Exploitation
Blessing Olamide Taiwo; Oluwaseun Victor Famobuwa; Melodi Mbuyi Mata; Mohammed Sazid; Yewuhalashet Fissha; Victor Afolabi Jebutu; Adams Abiodun Akinlabi; Olaoluwa Bidemi Ogunyemi; Ozigi Abubakar
Abstract
The purpose of this research work is to create empirical models for assessing the profitability of granite aggregate production in Akure, Ondo State, aggregate quarries. In addition, an Artificial Neural Network (ANN) model for granite profitability was developed. A structured survey questionnaire was ...
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The purpose of this research work is to create empirical models for assessing the profitability of granite aggregate production in Akure, Ondo State, aggregate quarries. In addition, an Artificial Neural Network (ANN) model for granite profitability was developed. A structured survey questionnaire was used to collect data for the study. The data extracted from the case study mine for this study includes granite marketing operations, royalty, production costs, and mine production information. In this study, the efficacy of granite fragmentation was assessed using the WipFrag software. The relationship between particle size distribution, blast design, blast efficiency, and uniformity index were analyzed using the WipFrag result. The optimum blast design was also identified and recommended for mine production. The result revealed that large burden distances result in bigger X50, X80, and Xmax fragmentation sizes. A burden distance of 2 m and a 2 m spacing were identified as the optimum burden and spacing. The finding revealed that blast mean size and 80% passing mesh size have a positive correlation. The result from this study indicated that the uniformity index has a positive correlation with blast efficiency and a negative correlation with maximum blast fragmentation size. The prediction accuracy of the developed models was evaluated using the coefficient of determination (R2), root mean square error (RMSE), and mean square error (MSE). The error analysis revealed that the ANN model is suitable for predicting quarry-generated profit.
Exploitation
Shahrokh Khosravimanesh; Masoud Cheraghi Seifabad; Reza Mikaeil; Raheb Bagherpour
Abstract
Specific energy is a key indicator of drilling performance to consider in the feasibility and economic analyses of drilling projects. Any improvement in the specific energy of a drilling operation may reflect an improvement in the overall efficiency of drilling operations. This improvement can be achieved ...
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Specific energy is a key indicator of drilling performance to consider in the feasibility and economic analyses of drilling projects. Any improvement in the specific energy of a drilling operation may reflect an improvement in the overall efficiency of drilling operations. This improvement can be achieved by delivering a suitable cooling lubricant into the drilling environment. The present study examines the mechanical characteristics of the drilled rock, the physical qualities of the cooling lubricant employed, and the drilling rig operational parameters related to the drilling-specific energy (DSE). To this end, seven rock samples (granite, marble, and travertine) were drilled using water and five other fluids as the cooling lubricants. A total of 492 drilling experiments were conducted with a custom-designed and built laboratory-scale drilling rig on cuboid rock specimens. The univariate linear regression analysis of experimental results revealed a significant drop in DSE after using cooling lubricants instead of conventional cooling fluid (i.e. water). Under constant conditions in terms of mechanical properties of the rock, using Syncool with a concentration of 1:100 and soap water with a concentration of 1:120 instead of water led to 34% and 43% DSE reductions in the granite samples, 48% and 54% in the marble samples, and 41% and 50% in the travertine samples, respectively. These variations in specific energy suggest that the drilling efficiency and performance can be augmented using properly selected cooling lubricants.
Exploitation
Hassanreza Ghasemitabar; Andisheh Alimoradi; Hamidreza Hemati Ahooi; Mahdi Fathi
Abstract
Drilling of exploratory boreholes is one of the most important and costly steps in mineral exploration, which can provide us with accurate and appropriate information to continue the mining process. There are limitations on drilling the target boreholes, such as high costs, topographical problems in ...
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Drilling of exploratory boreholes is one of the most important and costly steps in mineral exploration, which can provide us with accurate and appropriate information to continue the mining process. There are limitations on drilling the target boreholes, such as high costs, topographical problems in installation of drilling rigs, restrictions caused by previous mining operation etc. The advances in artificial intelligence can help to solve these problems. In this research, we used python as one of the most pervasive and the most powerful programming languages in the field of data analysis and artificial intelligence. In this method mean shift algorithms have been used to cluster data, random forest to estimate clusters, and gradient boosting to estimate iron grade. Finally, in the studied area of Choghart in Central Iran, more than 91% accuracy was achieved in detection of ore blocks. Also, the results of the neural network indicate the mean square error (MSE) and mean absolute error (MAE) in the training data, respectively equal to 0.001 and 0.029, in the test data is 0.002 and 0.03, and in the validation boreholes, we reached a maximum of 0.06 and 0.2.
Exploitation
Rym Khettabi; Issam Touil; Mohamed Kezzar; Mohamed R. Eid; Fatima.Z Derdour; Kamel Khounfais; Lakhdar Khochmane
Abstract
It is well-established that the response surface methodology (RSM) is commonly employed to establish the differences between the predicted values and those observed experimentally. This study mainly goals on the impact of four drilling factors including weight on the bit (WOB), the rotating rapidity ...
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It is well-established that the response surface methodology (RSM) is commonly employed to establish the differences between the predicted values and those observed experimentally. This study mainly goals on the impact of four drilling factors including weight on the bit (WOB), the rotating rapidity of the bit, RPM, cutting angle , and rock resistance on the penetration rate of the drilling tool. In this examination, three kinds of limestone rocks were considered. The planned assessments were carried out at three stages of the considered four input variables. The statistical analysis was realized using both RSM approach and analysis of variance (ANOVA). This analysis allowed us to develop the appropriate penetration model with a higher determination coefficient of 96.19%, which demonstrates the high correlation between the predicted and experimental data, and consequently, it can be concluded that the obtained model is highly suitable for the prediction of the penetration rate. Also from variance analysis, the results obtained show that rotational speed, RPM, and weight on the bit (WOB) parameters, as well as the nature of the rock, which is determined by the rock compressive resistance, having a significant effect on the penetration rate; however, the rake angle has little effect. Finally, the optimal parameters were determined to find the best possible penetration rate of the drilling tool.
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.
Exploitation
Emad Ansari; Ramin Rafiee; Mohammad Ataei
Abstract
Due to longwall mining, a large space without any support is created, and the in-situ stress regimes change. The change of the in-situ stress regimes affects the roof and face of the adjacent panel. In other words, the strata behavior would be different from the intact condition during the previous panel ...
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Due to longwall mining, a large space without any support is created, and the in-situ stress regimes change. The change of the in-situ stress regimes affects the roof and face of the adjacent panel. In other words, the strata behavior would be different from the intact condition during the previous panel mining. In this study, two adjacent panels are simulated in the FLAC3D software to study the effect of panel extraction on its adjacent panel strata behavior during longwall mining. The available data of the Tabas Parvadeh Coal Mine panels is used for this purpose. According to the numerical modeling results, the length of the first roof’s weighting effect (FRWE) in the gob of the first and second panels is calculated, respectively, as 26 and 21 meters. In other words, the gob dimension in the second panel is reduced by about 19.2%, and the vertical displacement value is increased by about 18.5%. In addition, the chance of roof collapse and face spalling during the first-panel mining is more than the second-panel. It means that roof and face instability in the (FRWE) during the first-panel mining is confirmed, while in the second-panel extraction is just very likely.
Exploitation
Sonu Singh; Vijay Shankar; Joseph Tripura
Abstract
Assessing the groundwater potential (GWP) and protective capacity of aquifers is essential to provide solutions to challenges in aquifer exploration and conditions in hilly terrain regions. The study was conducted in the hilly terrain region of Hamirpur, Himachal Pradesh, India, to obtain one-dimensional ...
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Assessing the groundwater potential (GWP) and protective capacity of aquifers is essential to provide solutions to challenges in aquifer exploration and conditions in hilly terrain regions. The study was conducted in the hilly terrain region of Hamirpur, Himachal Pradesh, India, to obtain one-dimensional vertical electrical sounding (VES) data for groundwater exploration and evaluate the vulnerability of sublayers. Forty VES sites were used in the Schlumberger electrode configuration. The analysis of data resulted in stratified 2-5 different curves. According to the geoelectric sections, there are two to five layers of soil beneath the region i.e. Shale/clay (10-650 Ohm-m), fractured sandstone/gravel/sand (10.3-436 Ohm-m), clay mix gravel/clay mix sand/coarse-grained sandstones (1.06-355 Ohm-m), conglomerate/clay/hard sandstone (60.5-658.7 Ohm-m), sandstone/shale (90.8-125 Ohm-m) with aquifer resistivity (AR) in parenthesis. Aquifer resistivity (AR), longitudinal conductance (S), layer thickness (LT), and transverse resistivity (TR) distribution maps were generated using interpreted VES data for various sub-layers using ArcGIS 10.1. The geologic second and third sub-surface layers are generally porous and permeable. S values for underlying layers are generally less than unity, which indicates vulnerable zones with a significant risk of contamination. Based on the S values, the strata are divided into five categories as Poor (5.55%), weak (19.43%), moderate (19.45%), good (38.89%), and very good (16.68%). Areas with moderate to very good protection capacity are planned as zones with high GWP. The study results are useful in preliminary pollution control and assessment for sustainable groundwater management.
Exploitation
Babatunde Adebayo; Blessing Olamide Taiwo; BUSUYI THOMAS AFENI; Aderoju Oluwadolapo Raymond; Joshua Oluwaseyi Faluyi
Abstract
The quarry operators and managers are having a running battle in determining with precision the rate of deterioration of the button of the drill bit as well as its consumption. Therefore, this study is set to find the best-performing model for predicting the drill bit button's wear rate during rock drilling. ...
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The quarry operators and managers are having a running battle in determining with precision the rate of deterioration of the button of the drill bit as well as its consumption. Therefore, this study is set to find the best-performing model for predicting the drill bit button's wear rate during rock drilling. Also, the rate at which drill bit buttons wear out during rock drilling in Ile-Ife, Osogbo, Osun State, and Ibadan, Oyo State, Southwest, Nigeria was investigated. Artificial Neural Network (ANN), Adaptive Neuro-Fuzzy Inference System (ANFIS), and adaptive moment Estimation-based Long Short-Term Memory (LSTM) machine learning approaches were used to create models for estimating the bit wear rate based on circularity factor, rock grain size, equivalent quartz content, uniaxial compressive strength, porosity, and abrasive properties of the rock. The performance of the models was measured using a new error estimation index and four other convectional performance estimators. The analysis of performance shows that the adaptive moment estimation algorithm-based LSTM model did better and more accurately than the other models. Thus, the LSTM models presented can be used to improve drilling operations in real-life situations.
Exploitation
R. Shamsi; M. S. Amini; H. Dehghani; M. Bascompta; B. Jodeiri Shokri; Sh. Entezam
Abstract
This paper attempted to estimate the amount of flyrock in the Angoran mine in Zanjan province, Iran using the gene expression programming (GEP) predictive technique. The input data, including flyrock, mean depth of the hole, powder factor, stemming, explosive weight, number of holes, and booster were ...
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This paper attempted to estimate the amount of flyrock in the Angoran mine in Zanjan province, Iran using the gene expression programming (GEP) predictive technique. The input data, including flyrock, mean depth of the hole, powder factor, stemming, explosive weight, number of holes, and booster were collected from the mine. Then, using GEP, a series of intelligent equations were proposed to predict flyrock distance. The best GEP equation was selected based on some well-established statistical indices in the next stage. The coefficient of determination for training and testing datasets of the GEP equation were 0.890 and 0.798, respectively. The model obtained from the GEP method was then optimized using teaching– learning-based optimization algorithm (TLBO). Based on the results, the correlation coefficient of training and testing data increased to 91% and 89%, which increased the accuracy of the Equation. This new intelligent equation could forecast flyrock resulting from mine blasting with a high level of accuracy. The capabilities of this intelligent technique could be further extended to the other blasting environmental issues.
Exploitation
M. Hosseini; H. Madani; K. Shahriar
Abstract
The main purpose of this work is modeling the dispersion of the sarin gas in a subway station in a hypothetical scenario. The dispersion is modeled using the CFD approach. In the analysis of the environmental conditions of the underground spaces, the only factor that draws a distinction between a subway ...
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The main purpose of this work is modeling the dispersion of the sarin gas in a subway station in a hypothetical scenario. The dispersion is modeled using the CFD approach. In the analysis of the environmental conditions of the underground spaces, the only factor that draws a distinction between a subway station and other spaces is the train piston effect. Therefore, the present research work models the sarin dispersion in the two general cases of with and without a train in the subway system. About 0.5 L of sarin is assumed to be released through the main air handling unit (AHU) of the station. The results obtained show that in the case with no train service in the station, after 20 minutes of sarin release, the concentration and dose of sarin in the station will be 8.9 mg/m3 and 80 mg minute/m3, respectively, and these values are highly dangerous and lethal, and would have severely adverse effects on many individuals, and lead to death. This is highly important, especially when the effect of ventilation chambers at the ground level is taken into consideration. The results obtained also show that the train piston effect reduces the concentration and dose of sarin in the station so that when train arrival at and departure from the station, the sarin dose considerably reduces to 25 mg min/m3 after the release, and contributes to lower casualties. Finally, the results obtained show that time is a key factor to save lives in the management of such incidents.
Exploitation
R. Norouzi Masir; M. Ataei; A. Mottahedi
Abstract
The drilling and blasting method is the first choice for rock breakage in surface or underground mines due to its high flexibility against variations and low investment costs. However, any method has its own advantages and disadvantages. The flyrock phenomenon is one of the drilling and blasting disadvantages ...
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The drilling and blasting method is the first choice for rock breakage in surface or underground mines due to its high flexibility against variations and low investment costs. However, any method has its own advantages and disadvantages. The flyrock phenomenon is one of the drilling and blasting disadvantages that the mining engineers have always been faced with in the surface mine blasting operations. Flyrock may lead to fatality and destroy mine equipment and structures, and so its risk assessment is very essential. For a flyrock risk assessment, the causing events that lead to flyrock along with their probabilities and severities should be identified. For this aim, a combination of the fuzzy fault tree analysis and multi-criteria decision-making methods are used. Based on the results obtained, the relevant causing events of flyrock in surface mines can be categorized into three major groups: design error, human error, and natural error. Finally, using the obtained probabilities and severities for these three groups, the risk matrix is constructed. Based on the risk matrix, the risk numbers of flyrock occurrence due to the design errors, human errors, and natural influence are 12, 6, and 2, respectively. Hence, in order to minimize the flyrock risk, it is very vital for the engineers to select appropriate values for the design events of blasting pattern such as burden, spacing, delays, and hole diameter.
Exploitation
M. Mohseni; M. Ataei; R. Khaloo Kakaie
Abstract
The contamination of ores with wastes or materials of lower than the cut-off grade is referred to as dilution. Dilution is an undesirable phenomenon that, on one hand, reduces the product grade and, consequently, reduces the sales prices and, on the other hand, adds an extra cost to waste production. ...
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The contamination of ores with wastes or materials of lower than the cut-off grade is referred to as dilution. Dilution is an undesirable phenomenon that, on one hand, reduces the product grade and, consequently, reduces the sales prices and, on the other hand, adds an extra cost to waste production. Therefore, studying and evaluating the dilution risk is important in mining, and especially in underground mining. In this work, using a powerful decision-making method, i.e. Multi-Attributive Approximation Area Comparison (MABAC), the dilution risk and ranking it in underground mines are assessed. For this purpose, the most important parameters affecting the dilution in 10 mines of the Venarch manganese mines are first identified and then weighed using the Fuzzy Delphi Analytical Hierarchy Analysis (FDAHP) method. Then using the MABAC method, the dilution risk score for each mine is estimated, and subsequently, various mines are ranked as the dilution risk. Then with the implementation of the Cavity Monitoring System (CMS) and measurement of the actual dilution values, the mines are ranked in dilution. The correct matching of the results of these two rankings indicates that the MABAC method is highly effective in the ranking of the risk. At the end, the risk ranking of the mines is done using the TOPSIS method, and the lack of full compliance with the results of this method with the actual values indicates that the MABAC method is preferable to the TOPSIS method.
Exploitation
F. Sotoudeh; M. Ataei; R. Kakaie; Y. Pourrahimian
Abstract
In mining projects, all uncertainties associated with a project must be considered to determine the feasibility study. Grade uncertainty is one of the major components of technical uncertainty that affects the variability of the project. Geostatistical simulation, as a reliable approach, is the most ...
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In mining projects, all uncertainties associated with a project must be considered to determine the feasibility study. Grade uncertainty is one of the major components of technical uncertainty that affects the variability of the project. Geostatistical simulation, as a reliable approach, is the most widely used method to quantify risk analysis to overcome the drawbacks of the estimation methods used for an entire ore body. In this work, all the algorithms developed by numerous researchers for optimization of the underground stope layout are reviewed. After that, a computer program called stope layout optimizer 3D is developed based on a previously proposed heuristic algorithm in order to incorporate the influence of grade variability in the final stope layout. Utilizing the sequential gaussian conditional simulation, 50 simulations and a kriging model are constructed for an underground copper vein deposit situated in the southwest of Iran, and the final stope layout is carried out separately. It can be observed that geostatistical simulation can effectively cope with the weakness of the kriging model. The final results obtained show that the frequency of economic value for all realizations varies between 6.7 M$ and 30.7 M$. This range of variation helps designers to make a better and lower risk decision under different conditions.
Exploitation
M. Lotfi; H. Arefi; A. Bahroudi
Abstract
Hyperspectral remote sensing records reflectance or emittance data in a large sum of contiguous and narrow spectral bands, and thus has many information in detecting and mapping the mineral zones. On the other hand, the geological and geophysical data gives us some other fruitful information about the ...
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Hyperspectral remote sensing records reflectance or emittance data in a large sum of contiguous and narrow spectral bands, and thus has many information in detecting and mapping the mineral zones. On the other hand, the geological and geophysical data gives us some other fruitful information about the physical characteristics of soil and minerals that have been recorded from the surface. The Sarcheshmeh mining area located in the NW-trending Uromieh-Dokhtar magmatic belt within Central Iran is mainly of porphyry type, and is associated with extensive hydrothermal alterations. Due to the semi-arid type of climate with abundant rock exposure, this area is suitable for application of remote sensing techniques. In this work, we focus on generating the alteration maps around Cu porphyry copper deposits using the spectral angle mapper algorithm on Hyperion data by applying two filters named reduction to pole and analytical signal on a total magnetic intensity map and generating the Kd map from radiometry data. What is clear is the high importance of applying the adequate pre-processing on Hyperion data because of low signal-to-noise ratio. By comparing the known deposits in the region with the results obtained by applying the mentioned methods, it is revealed that not all the higher K radiometric values are entirely associated with the hydrothermal alteration zones, and in contrast, the potassic alteration map extracted from Hyperion imagery successfully corresponds to the alteration zones around the Sarcheshmeh mining area. Finally, the results particularly obtained from processing the Hyperion data are confirmed by indices of Cu porphyry deposits in the region.
Exploitation
B. Tokhmechi; S. Ebrahimi; H. Azizi; Seyed R. Ghavami-Riabi; N. Farrokhi
Abstract
Recognition of ore deposit genesis is still a controversial challenge for economic geologists. Here, this task was addressed by the virtue of Bayesian data fusion (BDF) implementing available proofs: semi-schematic examples with two (Cu and Pb + Zn) and three (Cu, Pb + Zn and Ag) evidences. The data, ...
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Recognition of ore deposit genesis is still a controversial challenge for economic geologists. Here, this task was addressed by the virtue of Bayesian data fusion (BDF) implementing available proofs: semi-schematic examples with two (Cu and Pb + Zn) and three (Cu, Pb + Zn and Ag) evidences. The data, in current paper are just concentrations of indicated elements, were collected from Angouran’s deposit in Iran at prospecting and general exploration stages. BDF was used for discrimination between three geneses of Massive Sulfide, Mississippi and SEDEX types. Better genesis recognition with clear discrimination between the geneses was achieved by BDF as compared with earlier studies. The results showed that uncertainties were reduced from 50% to less than 30% and deposit recognition was improved greatly. Furthermore, we believe that using more properties can have a beneficial effect on the overall outcome. The comparison made between 2 and 3 properties showed that the amount of probable belonging values to any type of deposit was greater in 3 properties. It was also confirmed that using the completed information from the various stages of exploration progress can be amplified and be used for genesis recognition via BDF.
Exploitation
M. Ghobadi Samani; M. Monjezi; J. Khademi Hamidi; A. Mousavinogholi
Abstract
Truck-Shovel fleet, as the most common transportation system in open-pit mines, has a significant part of mining costs, for which optimal management can lead to substantial cost reductions. Among the available dispatch mathematical models, the multi-stage approach is well suited for allocating trucks ...
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Truck-Shovel fleet, as the most common transportation system in open-pit mines, has a significant part of mining costs, for which optimal management can lead to substantial cost reductions. Among the available dispatch mathematical models, the multi-stage approach is well suited for allocating trucks to respected shovels in a dynamic dispatching program. However, with this kind of modeling sequencing of the allocated trucks is not possible though it is important to find out the best solution so that getting the minimum accrued cost. To comply with the shortcoming of the traditional model, in this paper, a new hybrid model is developed and applied in Copper Mine of Iran, in which for each truck an allocation matrix is considered as input to the genetic algorithm implemented to determine the best solution. According to the obtained results, the optimal sequencing of the trucks can result in a significant (31%) cost reduction in a shift.
Exploitation
A. Saffari; M. Ataei; F. Sereshki
Abstract
Spontaneous combustion of coal is one of the most horrifying hazards in coal industries, especially in underground coal mines. Thus having a prior knowledge about the occurrence of this phenomenon in underground coal mines is of crucial importance in preventing this process, loss of life, huge economic ...
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Spontaneous combustion of coal is one of the most horrifying hazards in coal industries, especially in underground coal mines. Thus having a prior knowledge about the occurrence of this phenomenon in underground coal mines is of crucial importance in preventing this process, loss of life, huge economic loss, and environmental pollution. The aim of this work is to determine the spontaneous combustion of coal potential in the Tabas Parvadeh coal mines in Iran in order to assess the effect of coal intrinsic characteristics on its occurrence. For the purpose of this investigation, the coal samples were collected from Parvadeh I to IV, and the coal intrinsic characteristics of the samples were tested. In order to determine the spontaneous combustion of coal propensity in this case study, the Crossing Point Temperature (CPT) test was used. Then the relation between the coal intrinsic characteristics and the CPT test values was determined. The results obtained showed that the B1 seam in Parvadeh II and C1 seam in Parvadeh III had a high potential of spontaneous combustion of coal potential. These results also show that an increase in the moisture, volatile matter, pyrite, vitrinite, and liptinite contents enhance the spontaneous combustion of coal tendency in these mines. The results obtained have major outcomes for the management of this phenomenon in the Tabas Parvadeh coal mines. Therefore, evaluation of the spontaneous combustion of coal hazards in coal mines should start in the first stage of design and carried on during their whole lifecycle, even after mine closure.
Exploitation
H. Bakhshandeh Amnieh; M. Hakimiyan Bidgoli; H. Mokhtari; A. Aghajani Bazzazi
Abstract
Estimating the costs of blasting operations is an important parameter in open-pit mining. Blasting and rock fragmentation depend on two groups of variables. The first group consists of mass properties, which are uncontrollable, and the second one is the drill-and-blast design parameters, which can be ...
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Estimating the costs of blasting operations is an important parameter in open-pit mining. Blasting and rock fragmentation depend on two groups of variables. The first group consists of mass properties, which are uncontrollable, and the second one is the drill-and-blast design parameters, which can be controlled and optimized. The design parameters include burden, spacing, hole length, hole diameter, sub-drilling, charge weight, charge length, stemming length, and charge density. Blasting costs vary depending on the size of these parameters. Moreover, blasting brings about some undesirable results such as air overpressure, fly rock, back-break, and ground vibration. This paper proposes a mathematical model for estimating the costs of blasting operations in the Baghak gypsum mine. The cost of blasting operations in the objective function is divided into three parts: drilling costs, costs of blasting system, and costs of blasting labours. The decision variables used to minimize the costs include burden, spacing, hole diameter, stemming length, charge density, and charge weight. Constraints of the model include the boundary and operational limitations. Air overpressure in the mine is also anticipated as one of the model constraints. The non-linear model obtained with consideration of constraints is optimized by simulated annealing (SA). After optimizing the model by SA, the best values for the decision variables are determined. The value obtained for the cost was obtained to be equal to 2259 $ per 7700 tons for the desired block, which is less than the blasting costs in the Baghak gypsum mine.
Exploitation
F. Soltani; P. Moarefvand; F. Alinia; P. Afzal
Abstract
The traditional approaches of modeling and estimation of highly skewed deposits have led to incorrect evaluations, creating challenges and risks in resource management. The low concentration of the rare earth element (REE) deposits, on one hand, and their strategic importance, on the other, enhances ...
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The traditional approaches of modeling and estimation of highly skewed deposits have led to incorrect evaluations, creating challenges and risks in resource management. The low concentration of the rare earth element (REE) deposits, on one hand, and their strategic importance, on the other, enhances the necessity of multivariate modeling of these deposits. The wide variations of the grades and their relation with different rock units increase the complexities of the modeling of REEs. In this work, the Gazestan Magnetite-Apatite deposit was investigated and modeled using the statistical and geostatistical methods. Light and heavy REEs in apatite minerals are concentrated in the form of fine monazite inclusions. Using 908 assayed samples, 64 elements including light and heavy REEs from drill cores were analyzed. By performing the necessary pre-processing and stepwise factor analysis, and taking into account the threshold of 0.6 in six stages, a mineralization factor including phosphorus with the highest correlation was obtained. Then using a concentration-number fractal analysis on the mineralization factor, REEs were investigated in various rock units such as magnetite-apatite units. Next, using the sequential Gaussian simulation, the distribution of light, heavy, and total REEs and the mineralization factor in various realizations were obtained. Finally, based on the realizations, the analysis of uncertainty in the deposit was performed. All multivariate studies confirm the spatial structure analysis, simulation and analysis of rock units, and relationship of phosphorus with mineralization.
Exploitation
R. Razzaghzadeh; R. Shakoor Shahabi; A. Nouri Qarahasanlou
Abstract
The appropriate operating of mining machines is affected by both the executive and environmental factors. Considering the effects and the related risks lead to a better understanding of the failures of such machines. This leads to a proper prediction of the reliability parameters of such machines. In ...
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The appropriate operating of mining machines is affected by both the executive and environmental factors. Considering the effects and the related risks lead to a better understanding of the failures of such machines. This leads to a proper prediction of the reliability parameters of such machines. In this research work, the reliability and maintainability analysis of the loading and haulage machines in the Sungun Copper Mine, considering the repair condition as multiple repairable units, was performed. For this purpose, the data necessary for the loading and haulage equipment including 2 loaders and 8 dump trucks for a 15-month period was collected and categorized in 10 operational units after the system and sub-systems of the department were determined. Initially, the time between failures (TBFs) and time to repair (TTR) for each unit was calculated. Then 20 sub-systems were developed. Primarily, the Stata software was utilized to carry out the heterogeneity test for all the sub-systems. In consequence, most of the sub-systems were regarded as the heterogeneous ones, except for 7 of them including the dump truck units 1, 2, 3, 4, 5, 7, and 8 in TBFs. Hence, "PHM" that is a covariate-based model displayed the heterogeneous group. Its reliability function was also estimated. For the next step, the trend tests were done on the non-heterogeneous sub-systems by means of the Minitab software. The homogeneous sub-systems with failure trend were modeled by “NHPP”. Afterwards, the non-trended sub-systems formed the data group. Later, the correlation tests were modeled by “HPP”. Finally, the reliability and maintainability functions were calculated with the 95% confidence level.
Exploitation
S. Salarian; O. Asghari; M. Abedi; S. K. Alilou
Abstract
This work aims at figuring out the spatial relationships between the geophysical and geological models in a case study pertaining to copper-sulfide mineralization through an integrated 3D analysis of favorable target. The Ghalandar Skarn-Porphyry Cu Deposit, which is located in NW Iran, is selected for ...
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This work aims at figuring out the spatial relationships between the geophysical and geological models in a case study pertaining to copper-sulfide mineralization through an integrated 3D analysis of favorable target. The Ghalandar Skarn-Porphyry Cu Deposit, which is located in NW Iran, is selected for this research work. Three geophysical surveys of direct current electrical resistivity and induced polarization tomography along with magnetometry are performed to construct the physical properties of electrical resistivity, chargeability, and magnetic susceptibility, respectively. Inverse modeling and geostatistical interpolation are utilized to generate the physical 3D models. A 3D model of Cu grade is generated using ordinary kriging; however, the indicator kriging method is run to design a 3D model of rock types through incorporating the drilling results. Block models of geophysical and geological characteristics are cast in a similar 3D mesh to investigate their relationships in copper mineralization. A concentration-volume multi-fractal method is utilized to divide each model into its sub-sets, where the most productive portions in association with Cu-bearing mineralization are distinguished. Note that sub-sets of geophysical models are spatially matched with geological models of Cu grade and rock types. The zones with low electrical resistivity, high chargeability, and low magnetic susceptibility correspond to the main source of Cu mineralization in a dominated skarn rock type setting.
Exploitation
A. Mozafari; A. H. Bangian Tabrizi; M. Taji; A. Parhizkar
Abstract
In this paper, we present an integrated model to find the optimum size of blast block that uses (i) a multi-criteria decision-making method to specify the applicable size of the mineable block; (ii) a linear programming method for the selection of the blasted areas to be excavated and in deciding the ...
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In this paper, we present an integrated model to find the optimum size of blast block that uses (i) a multi-criteria decision-making method to specify the applicable size of the mineable block; (ii) a linear programming method for the selection of the blasted areas to be excavated and in deciding the quantity of ores and wastes to be mined from each one of the selected blocks. These two methods use improved estimates of the orebody characteristics utilizing the blast hole data in addition to the usual borehole statistics to improve the prediction accuracy of the block level ore body characteristics. This work aims to make a mathematical model to figure out the ideal width and length of the blast block in order to curtail drilling and blasting expenses in open-pit mines. As a consequence, the effective blast block size is heeded so as to decrease the expenses of drilling and blasting. Furthermore, a complete set of actual principles is presented to specify the applicable size of the mineable block by means of the multi-criteria decision-making method of fuzzy logic. The aforementioned model is practiced to forecast the block size necessary for the purpose of production planning. Next, a mixed integer programming model is developed to blast planning in order to select the optimal size of the blast block by considering the mineable block. The proposed model is applied in the Chadormalu iron ore mine and the rationality of the model is demonstrated by the outcomes of dissimilar circumstances.
Exploitation
O. Gholampour; A. Hezarkhani; A. Maghsoudi; M. Mousavi
Abstract
This paper presents a quantitative modeling for delineating alteration zones in the hypogene zone of the Miduk porphyry copper deposit (SE Iran) based on the core drilling data. The main goal of this work was to apply the Ordinary Kriging (OK), Artificial Neural Networks (ANNs), and Concentration-Volume ...
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This paper presents a quantitative modeling for delineating alteration zones in the hypogene zone of the Miduk porphyry copper deposit (SE Iran) based on the core drilling data. The main goal of this work was to apply the Ordinary Kriging (OK), Artificial Neural Networks (ANNs), and Concentration-Volume (C-V) fractal modelings on Cu grades to separate different alteration zones. Anisotropy was investigated and modeled based on calculating the experimental semi-variograms of Cu value, and then the main variography directions were identified and evaluated. The block model of Cu grade was generated using the kriging and ANN modelings followed by log-log plots of the C-V fractal modeling to determine the Cu threshold values used in delineating the alteration zones. Based on the correlation between the geological models and the results derived via C-V fractal modeling, Cu values less than 0.479% resulting from kriging modeling had more overlapped voxels with the phyllic alteration zone by an overall accuracy (OA) of 0.83. The spatial correlation between the potassic alteration zone in a 3D geological model and the high concentration zones in the C-V fractal model showed that Cu values between 0.479% and 1.023%, resulting from kriging modeling, had the best overall accuracy (0.78). Finally, based on the correlation between classes in the binary geological and fractal models of the hypogene zone, this research work showed that kriging modeling could delineate the phyllic (with lower grades) and potassic (with higher grades) alteration zones more effectively compared with ANNs.
Exploitation
H.R. Nezarat; Seyed M. E. Jalali; M. Nazari
Abstract
Knowledge of the airflow distribution inside a Tunnel Boring Machine (TBM) can create a safe working environment for workers and machinery. The airflow quality and the related mass flow rate in the ventilation system should be sufficient to dilute gases and remove dust inside the tunnel. In this work, ...
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Knowledge of the airflow distribution inside a Tunnel Boring Machine (TBM) can create a safe working environment for workers and machinery. The airflow quality and the related mass flow rate in the ventilation system should be sufficient to dilute gases and remove dust inside the tunnel. In this work, airflow distribution in the single shield TBM tunnel was studied using computational fluid dynamics. The finite volume-based finite element method was used in the simulation based on the 3D complex geometry of TBM. In order to validate the numerical results, the air velocity inside the Chamshir tunnel was measured experimentally at different sections. With a length of 7050 m and a final diameter of 4.6 m, the Chamshir water transport tunnel is located in the south of Iran. The results obtained show that there is not enough airflow in 59.6% of the TBM space in the current working conditions. In other words, there are many dead zones from the control cabin to the end of gantry 6 in the backup system. Several applicable scenarios were studied to remove the dead zone area and optimize the airflow velocity by employing high capacity jet fan in the ventilation system. The results show that the dead zone volume can be decreased by about 5.21% by increasing the airflow rate of the jet fan.
Exploitation
S. Soltani-Mohammadi; A. Soltani; B. Sohrabian
Abstract
Due to the nature of the geological and mining activities, different input parameters in the grade estimation and mineral resource evaluation are always tainted with uncertainties. It is possible to investigate the uncertainties related to the measurements and parameters of the variogram model using ...
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Due to the nature of the geological and mining activities, different input parameters in the grade estimation and mineral resource evaluation are always tainted with uncertainties. It is possible to investigate the uncertainties related to the measurements and parameters of the variogram model using the fuzzy kriging method instead of the kriging method. The fuzzy kriging theory has already been the subject of relatively various research studies but the main weak point in such studies is that the results of the fuzzy estimations are not used in decision-making and planning. A very common, but key, tool of decision-making for mining engineers is the tonnage-average grade models. Under conditions where measurements or/and variogram model parameters are tainted with uncertainties, the tonnage-average grade model will be uncertain as well. Therefore, it is necessary to use the fuzzy tonnage-grade model instead of the crisp ones, and the next analysis steps and decision-makings are done accordingly. In this paper, the computational principles of the fuzzy tonnage-average grade curve and a case study regarding its usage are presented.
