dispatched from different bench levels in open pit and also four ore dumps to a windrow-type blending bed in order to provide a mixed material of homogenous composition. The chance-constrained programming technique was used to obtain the equivalent deterministic non-linear programming problem of the primary model. The resulting non-linear model was then solved using LINGO. The results obtained showed a better feed grade for the processing plant with a higher probability of grade blending constraint satisfaction.
    Keywords: Stochastic Programming, Iron Ore Mine, Homogenization, Processing Plant
  • M. Heshami, R. Ahmadi * Pages 339-348
    The aim of this work is to investigate the effect of thermal treatment on the grinding behavior of manganese ore in the various size fractions of -1.7.18, -1.18.6, -0.6.3 and -0.3 0.15 mm. Breakage Function Determination Software (BFDS) is used to calculate the selection function of the experiment. The results of SEM analysis show the micro-cracks in the thermally treated manganese sample, and DTA/TG analysis show that heating at 750 °C leads to dehydroxylation of montmorillonite, and decomposition of calcite and decomposition of montmorillonite to silicate minerals occur at 850 °C. Montmorillonite mineral with a hardness of 2 is turned into silicate minerals with an average hardness of 7. Therefore, it can be seen that the thermal treatment leads to a decrease in the specific rate of breakage from 1.04 min-1 to 0.65 min-1 (approximately to 37%) for a size fraction of -0.300 0.15 mm. It; can be expressed that the thermally treated sample is broken more slowly than the untreated sample. Also, parameter “A” is the maximum Si value, decreasing for the heated sample from 4.36 min-1 to 4.28 min-1. The selection function results show that all size fractions of this material follow a first-order kinetics.
    Keywords: Thermal Treatment, Specific rate of Breakage, Grinding Kinetics, Breakage Function Determination Software, Manganese Ore
  • H. Dehghani * Pages 349-360
    Forecasting the prices of metals is important in many aspects of economics. Metal prices are also vital variables in financial models for revenue evaluation, which forms the basis of an effective payment regime using resource policymakers. According to the severe changes of the metal prices in the recent years, the classic estimation methods cannot correctly estimate the volatility. In order to solve this problem, it is necessary to use the artificial algorithms, which have a good ability to predict the volatility of various phenomena. In the present work, the gene expression programming (GEP) method was used to predict the copper price volatility. In order to understand the ability of this method, the results obtained were compared with the other classical prediction methods. The results indicated that the GEP method was much better than the time series and multivariate regression methods in terms of the prediction accuracy.
    Keywords: Copper price, Gene expression programming, Forecasting, Time Series
  • M. Yazdi, A. Bahrami, Z. Alaminia *, H. Jamali, M. A. Mackizadeh Pages 361-369
    This research work introduces the Early Triassic, Late Triassic-Early Jurassic, and Early Cretaceous silica-rich sand levels at east and central Alborz, Kopeh-Dagh, and Central Iran, and compares them with the Permian silica-rich sand level in the Chirouk mine at east Iran. Ghoznavi and Gheshlaq loose sand in Alborz (Early Triassic-Early Jurassic), Soh quartzite in Central Iran (Early Triassic-Early Jurassic), Firuzeh sands with mud levels in Kopeh-Dagh (Early Cretaceous), and Sarnaza in Central Alborz (Late Triassic-Early Jurassic) silica-rich levels are studied in this work. Geochemical analysis and physical factors of the studied silica levels are checked regarding grain size, heat resistance, and steel molding. The laboratory and industrial methods used for washing, sieving, heating, molding, and controlling the purity of refractory sand levels show that the main difficulty of these levels within the molding process is intra-grain cracks, which spoils the alloy’s final product. The Early Triassic level in the Ghoznavi area has a high purity but the average grain size is below the steel molding standard. The Late Triassic to Early Jurassic levels in Alborz and Central Iran are oversize with grain cracks but can be fixed by the industrial refinery methods. The size of Early Cretaceous refractory sands of Firuzeh (Kopeh-Dagh) is below the standard molding process; it can be fixed by the washing and refinery methods. The systematic exploration methods show that all the studied silica-rich sand levels have an intra-grain collapse within the molding process. Final test shows that the Chirouk silica-rich levels can be used as refractory sand for cast and molding in the steel industry.
    Keywords: Mesozoic refractory sand, Heat resistance, Grain size, Iran
  • H. Khalili, P. Afzal * Pages 371-378
    The main goal of this research work was to detect the different Cu mineralized zones in the Sungun porphyry deposit in NW Iran using the Spectrum-Volume (S-V) fractal modeling based on the sub-surface data for this deposit. This operation was carried out on an estimated Cu block model based on a Fast Fourier Transformation (FFT) using the C and MATLAB programing. The S-V log-log plot was generated and six Cu populations were distinguished. Based on the S-V log-log plot obtained, different mineralized zones were detected in the Sungun deposit. Copper mineralized zones in the porphyry and skarn types commenced from 0.12% and 1.3%, respectively. A supergene enrichment zone began form 0.82%; it was located in the eastern part of this deposit. The enriched skarn zones were situated in the eastern and SE parts of the Sungun deposit that overlapped the intersection of cretaceous limestones and porphyry stock. Overlapping between the resulting zones derived via the S-V fractal model and geological zones and evidences were calculated using the logratio matrix, which indicated that the S-V fractal model had proper results for detection of the mineralized zones.
    Keywords: Spectrum, Volume Fractal Model, C++ programming, Cu mineralized zones, Sungun
  • M. Hosseini *, A. R. Khodayari Pages 379-391
    The fracture mechanics examines the development and expansion of cracks in solids and how they affect the deformation of materials. The stress intensity factors at the tip of the crack and the critical stress intensity factors or fracture toughness of materials are considered in the relevant criteria. There are three main modes of applying forces to a crack including the tensile mode, shear mode, and mixed mode. Mode II fracture toughness, which is also called the shear mode, is an important parameter for investigating the rock behaviors. This parameter is used in many different areas such as mining and tunneling. Several methods have been proposed for determining the mode II fracture toughness. In this work, the Punch-True-Shear (PTS) test, standardized by the International Society for Rock Mechanics, was used to determine the fracture toughness while the confining pressure is present. The studied sample was the Lushan sandstone. In this work, notchd cylindrical specimens were prepared for PTS testing. In order to investigate the effect of confining pressure, some tests were conducted in the presence of the confining pressures of 0, 3, 5, 7, and 10 MPa, and to check the effect of temperature, some tests were conducted under 1, 5, and 10 heating and cooling cycles at 60, 100, and 150 ˚C as well as at the ambient temperature (25 °C). The confining pressure of 3 MPa was used in all the tests to examine the effect of temperature. The analyses results showed that with increase in the confining pressure, the mode II fracture toughness and the fracture energy would increase as well. By increasing the number of heating-cooling cycles, the mode II fracture toughness as well as the fracture energy would decrease leading to a reduced fracture toughness and energy for all the three modes of heating specimens up to 60, 100, and 150 ˚C. The effect of the number of heating-cooling cycles on reducing the fracture toughness and fracture energy was greater than the effect of temperature.
    Keywords: Fracture toughness, Mode II, Confining pressure, Temperature, Sandstone
  • M. Ghanbari, H. Naderi *, M. Torabi Pages 393-402
    Solvent extraction of copper from the copper leach solution obtained from the ammoniacal carbonate leaching of the Sarcheshmeh copper concentrate was carried out, and the performance of CP-150, LIX984N, and Kelex100 as well as the effects of different parameters involved were investigated. According to the results obtained, the extraction kinetics of all the three extractants was fast. High concentrations (7.5%, V/V) of CP-150 and Kelex100 were required to completely extract copper, while only 1% of LIX984N was sufficient. Addition of hexane to the diluent decreased the capability of CP-150 to extract copper, while it showed less effects on LIX984N and Kelex100. A desirable stripping of copper from the loaded organic phase could be obtained using H2SO4 solution.
    Keywords: Copper, Ammoniacal carbonate leaching, Kelex 100, LIX984N, CP, 150
  • M. P. Sadr *, M. Nazeri Pages 403-416
    The Dolatabad area located in SE Iran is a well-endowed terrain owning several chromite mineralized zones. These chromite ore bodies are all hosted in a colored mélange complex zone comprising harzburgite, dunite, and pyroxenite. These deposits are irregular in shape, and are distributed as small lenses along colored mélange zones. The area has a great potential for discovering further chromite resources. Therefore, the current work endeavors to delineate the favorable zones of podiform chromite mineralization to focus on the detailed exploration surveys. In order to achieve this goal, the machine learning random forests algorithm was adapted to integrate the footprints of mineralization in various exploration datasets. The genetic characteristics of podiform chromite deposits were used to define the exploration criteria. These defined criteria were then translated to a set of exploration evidence layers. The competent exploration evidence layers, i.e. those with remarkable positive spatial associations with mineralization, were then recognized using distance distribution analysis. Respecting the location of known chromite mineralizations and competent exploration evidence layers, a predictive random forests model was trained and then applied to predict the favorable zones of chromite prospectivity. The delineated targets were found to occupy 19% of the studied area, in which all the known chromite mineralizations were delimited. Consequently, it is worthy to follow up the detailed exploration surveys within the delineated zones.
    Keywords: Podiform Chromite Deposits, Random Forests, Mineral Prospectivity Mapping
  • S. Torbati *, S. Alipour, M. Rostami, S. Hajializadeh Pages 417-429
    The Agh-Dareh and Zarshouran mines are two known active gold deposits in Takab, NW Iran. In the present study, the potentials of two species of Astragalus (A. microcephalus from Agh-Dareh and A. effusus from Zarshouran mines), as the dominant plants grown in these areas, were assessed for the bio-accumulation of the major, trace, and rare earth elements (REEs). The plant and soil samples were collected from the mining areas and analyzed by inductively coupled plasma-mass spectroscopy (ICP-MS). According to the results obtained, A. effusus in the Zarshouran mine passed a high ability in the accumulation of some major elements such as S, P, K, Ca, and Zn. Although the amounts of the examined trace elements in the soil samples were more than those in the shoots of both examined plants, the potential of A. microcephalus in the absorbance and translocation of Cd, U, Tl, and Pb was more than that for A. effusus. It became clear that the performance of A. microcephalus from the Agh-Dareh mine in the uptake and transportation of REEs was more than that for A. effusus from the Zarshouran mine; also both plant species absorbed and transported much more light REEs than heavy REEs did. According to the results obtained, the present study provides some geochemical findings about the substrate and leads to the increasing information about the plants as a useful indicator of metal mineralization.
    Keywords: Astragalus, Bio, accumulation, Gold Deposits, Agh, Dareh, Zarshouran
  • M. Mohseni, M. Abdollahy *, R. Poursalehi, M. R. Khalesi Pages 431-439
    The reactivity of the protonated and hydroxylated sphalerite (1 1 0) surface with xanthate was simulated using the density functional theory (DFT). The difference between the energy of the lowest unoccupied molecular orbital of the sphalerite surface and the energy of the highest occupied molecular orbital of xanthate ( was used to compare the reaction capability of xanthate with fresh and functionalized surfaces. The Mulliken atomic charge analysis was used to provide an in-depth insight into the effects of –H and –OH- groups on the reactivity of Zn atoms at the sphalerite surface. The values for different systems showed that the protonated surfaces exposed a higher reactivity with xanthate than the fresh and hydroxylated surfaces. The results of the Mulliken atomic charge analysis demonstrated that after the formation of –H and –OH- contained groups on the sphalerite surface, the surface atoms found a new charge due to the reduction and oxidation mechanism. In addition, the results obtained revealed that the electrophilicity of Zn atoms after the ion adsorption could be considered as a key factor in the reactivity of the sphalerite surface with xanthate. The DFT-based calculations also showed that different alkyl groups of xanthate had no significant influence on the reactivity of their head groups. The findings of this research work provided insights into the reactions of the sphalerite surface with xanthate.
    Keywords: DFT, Surface species, Xanthate collector, Surface reactivity, Mineral surface
  • M. B. Eslami Andargoli, K. Shahriar *, A. Ramezanzadeh, K. Goshtasbi Pages 441-456
    During the recent decades, the design and construction of underground spaces into rock salt have been particularly regarded for storing petroleum fluids, natural gas, and compressed air energy, and also for disposing nuclear and chemical wastes. The rock salt hosting such spaces will be subjected to various types of monotonic/cyclic, short-term/long-term stresses during the construction and/or operation phases. On this basis, it is necessary to investigate the mechanical behavior of the rock salt under the effects of various monotonic short-term/long-term stresses. Out of the most important factors affecting the creep behavior of rock salt are the composition of minerals and size of the crystals comprising the rock salt, humidity, temperature, time, loading scheme, loading rate, strain rate, and loading period. In the present research work, a loading scheme and a loading period were considered. On this basis, in order to achieve a true understanding of the creep behavior of rock salt, it is necessary to determine the creeping coefficients via laboratory tests. Thus, twenty cylindrical (length to diameter ratio > 2) specimens of rock salt were prepared for conducting the creep tests. Two stepwise short-term creep tests (each at three stress levels, namely 4.4, 10.1, and 11.9 MPa, and 7.5, 12, and 17 MPa, respectively) and eighteen long-term creep tests (at six stress levels, namely 5.5, 7.5, 10, 12, 14, and 18 MPa) were conducted. Then, first, the creep coefficients were determined according to the Lubby 2 constitutive model. These coefficients were adjusted using the results of the creep tests. Afterwards, a creep experimental model was presented using linear and nonlinear regression of the creep test data. For validation of the results obtained, both the adjusted Lubby 2 constitutive model and the proposed experimental model were compared with the results obtained for the creep tests. Both models had fairly good agreements with the data for the creep tests at a determination factor of about 93%.
    Keywords: Rock Salt_Creep Test_Experimental Model_Lubby 2 Model_Creep Coefficients
  • E. Farrokh * Pages 457-472
    The study of downtime and subsequently machine utilization in a given project is one of the major requirements of an accurate estimation of TBM performance and daily advance rate. Interestingly, while it is very common to report the components of downtime when discussing a tunneling project in the literature; there has not been a great amount of in-depth studies on this topic in the recent years. This work presents an in-depth analysis of the different components of hard rock TBM tunneling downtime on the basis of the information about several TBM tunneling projects from around the world including some that are underway or completed in the recent years. This includes the comparison of the recorded downtimes with those predicted by the existing models for these tunnels. The results of this comparison show that with the existing models, there is a poor correlation between the predicted and the actual downtime component values. This indicates that the existing models might be outdated or, in some cases, incompatible with the newly developed technologies. In order to provide a more accurate downtime model, an in-depth statistical analysis of the information about the same tunnels, used for the comparative studies, is conducted to develop the new “hard rock TBM downtime model”. This model includes a set of formulas and tables as well as some charts to predict different activities’ downtimes for three major hard TBM types including open TBM, single-shield TBM, and double-shield TBM. The comparison between the new model predictions and the actual values show a good agreement. The results of this work can be very helpful for the evaluation of time and cost to complete a TBM tunneling project, especially when the downtime is expected to be high.
    Keywords: Tunnel, TBM, Advance rate, TBM Utilization, Downtime
  • M. Mohammadiun *, B. Dahrazma, Seyed F. Saghravani, A. Khodadadi Darban Pages 473-484
    Use of nanotechnology has proven to be a promising approach toward remediation of all phases of environment. The aim of this work is to investigate the effects of different parameters on using iron III oxide nanoparticles in a continuous flow configuration for the removal of Cd2 ionsfrom contaminated soils. Also selective sequential extraction tests are carried out to evaluate the nanoparticle tendency to remove cadmium from different fractions of soils. In order to achieve this goal, a specific flow rate of a nanoparticle solution was passed through a soil sample in a column with 3 cm diameter and 4 cm height. Up to 100% of cadmium removal was achieved by providing a nano-fluid concentration of 500 ppm, pH of 6.5, treatment duration of 24 hours, and flow rate of 0.5 mL/min. Evaluation of the results obtained showed that the tendency of the iron oxide nanoparticles to remove cadmium from different fractions of contaminated soil was in the order of exchangeable > carbonates > oxides and hydroxides > organic matter > residual. The results obtained from this work can be used to develop an appropriate remediation protocol for contaminated soils.
    Keywords: Selective Sequential Extraction, Iron(III) Oxide Nanoparticles, Continuous Flow Configuration, Cd2+ Removal
  • M. Noroozi *, R. Rafiee, M. Najafi Pages 485-497
    Various structural discontinuities, which form a discrete fracture network, play a significant role in the failure conditions and stability of the rock masses around underground excavations. Several continuum numerical methods have been used to study the stability of underground excavations in jointed rock masses but only few of them can take into account the influence of the pre-existing natural fractures. In this work, the pre-existing fractures are explicitly modeled as a Discrete Fracture Network (DFN) model, which is fully coupled with the FEM modeling for stability analysis of support systems in a diversion tunnel at the Rudbar Lorestan dam site. Hence, at first, using the surveyed data in the diversion tunnel and an estimation of the suitable probability distribution function on geometric characteristics of the existing joint sets in this region, the 3D DFN model was simulated using the stochastic discrete fracture networks generator program, DFN-FRAC3D. In the second step, a coupled 2D Finite Element Method and the prepared stochastic model were used for analysis of existent (based on technical reports) recommended support systems. The objective here is to grasp the role of the fracture networks on the results of the tunnel stability analysis using FEM modeling and also to compare the results with those obtained through stability analysis without considering the effect of fractures.
    Keywords: Tunnel Stability Analysis, Finite Element Method, Discrete Fracture Network
  • M. Jahangiri *, Seyed R. Ghavami Riabi, B. Tokhmechi Pages 499-511
    Bearing in mind that lack of data is a common problem in the study of porphyry copper mining exploration, our goal was set to identify the hidden patterns within the data and to extend the information to the data-less areas. To do this, the combination of pattern recognition techniques has been used. In this work, multi-layer neural network was used to estimate the concentration of geochemical elements. From 1755 surface and boreholes data available, analyzed by ICP, 70% was used for training, and the rest for testing. The average accuracy of estimators for 22 geochemical elements when using all data was equal to 75%. Based on validation, the optimal number of clusters for the total data was identified. The Gustafson-Kessel (GK) clustering was used to design the estimator for the geochemical element concentrations in different clusters, and the clusters were selected for estimation. The results obtained show that using GK, the estimator's average accuracy increase up to 84%. The accuracy of the elementsZn, As, Pb, Mo, and Mn with low accuracies of 0.51, 0.62, 0.64, 0.65, and 0.68 based on all data were developed to 0.76, 0.86, 0.76, 0.80, and 0.71 with the clustered data, respectively. The mean square error using all the data was 0.079, while in the case of hybrid developed method, it decreased to 0.048. There were error reductions in Al from 0.022 to 0.012, in As, from 0.105 to 0.025, and from 0.115 to 0.046 for S.
    Keywords: Clustering algorithm, Estimation Precision Improvement, Gustafson, Kessel, Geochemical Elements Estimation, neural network
  • M. Abedini *, M. Ziaii, Y. Negahdarzadeh, J. Ghiasi-Freez Pages 513-525
    The porosity within a reservoir rock is a basic parameter for the reservoir characterization. The present paper introduces two intelligent models for identification of the porosity types using image analysis. For this aim, firstly, thirteen geometrical parameters of pores of each image were extracted using the image analysis techniques. The extracted features and their corresponding pore types of 682 pores were used for training two intelligent models, BPN (back-propagation network) and SAE (stacked autoencoder). The trained models take the geometrical properties of pores to classify the type of six porosity types including
    intra-particle, inter-particle, vuggy, moldic, biomoldic, and fracture. The MSE values for the BPN and SAE models were found to be 0.0042 and 0.0038, respectively. The precision, recall, and accuracy of the intelligent models for classifying the types of pores were calculated. The BPN model was able to correctly recognize 193 intra-particle pores out of 197 ones, 45 inter-particle pores out of 50 ones, 7 vuggy pores out of 9 ones, 10 moldic pores out of 12 ones, 2 biomoldic pores out of 3 ones, and 6 fractures out of 7 ones. Also the SAE model was able to correctly classify 193 intra-particle pores out of 197 ones, 46 inter-particle pores out of 50 ones, 8 vuggy pores out of 9 ones, 10 moldic pores out of 12 ones, 3 biomoldic pores out of 3 ones, and 7 fractures out of 7 ones. The results obtained showed that the SAE model carried out a bit more accuracy for classification of the inter-particle, vuggy, biomoldic, and fracture pores.
    Keywords: porosity classification, image analysis, neural network, deep learning, stacked autoencoder
  • M. M. Tahernejad *, M. Ataei, R. Khalokakaie Pages 527-537
    In the context of open-pit mine planning, uncertainties including commodity price would significantly affect the technical and financial aspects of mining projects. A mine planning that takes place regardless of the uncertainty in price just develops an optimized plan at the starting time of the mining operation. Given the price change over the life of mine, which is quite certain, optimality of the proposed plan will be eliminated. This paper presents a risk-averse decision-making tool to help mine planners in mining activities under price uncertainty. The objective is to propose mine planning in a way that a target Net Present Value (NPV) is guaranteed. In order to reach this goal, Information Gap Decision Theory (IGDT) is developed to hedge the mining project against the risk imposed by the information gap between the forecasted and actual price. The proposed approach is of low sensitivity to the price change over the life of mine, and can use the estimated prices with uncertainty. A case study at an existing iron mine demonstrates the performance of the proposed approach. The results obtained showed that the proposed method could provide a robust solution to mine planning under price uncertainty. Moreover, it was concluded that the method could present more reliable mine plans under condition of price uncertainty.
    Keywords: IGDT, Open, Pit, mine planning, uncertainty modelling, price uncertainty
  • S. Nazari, Seyed Ziaedin Shafaei *, M. Gharabaghi, R. Ahmadi, B. Shahbazi Pages 539-546
    In this work, the effects of the types of frother (MIBC, pine oil, and A65) and operational parameters (impeller speed and air flow rate) on the flotation of quartz coarse particles was investigated using nano bubbles (NBs). Quartz particles of the size of -425흎 mm and three types of frother were used for the flotation experiments. Also the impeller speed was 600 to 1300 rpm, and the air flow rates were 30 and 60 L/h. In the absence of NBs, the maximum recovery was achieved with the pine oil frother, an impeller speed of 1000 rpm, and an air flow rate of 60 L/h. In the presence of NBs, the maximum recovery was achieved using pine oil at an impeller speed of 900 rpm and an air flow rate of 30 L/h. However, increasing the recovery in the presence of NBs, compared to the absence of NBs for MIBC, was more than the other two frothers, and the recovery using this frother to increase up to 25% but using pine oil, the recovery increased up to 23%. The lowest recovery in the presence of NBs was obtained using A65. Also the use of NBs increased recovery in all the three fractions compared to the absence of NBs but the presence of NBs increased the recovery of particles with size of -212흎 mm more than the particle size in the ranges of -300� and -425� mm.
    Keywords: Flotation, Nano Bubbles, Frother type, Particle size, Operational parameters