Mineral Processing
M. R. Heydartaemeh
Abstract
In this research work, the Ni-Zn Ferrite Mineral Nanoparticles (NZFMN), as a novel nanoadsorbent, was used for the removal of the Green Malachite (GM) dye from aqueous solutions by in a batch and fixed bed column. Firstly, the NZFMN adsorption properties were investigated. The effects of the process ...
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In this research work, the Ni-Zn Ferrite Mineral Nanoparticles (NZFMN), as a novel nanoadsorbent, was used for the removal of the Green Malachite (GM) dye from aqueous solutions by in a batch and fixed bed column. Firstly, the NZFMN adsorption properties were investigated. The effects of the process parameters including the contact time, adsorbent dosage, solution pH, and GM initial concentration were also studied. Thence, GM was quantitatively evaluated using the Freundlich and Langmuir isotherms and the pseudo-first- and second-order models. The adsorption data for the adsorption equilibrium was found to be described well using the Freundlich isotherm model. The results obtained for the AFM and SEM analyses showed that the particle size was less than 100 nm. Also the BET analysis showed that the surface area for NZFMN was 120 . The results obtained also showed that the adsorption capacity and removal percentage of GM on NZFMN from wastewater was about 90%. Consequently, NZFMN was found to be a good adsorbent for wastewater purification.
Mineral Processing
M. Jahani Chegeni
Abstract
A deeper understanding of the milling operation of ball mills helps mineral processing engineers to control and optimize them, and therefore, reduce their consuming power. In this work, the milling operation of ball mills is investigated using two methods, i.e. DEM and combined DEM-SPH. First, a pilot ...
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A deeper understanding of the milling operation of ball mills helps mineral processing engineers to control and optimize them, and therefore, reduce their consuming power. In this work, the milling operation of ball mills is investigated using two methods, i.e. DEM and combined DEM-SPH. First, a pilot scale ball mill with no lifter is simulated by both methods. Then another pilot scale ball mill with eight rectangle lifters is simulated again by both methods. The effects of lifters on ball shoulder and toe points as well as on creation of cascading and cataracting movements for balls are studied by both methods. At the present time, there is not enough measured data available for dense slurries interacting with the coarse particulates available in the public domain that can be used adequately to validate these types of predictions. The results obtained indicated that fluid slurry in the mill lowered the charge shoulder by about 28 cm and 25 cm in the no-lifter and eight-lifter cases, respectively. However, it raised the charge toe by about 36 cm and 6 cm in the no-lifter and eight-lifter cases, respectively.
S. Mohammadi; M. Babaeian; M. Ataei; K. Ghanbari
Abstract
This work incorporates the DEMATEL-MABAC method for quantifying the potential of roof fall in coal mines by means of the coal mine roof rating (CMRR) parameters. For this purpose, considering the roof weighting interval as a quantitative criterion for the stability of the roof, the immediate roof falling ...
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This work incorporates the DEMATEL-MABAC method for quantifying the potential of roof fall in coal mines by means of the coal mine roof rating (CMRR) parameters. For this purpose, considering the roof weighting interval as a quantitative criterion for the stability of the roof, the immediate roof falling potential was quantified and ranked in 15 stopes of Eastern Alborz Coal Mines Company. In this regard, on the basis of the experts’ judgments, the fuzzy DEMATEL method was used for designation weights of the parameters, and the MABAC method was incorporated to quantify and rank the stopes (alternatives). “UCS of roof” and “joint spacing” in the immediate roof were found to be the most important parameters that controlled roof falling in stopes; and “joint persistence” was also found to be a quite significant parameter. Finding confirms that overall strength of rood rock mass plays a main role in the falling potential. Comparison of the coefficients of determination (R2) between the weighting interval and proposed model with that and original CMRR indicated more than 15% increase, which represented that the new proposed model was more accurate to quantify roof quality. The findings of this work show that using this combined method and specializing the CMRR method for a given mine geo-condition to assess the quality of the roof and its potential of collapse possesses a higher performance when compared with the original CMRR method.
A. Moeini; S. Mohammadnejad
Abstract
A comprehensive utilization of concentrated seawater is crucial in order to promote the development of the desalination industry as a key solution to global freshwater. Debromination of the desalination plant effluent as well as the bromine product extraction are two parallel goals, which have been the ...
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A comprehensive utilization of concentrated seawater is crucial in order to promote the development of the desalination industry as a key solution to global freshwater. Debromination of the desalination plant effluent as well as the bromine product extraction are two parallel goals, which have been the subject of many research studies as well as industrial operations. In this investigation, bromine extraction is investigated experimentally form the effluent of the Konarak desalination plant located in Chabahar bay, Iran. For this purpose, an air blow-out method is used, and the effects of the operating parameters including the temperature, pH, and chlorine gas flow rate are examined in a continuous reactor. The parameters are optimized, and the trend is discussed in details. The bromine concentration of the sample collected from the Pozm Tiyab area, close to the plant discharge point, has been determined to be 1.172 g/L using ion chromatography. A pre-concentration procedure is conducted in order to reach a concentration of 3.100 g/L by evaporation. A reactor with the dimensions of 60 mm × 800 mm is designed and assembled for the experimental studies. In order to investigate the operating parameters, a central composition design (CCD) method is used. Among the factors studied, only the chlorine gas flow rate has a substantial effect on the bromine recovery, and the effects of the other two factors are negligible in the pH range of 2-3 and the temperature range of 50-70 °C. At the three chlorine concentrations of 1, 1.5, and 2 L/min, the bromine production increases almost linearly with the increasing chlorination injection rate. The Br2 gas is recovered with a maximum rate of 93.8% and a bromine loss of 185 mg/L in the mother liquid. The optimum operating parameters to achieve this recovery are a pH of 2.5, a temperature of 60 ˚C, and a chlorine gas flow rate of 1.5 L/min.
F. Ghadimi; A. Hajati; A. Sabzian
Abstract
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 ...
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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.
Blessing olamide Taiwo; Raymond O Aderoju; Olutosin Mojisola Falade; Yewuhalashet Fissha; O B Ogunyemi; A O Omosebi; S. Omeyoma; Oluwatomisin Victoria Adediran; H A Bamidele; Michael Ogundiran
Abstract
Overburden material is typically removed in surface mining operations to expose the primary ore deposit. Because of the presence of trace minerals, environmental pollution and acid drainage are caused when the overburdened materials are removed from the mine site and transported to another location. ...
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Overburden material is typically removed in surface mining operations to expose the primary ore deposit. Because of the presence of trace minerals, environmental pollution and acid drainage are caused when the overburdened materials are removed from the mine site and transported to another location. In order to promote the economic and environmental sustainability of dolomite mining, the waste materials must therefore be evaluated for their environmental impact and potential industrial application. Akoko Edo Nigeria is known for its large production of dolomite and carbonate rock with large tonnage waste. The hydrogeochemical and geotechnical analysis of selected mine in this area is performed by randomly collecting and analyzing soil and water samples from four exploration drill holes using an atomic absorption spectrophotometer. The geotechnical analysis results show that dolomite waste soil is suitable for constriction material addictive such as road subgrade, dam design, highway, and other construction work. According to the study's findings, the mine water is slightly polluted, as measured by both the Overall Index of Pollution (OIP) and the Pollution Load Index (PLI). The chemical analysis of the mine pit water also reveal that the mean value of electrical conductivity, TDS, iron, manganese, copper, and lead all exceed the WHO and SON standards for a safe drinking water. A new pollution assessment model with suitable prediction correlation accuracy (R2= 0.76, mean average error = 0.27) is also developed in this work.
Exploration
Devraj Dhakal; Kanwarpreet Singh
Abstract
Landslides pose significant risks to human life, infrastructure, and the environment, particularly in geologically unstable regions like the Himalayas. This study aims to develop and validate landslide susceptibility maps using Frequency Ratio (FR) and Information Value (IV) models within a GIS framework. ...
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Landslides pose significant risks to human life, infrastructure, and the environment, particularly in geologically unstable regions like the Himalayas. This study aims to develop and validate landslide susceptibility maps using Frequency Ratio (FR) and Information Value (IV) models within a GIS framework. Employing high-resolution geospatial data, including geomorphological, topographical, and hydrological factors derived from high-resolution digital elevation models (DEMs) and other geospatial datasets. The susceptibility maps were classified into five categories: Low, Moderate, High, Very High, and Extremely High. The models were trained and validated using a landslide inventory of 1313 landslide events, with a 70:30 split for training and testing datasets. The predictive performance of the models was evaluated using the Area Under the Curve (AUC) of the Receiver Operating Characteristic (ROC) curve, yielding AUC values of 84.1 for the FR model and 83.9 for the IV model. The Landslide Density Index (LDI) further confirmed the models' reliability, indicating higher landslide densities in the predicted high-susceptibility zones. The study demonstrates that both FR and IV models are effective tools for landslide susceptibility mapping and its validation. The findings highlight the FR model's superior predictive accuracy in this specific area. Future research should leverage advanced machine learning techniques, such as XGBoost, Random Forest (RF), Naive Bayes (NB), and K-Nearest Neighbors (KNN), to enhance the reliability and precision of landslide susceptibility models.
Exploitation
Morteza Javadi; Ashkan Shahpasand; Shahrbanou Sayadi; Arash Shahpasand
Abstract
The stratified-sedimentary rock mass, as the typical host ground of coal mine tunnels, is characterized by highly non-isotropic deformation due to the very persistent discontinuity of bedding planes. This study evaluates the effect of tunnel location relative to the host ground strata on the excavation-induced ...
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The stratified-sedimentary rock mass, as the typical host ground of coal mine tunnels, is characterized by highly non-isotropic deformation due to the very persistent discontinuity of bedding planes. This study evaluates the effect of tunnel location relative to the host ground strata on the excavation-induced displacements around a coal mine tunnel driven along the inclined coal seam. To achieve this goal, a calibrated finite element method (FEM) numerical model based on field monitoring displacements was developed for the coal mine tunnel at a depth of 300 m. This calibrated numerical model was then utilized to investigate the effect of the horizontal location of the tunnel on the induced displacement field through sensitivity analysis. Finally, the sensitivity analysis results were compared in terms of displacement components around the tunnel. The results of this study demonstrate a reasonable level of accuracy (for practical demands) of the calibrated numerical model, with an average error of about 8% for maximum displacements at measured points. The numerical models show an asymmetric spatial distribution of displacements around the tunnel due to the anisotropy of the rock mass, especially in the case of inclined layers. The arrangement of weak-strength coal and intercalary stone layers relative to the excavation line of the tunnel plays a key role in this issue. The critical state of displacements (maximum displacement in sensitivity analysis) occurs where the intersection line of the coal-intercalary stone is tangent to the tunnel excavation line. Additionally, the excavation-induced displacement decreases as the distance between the coal-intercalary stone interface and the tunnel increases, with a distance of about 1.5 m suggested for practical applications.
A. Alipour; A. A. Khodaiari; A. Jafari; R. Tavakkoli-Moghaddam
Abstract
Open-Pit Production Scheduling (OPPS) problem focuses on determining a block sequencing and scheduling to maximize Net Present Value (NPV) of the venture under constraints. The scheduling model is critically sensitive to the economic value volatility of block, block weight, and operational capacity. ...
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Open-Pit Production Scheduling (OPPS) problem focuses on determining a block sequencing and scheduling to maximize Net Present Value (NPV) of the venture under constraints. The scheduling model is critically sensitive to the economic value volatility of block, block weight, and operational capacity. In order to deal with the OPPS uncertainties, various approaches can be recommended. Robust optimization is one of the most applicable methods in this area used in this study. Robust optimization based on the box counterpart formulation is applied to deal with the OPPS problem. To have a comparison between the solutions of the box counterpart optimization model and the deterministic model, a Two-Dimensional (2D) numerical study of a hypothetical open-pit mine is conducted followed by additional computations on the actual large-scale instances (Marvin orebody). This investigation shows that the different features of the robust planning under uncertainty can be scheduled. Also the price of robustness is obtained in different levels of conservatism.
M. P. Sadr; M. Nazeri
Abstract
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 ...
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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.
Mineral Processing
S. Khoshjavan; K. Moshashaei; B. Rezai
Abstract
In this research work, the effects of flotation parameters on coking coal flotation combustible material recovery (CMR) were studied by the artificial neural networks (ANNs) method. The input parameters of the network were the pulp solid weight content, pH, collector dosage, frother dosage, conditioning ...
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In this research work, the effects of flotation parameters on coking coal flotation combustible material recovery (CMR) were studied by the artificial neural networks (ANNs) method. The input parameters of the network were the pulp solid weight content, pH, collector dosage, frother dosage, conditioning time, flotation retention time, feed ash content, and rotor rotation speed. In order to select the most efficient model for this work, the outputs of different models were compared with each other. A five-layer ANN was found to be optimum with the architecture of 8, 15, 10, and 5 neurons in the input layer, and the first hidden, second hidden, and third hidden layers, respectively, as well one neurons in the output layer. In this work, the training, testing, validating, and data square correlation coefficients (R2) were achieved to be 0.995, 0.999, 0.999, and 0.998, respectively. The sensitivity analysis showed that the rotor speed and the solid weight content had the highest and lowest effects on CMR, respectively. It was verified that the predicted ANN values coincided very well with the experimental results.
M. Talaei; A. Mousavi; A. R. Sayadi
Abstract
Nowadays due to the existence of the economic and geological uncertainties and the increasing use of scenario-based project evaluation in the design of open-pit mines, it is necessary to find an exact algorithm that can determine the ultimate pit limit in a short period of time. Determining the ultimate ...
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Nowadays due to the existence of the economic and geological uncertainties and the increasing use of scenario-based project evaluation in the design of open-pit mines, it is necessary to find an exact algorithm that can determine the ultimate pit limit in a short period of time. Determining the ultimate pit limit is an important optimization problem that is solved to define what will be eventually extracted from the ground, and directly impacts the mining costs, revenue, choosing mining equipment, and approximation of surface infrastructures outside the pit. This problem is solved in order to maximize the non-discounted profit under the precedence relation (access) constraints. In this paper, the Highest-Level Push-Relabel (HI-PR) implementation of the push–relabel algorithm is discussed and applied in order to solve the ultimate pit limit optimization problem. HI-PR uses the highest-label selection rule, global update, and gap heuristics to reduce the computations. The proposed algorithm is implemented to solve the ultimate pit limit for the nine real-life benchmark case study publicly available on the Minelib website. The results obtained show that the HI-PR algorithm can reach the optimum solution in a less computational time than the currently implemented algorithms. For the largest dataset, which includes 112687 blocks and 3,035,483 constraints, the average solution time in 100 runs of the algorithm is 4 s, while IBM CPLEX, as an exact solver, could not find any feasible solution in 24 hours. This speeding-up capability can significantly improve the current challenges in the real-time mine planning and reconciliation, where fast and reliable solutions are required.
H. Fattahi; N. Babanouri
Abstract
The tensile strength (TS) of rocks is an important parameter in the design of a variety of engineering structures such as the surface and underground mines, dam foundations, types of tunnels and excavations, and oil wells. In addition, the physical properties of a rock are intrinsic characteristics, ...
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The tensile strength (TS) of rocks is an important parameter in the design of a variety of engineering structures such as the surface and underground mines, dam foundations, types of tunnels and excavations, and oil wells. In addition, the physical properties of a rock are intrinsic characteristics, which influence its mechanical behavior at a fundamental level. In this paper, a new approach combining the support vector regression (SVR) with a cultural algorithm (CA) is presented in order to predict TS of rocks from their physical properties. CA is used to determine the optimal value of the SVR controlling the parameters. A dataset including 29 data points was used in this study, in which 20 data points (70%) were considered for constructing the model and the remaining ones (9 data points) were used to evaluate the degree of accuracy and robustness. The results obtained show that the SVR optimized by the CA model can be successfully used to predict TS.
S. Talesh Hosseini; O. Asghari; Seyed A. Torabi; M. Abedi
Abstract
An accurate modeling of sophisticated geological units has a substantial impact on designing a mine extraction plan. Geostatistical simulation approaches, via defining a variogram model or incorporating a training image (TI), can tackle the construction of various geological units when a sparse pattern ...
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An accurate modeling of sophisticated geological units has a substantial impact on designing a mine extraction plan. Geostatistical simulation approaches, via defining a variogram model or incorporating a training image (TI), can tackle the construction of various geological units when a sparse pattern of drilling is available. The variogram-based techniques (derived from two-point geostatistics) usually suffer from reproducing complex and non-linear geological units as dyke. However, multipoint geostatistics (MPS) resolves this issue by incorporating a training image from a prior geological information. This work deals with the multi-step Single Normal Equation Simulation (SNESIM) algorithm of dyke structures in the Sungun Porphyry-Cu system, NW Iran. In order to perform a multi-step SNESIM algorithm, the multi-criteria decision-making and MPS approaches are used in a combined form. To this end, two TIs are considered, one for simulating dyke structures in the shallow depth, and two for simulating dyke structures in a deeper depth. In the first step, a TI is produced using geological map, which has been mined out during the previous exploration operations. After producing TI, the 35 realizations are simulated for the shallow depth of deposit in the area under study. To select the best realization (as a TI for the next step) of the simulation results, several statistical criteria are used and the results obtained are compared. To this end, a hybrid multi-criteria decision-making is designed on the basis of a group of statistical criteria. In the next step, the dyke structures in the deeper depth are also simulated by the new TI.
M. Hasani
Abstract
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 ...
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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.
Bijan Afrasiabian; Kaveh Ahangari; Ali Noorzad
Abstract
High-level vibrations caused by blasting operations in open-pit mining can exert adverse effects such as destruction of surrounding surface structures. Therefore, it is essential to identify the factors effective in mitigating the damaging effects of ground vibration in open-pit mines, and monitor them. ...
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High-level vibrations caused by blasting operations in open-pit mining can exert adverse effects such as destruction of surrounding surface structures. Therefore, it is essential to identify the factors effective in mitigating the damaging effects of ground vibration in open-pit mines, and monitor them. This study investigates the effects of some of the most important blast design parameters in a row of blast holes. According to the advantages of numerical methods, the 3D discrete element method is employed for this purpose. The Peak Particle Velocity (PPV) values are measured along the central hole at the distances of one meter. The results obtained demonstrate that an increase in the blast damage factor and inter-hole delay time results in higher PPV values. However, the increased delay time has no remarkable effect on reducing the development of the blast damage zone. On the other hand, as the decoupling increases, the PPV values diminish, leading to substantial reductions in the ground vibration and rock mass damage. It is also observed that the elimination of sub-drilling does not significantly reduce ground vibrations. The analysis of the results obtained from the numerical modeling show that the discontinuities of the rock mass act as a filter, which could decrease the wave energy by more than 90%. Moreover, it is found that the direction of the discontinuities also affects the emission of waves caused by the blast. The PPV values are reduced, and the damaged zone is less developed if the discontinuities are opposite of the slope surface.
Mineral Processing
Mohammadreza Shahbazi; Hadi Abdollahi; Sied Ziaeddin Shafaei; Ziaeddin Pourkarimi; Sajjad Jannesar Malakooti; Ehsan Ebrahimi
Abstract
Tabas coal possesses favorable plastometric properties that make it suitable for use in metallurgical industries as coking coal. However, its high sulfur content, which stands at approximately 2%, poses a significant environmental pollution risk. Additionally, reducing ash content to below 10% is a critical ...
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Tabas coal possesses favorable plastometric properties that make it suitable for use in metallurgical industries as coking coal. However, its high sulfur content, which stands at approximately 2%, poses a significant environmental pollution risk. Additionally, reducing ash content to below 10% is a critical objective of this study to prevent a decline in coal's thermal efficiency in the metallurgical industries. This research work investigates the removal of sulfur and ash from Tabas coal samples using the biological methods including bioflotation and bioleaching. Initially, a combination of mesophilic bacteria including Acidithiobacillus ferrooxidans, Acidithiobacillus thiooxidans, and Leptosprillium ferrooxidans were employed in the bioflotation method to detain pyrite sulfur in the Tabas coal samples. The highest reduction percentages of pyrite sulfur and ash were equal to 62% and 54.18%, respectively. In the next stage, bioleaching experiments were conducted, the effect of the test time, percentage of bacteria by volume, percentage of coal solids, and absence of bacteria on the amount of sulfur and ash removal was investigated. The test time emerged as the most critical factor. The best sulfur removal was achieved using bioleaching, with a maximum removal of 72.43%, observed for the PE coal sample. Bioflotation also achieved significant sulfur removal, with a maximum removal of 61% observed for the same sample. On the other hand, the best ash removal was achieved using bioflotation, with a maximum removal of 68.98% observed for the PE coal sample, and a maximum removal of 69.34% observed for the B4B2 coal sample using bioleaching. Finally, this research work conducted a comparison of biological methods to determine the amount of sulfur and ash reduction achieved. The results showed that both bioleaching and bioflotation were effective for coal desulfurization and ash removal, with bioleaching performing slightly better for sulfur removal and bioflotation performing slightly better for ash removal.
Rock Mechanics
M. H. Khosravi; T. Pipatpongsa; J. Takemura; M. Amini
Abstract
A series of physical modeling tests were conducted by means of a beam type geotechnical centrifuge machine in order to investigate the drainage impact on the slope failure mechanism under centrifugal acceleration. Meanwhile, the phenomenon of stress redistribution in undercut slopes and the formation ...
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A series of physical modeling tests were conducted by means of a beam type geotechnical centrifuge machine in order to investigate the drainage impact on the slope failure mechanism under centrifugal acceleration. Meanwhile, the phenomenon of stress redistribution in undercut slopes and the formation of arching effect were studied. For this purpose, a poorly graded sandy soil (Silica sand No. 6) as well as a relatively well-graded sandy soil (Edosaki sand) were used as the modeling materials. The humid modeling material was compacted on a low friction oblique rigid plate simulating the potential slippage plane. The process of undercutting was conducted, while the earth pressure redistribution inside the model was recorded by means of a miniature set of pressure cells. The results obtained showed completely different failure mechanisms for the two different modeling soils. By undercutting the slope, the earth pressure redistributed and the arch action was formed in a slope model made from a well-graded soil leading to a clear arch-shaped failure. However, in using the poorly graded soil, the water was drained out during centrifuge g-up, the modeling material properties changed, and an avalanche failure was observed. Therefore, in selecting a humid compacted soil as the centrifugal modeling material, a well-graded soil is recommended.
Mineral Processing
S. G. Ozkan
Abstract
Ultrasound can be used both simultaneously or as a pretreatment technique for flotation to produce higher combustible recoveries, higher heat values, and lower ash data from raw hard coals. The recent research works have indicated that modifying coal surfaces, especially physical surface cleaning with ...
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Ultrasound can be used both simultaneously or as a pretreatment technique for flotation to produce higher combustible recoveries, higher heat values, and lower ash data from raw hard coals. The recent research works have indicated that modifying coal surfaces, especially physical surface cleaning with the help of the cavitation process created by power ultrasound at certain frequency and time intervals, might cause significant changes in flotation responses by a thorough adsorption of reagents on coal surfaces. When power ultrasound is applied to a coal slurry that makes the bubbles to collapse near a coal surface, a high-speed jet of liquid is driven into the particles, and this jet may deposit enormous energy densities at the site of impact. The simultaneous ultrasonic treatment also causes significant changes in local temperatures and pressures within the slurry containing coal and a certain number of reagents at variable dosages during flotation. This treatment improves the effectiveness of reagent molecules at coal surfaces and interfaces due to their more uniform distribution in the pulp and also enhancement of the activity of the reagents used. This paper reviews the results of the recent studies and the possible mechanism of simultaneous ultrasound-assisted coal flotation.
Environment
H. Mahdiyanfar
Abstract
Detection of deep and hidden mineralization using the surface geochemical data is a challenging subject in the mineral exploration. In this work, a novel scenario based on the spectrum–area fractal analysis (SAFA) and the principal component analysis (PCA) has been applied to distinguish and delineate ...
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Detection of deep and hidden mineralization using the surface geochemical data is a challenging subject in the mineral exploration. In this work, a novel scenario based on the spectrum–area fractal analysis (SAFA) and the principal component analysis (PCA) has been applied to distinguish and delineate the blind and deep Mo anomaly in the Dalli Cu–Au porphyry mineralization area. The Dalli mineral deposit is located on the volcanic–plutonic belt of Sahand–Bazman in the central part of Iran. The geochemical data was transformed to the frequency domain using the Fourier transformation, and SAFA was applied for classification of geochemical frequencies and detection of geochemical populations. The very low-frequency signals in the fractal method were separated using the low-pass filter function and were interpreted using PCA. This scenario demonstrates that the Mo element has an important role in the mineralization phase in the very low-frequency signals that are related to the deep mineralization; it is an important innovation in this work. Then the Mo geochemical anomaly has been mapped using the inverse Fourier transformation. This research work shows that the high-power spectrum values in SAFA are related to the background elements and the deep mineralization. Two exploratory boreholes drilled inside and outside the deep Mo anomaly area properly confirm the results of the proposed approach.
A. Nouri Qarahasanlou; M. Ataei; R. Shakoor Shahabi
Abstract
Whether directly in the form of expenses or indirectly, the objective of maintenance in the mining industry is self-evident in time losses and loss of production. In this paper, the reliability-based maintenance is examined with a different insight than before. The system goes back to the Good As New ...
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Whether directly in the form of expenses or indirectly, the objective of maintenance in the mining industry is self-evident in time losses and loss of production. In this paper, the reliability-based maintenance is examined with a different insight than before. The system goes back to the Good As New (GAN) state or too Bad As Old (BAO) maintenance state; why so, the maintenance of the system shifts to the midrange state. On the other hand, the implementation of repairs is strongly influenced by the environmental factors that are known as the “risk factors”. Therefore, an analysis requires a model that integrates two basic elements: (1) incompleteness of the maintenance effect and (2) risk factors. Thus, an extensive proportional hazard ratio model (EPHM) is used as a combination of the Proportional Hazard Model (PHM) and the Hybrid Imperfect Preventive Maintenance model (HIPM) in order to analyze these elements. In this regards, four different preventive maintenance strategies are proposed. All four strategies are time-based including constant interval or periodic (the first and second strategies) and cyclic interval (the third and fourth strategies). The proposed method is applied for a Komatsu HD785-5 dump-truck in the Songun copper mine as a case study. The PM intervals with a mean value of risk factors for the four activities to reach the 80% reliability for the first and second strategies are about 5 and 48 hours. These intervals for the third strategy are calculated as 48.36, 11.58, 10.25, and 9.035, and for the fourth strategy are 5.06, 4.078, 3.459, and 1.92.
Ajay Kumar; Aditya Gupta; Yadvendra Pratap Singh; Monu Bhagat
Abstract
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 ...
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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 × 1 × 3], [5 × 5 × 3], and [10 × 10 × 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.
M. Ansari; M. Hosseini; A. R. Taleb Beydokhti
Abstract
Rock abrasivity, as one of the most important parameters affecting the rock drillability, significantly influences the drilling rate in mines. Therefore, rock abrasivity should be carefully evaluated prior to selecting and employing drilling machines. Since the tests for a rock abrasivity assessment ...
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Rock abrasivity, as one of the most important parameters affecting the rock drillability, significantly influences the drilling rate in mines. Therefore, rock abrasivity should be carefully evaluated prior to selecting and employing drilling machines. Since the tests for a rock abrasivity assessment require sophisticated laboratory equipment, empirical models can be used to predict rock abrasivity. Several indices based on five known methods have been introduced for assessing rock abrasivity including rock abrasivity index (RAI), Cerchar abrasivity index (CAI), Schimazek’s abrasivity factor (F-abrasivity), bit wear index (BWI), and LCPC abrasivity coefficient (LAC). In this work, 12 rock types with different origins were investigated using the uniaxial compressive strength (UCS), Brazilian test for tensile strength, and longitudinal wave velocity and LCPC tests, and microscopic observations were made to obtain a correlation for estimating the LCPC abrasivity coefficient by conducting the conventional rock mechanics tests. Using the equivalent quartz content, velocity of longitudinal waves, and rock brittleness index, a linear correlation was obtained with a coefficient of determination (R2) of 93.3% using SPSS in order to estimate LAC.
Environment
Sehla Altaf; Kanwarpreet Singh; Abhishek Sharma
Abstract
The expansion and contraction properties of black cotton soil make it a challenging task to construct structures on it. Hence, modifying its expansion and contraction behavior is imperative to make black cotton soil appropriate for construction purposes. This study aims to assess the geo-technical properties ...
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The expansion and contraction properties of black cotton soil make it a challenging task to construct structures on it. Hence, modifying its expansion and contraction behavior is imperative to make black cotton soil appropriate for construction purposes. This study aims to assess the geo-technical properties of black cotton soil through laboratory testing, incorporating waste foundry sand (WFS) and sodium chloride (NaCl) to utilize the combination as sub-grade material. Differential free swell, consistency limits, the standard Proctor test, and California bearing ratio (CBR) tests are conducted with varying amounts of both materials. The laboratory testing reveals that the addition of the appropriate amount of waste foundry sand, sodium chloride, or both, improve the geo-technical properties of black cotton soil (BCS). Furthermore, using the CBR values obtained, the thickness of flexible pavement is designed with the IITPAVE software and evaluated against the IRC: 37-2018 recommendations. The software analysis demonstrates a reduction in pavement thickness for varying levels of commercial vehicles per day such as 1000, 2000, and 5000 CVPD across all combinations. This mixture not only addresses the issues related to black cotton soil but also provides an economical solution for soil stabilization and proves to be sustainable as it involves the utilization of waste materials such as waste foundry sand.
B. Shokouh Saljoughi; A. Hezarkhani; E. Farahbakhsh
Abstract
The study area, located in the southern section of the Central Iranian volcano–sedimentary complex, contains a large number of mineral deposits and occurrences which is currently facing a shortage of resources. Therefore, the prospecting potential areas in the deeper and peripheral spaces has become ...
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The study area, located in the southern section of the Central Iranian volcano–sedimentary complex, contains a large number of mineral deposits and occurrences which is currently facing a shortage of resources. Therefore, the prospecting potential areas in the deeper and peripheral spaces has become a high priority in this region. Different direct and indirect methods try to predict promising areas for future explorations, most of which are very time-consuming and costly. The main goal of mineral prospecting is applying a transparent and robust approach for identifying high potential areas to be explored further in the future. This work presents the procedure taken to create two different Cu-mineralization prospectivity maps. The first map is created using a knowledge-driven fuzzy technique and the second one by a data-driven Artificial Neural Network (ANN) approach. In this study aim is to investigate the results of applying the ANN technique and to compare them with the outputs of applying the fuzzy logic method. The geo-datasets employed for creating evidential maps of porphyry Cu mineralization include the solid geology map, alteration map, faults, dykes, airborne total magnetic intensity, airborne gamma-ray spectrometry data (U, Th, K and total count), and known Cu occurrences. Based on this study, the ANN technique is a better predictor of Cu mineralization compared to the fuzzy logic method. The ANN technique, due to capabilities such as classification, pattern matching, optimization, and prediction, is useful in identifying the anomalies associated with the Cu mineralization.
