V. Sarfarazi; K. Asgari; Sh. Mohamadi Bolban Abad
Abstract
The interaction between an internal hole and two surrounded joints under a uniaxial compression are examined using the experimental and discrete element procedures. Inside the concrete sample, two notches and an internal hole are created. The joint angle change from 0° to 90° with an increment ...
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The interaction between an internal hole and two surrounded joints under a uniaxial compression are examined using the experimental and discrete element procedures. Inside the concrete sample, two notches and an internal hole are created. The joint angle change from 0° to 90° with an increment of 30°. The distances between the joint and the internal hole are 2 cm and 3 cm. Also the numerical models are provided. The joint angle change from 0° to 90° with an increment of 15°. The distances between the joint and the internal hole are 2 cm, 3 cm, and 4 cm. The compressive strength is 7.2 MPa. The rate of loading is 0.005 mm/s. The experiment indicates that the failure process is significantly dependent on the notch angle and the joint distance from the hole. The pattern of fracture and mechanism of failure of joints affect the shear strengths of the samples. The models with joint angles of 30° and 60° have a less compressive strength since the pure tensile failure occurs in these configurations. The model strength decreases with decrease in the join spacing. In fact, in the case that the joint spacing is 2 cm, the interaction between the hole and the neighboring joint is so strong. Consequently, the compressive strength is declined. In both approaches of the numerical simulation and experimental methods, the pattern and strength of failure are identical.
Kashitij Guleria; Ravi Kumar Sharma
Abstract
This paper discusses the applications of industrial waste like waste foundry sand (10%, 20%, 30%, and 40%) and calcium carbide residue (3%, 6%, 9%, and 12%) blended with polypropylene fibre (0.25%, 0.50%, 0.75%, and 1%) for soil stabilization. The purpose of this study is to develop a composite of clayey ...
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This paper discusses the applications of industrial waste like waste foundry sand (10%, 20%, 30%, and 40%) and calcium carbide residue (3%, 6%, 9%, and 12%) blended with polypropylene fibre (0.25%, 0.50%, 0.75%, and 1%) for soil stabilization. The purpose of this study is to develop a composite of clayey soil mixed with different additives, so it can be used for improving the geotechnical properties of the clayey soil. Multiple tests are conducted including differential free swell, Atterberg's limits test, compaction tests, unconfined compression test (UCS), and California-bearing ratio test (CBR) on clay soil individually and in different combinations and proportions with additive mixed with each other. The optimum percentage for the additives is found by performing differential free swell index and Atterberg limits test. The results demonstrate that the inclusion of additives in the clayey soil decreases the differential free swell and plasticity index of the composite but raises the composite UCS and CBR values. The maximum increase in the UCS and CBR values is obtained for optimum combination of C:PP:WFS:CC::76.25:0.75:20:3. Based on the CBR values, the thickness of flexible pavement is designed using the IITPAVE software. The results of the software analysis show a reduction in the pavement thickness for various values of commercial vehicles per day (1000, 2000, and 5000) for all combinations. The maximum reduction in layer thickness and construction costs is noticed for C:PP:WFS:CC:76.25:0.75:20:3. To further examine the improvement in the geotechnical properties of soil, calcium carbide residue, and waste foundry sand can be blended with nano-additives for potential uses.
F. Moradpouri; A. Moradzadeh; R. Cruz Pestana; M. Soleimani Monfared
Abstract
In this paper, first the limitations of the ray-based method and the one-way wave-field extrapolation migration (WEM) in imaging steeply dipping structures are discussed by some examples. Then a new method of the reverse time migration (RTM), used in imaging such complex structures is presented. The ...
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In this paper, first the limitations of the ray-based method and the one-way wave-field extrapolation migration (WEM) in imaging steeply dipping structures are discussed by some examples. Then a new method of the reverse time migration (RTM), used in imaging such complex structures is presented. The proposed method uses a new wave-field extrapolator called the Leapfrog-Rapid Expansion Method (L-REM) for wave-field extrapolation. This improved method also includes a new imaging condition based on Poynting vector for wave-field separation and calculating the reflection angles. Afterwards, the results obtained for the application of the new RTM method are compared with those obtained by the harmonic-source method as a delay shot or plane wave RTM. Finally, the efficiency of these imaging methods is tested using the BP 2004 2D seismic dataset. The results obtained indicate the superiority of the presented RTM method in imaging such steep dip structures in comparison with the other imaging procedures.
Exploitation
K. Ghanbari; M. Ataei; F. Sereshki; A. Saffari
Abstract
The presence of methane in coal mines is one of the major problems in underground coal mines. Every year, in underground coal mines, a lot of casualties due to outbursts and explosions of methane gas is occurring. Existence of this gas in the mines not only creates a difficult and dangerous situation ...
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The presence of methane in coal mines is one of the major problems in underground coal mines. Every year, in underground coal mines, a lot of casualties due to outbursts and explosions of methane gas is occurring. Existence of this gas in the mines not only creates a difficult and dangerous situation for work but also makes it more expensive. The release of this gas to the air causes a further pollution of the atmosphere and increases the greenhouse gases in the air. Thus Coal Bed Methane (CBM) drainage before, during, and after coal mining is necessary. Accordingly, the CBM drainage can reduce the risks involved in these mines. In the past decade, CBM has offered a significant potential to meet the ever-growing energy demand and can decrease the disastrous events. In this research work, the CBM potential in Eastern Kelariz, Western Razmja, Bornaky, Bozorg, Razzi, and Takht coal mines of Eastern Alborz coal mines company is investigated using the rock engineering systems (RES) based on the intrinsic and geological parameters. Nine main parameters are considered for modeling CBM, and the interactions between these parameters are calculated by a proposed system. Based on the RES method, the parameters that are dominant (depth of cover) or subordinate (gas content) and also the parameters that are interactive are introduced. The proposed approach could be a simple but efficient tool in the evaluation of the parameters affecting CBM, and hence be useful in decision-making. The results obtained show that Razzi coal mine has a good potential to perform CBM drainage.
A. Yusefi; H. R. Ramazi
Abstract
This paper presents an innovative solution for estimating the proximate parameters of coal beds from the well-logs. To implement the solution, the C# programming language was used. The data from four exploratory boreholes was used in a case study to express the method and determine its accuracy. Then ...
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This paper presents an innovative solution for estimating the proximate parameters of coal beds from the well-logs. To implement the solution, the C# programming language was used. The data from four exploratory boreholes was used in a case study to express the method and determine its accuracy. Then two boreholes were selected as the reference, namely the boreholes with available well-logging results and the proximate analysis data. The values of three well-logs were selected to be implemented in a system of equations that was solved, and the effect of each well-log on the estimated values of the proximate parameter was expressed as a coefficient called the effect factor. The coefficients were incorporated in an empirical relationship between the parameter and the three well-logs. To calculate the coefficients used for the most accurate estimation, a total of 22960 systems of equations were defined and solved for every three logs. As there was the possibility of 560 combinations for selecting three logs from all the available 16 logs, the three equation-three variable systems were solved more than 12 million times. The programming methods were utilized to achieve the final results. The results of each system were tested for deviation of the estimated values of volatile matter, ash, and moisture, and the coefficients of the lowest deviation were accepted to be applied in the relation. Implementing this method for estimating the volatile matter resulted in an average deviation of 10.5%. The corresponding estimated values of the ash and moisture contents were 22% and 14%, respectively.
M. Kamran
Abstract
The blasting operation is an important rock fragmentation technique employed in several foundation engineering disciplines such as mining, civil, tunneling, and road planning. Back-break (BB) is one of the adverse effects caused by the blasting operations that produces several effects including vulnerability ...
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The blasting operation is an important rock fragmentation technique employed in several foundation engineering disciplines such as mining, civil, tunneling, and road planning. Back-break (BB) is one of the adverse effects caused by the blasting operations that produces several effects including vulnerability of mining machinery, bench slope design, and risks to the next blast-patterns due to the eruption of gases from several discontinuities in jointed rock masses. Several techniques have been executed by the researchers in order to predict BB in the blasting operations. However, this is the first work to implement a-state-of-the-art Catboost-based t-distributed stochastic neighbor embedding (t-SNE) approach to predict BB. A total of 62 datasets having 12 influential BB-generating features are collected from genuine blasting patterns. A novel dimensionality depletion technique t-SNE that operates the Kullback-Leibler divergence interpretation is employed to tailor the pioneer exaggeration of the blasting dataset. Then the t-SNE dataset obtained is split into a 70:30 ratio of the training and testing datasets. Finally, the Catboost method is implemented on a low-dimensionality blasting database. The performance evaluation criterion confirms that the BB predictive model is more stable with a goodness of fit = 99.04 in the training dataset, 97.26 in the testing datasets, and could anticipate a more accurate prediction. Moreover, the model presented in this work performs superior to the existing publicly available execution of BB. In summary, this model can be practiced in order to predict BB in several rock engineering practices and mining industry scenarios.
Akbar Esmaeilzadeh; Sina Shaffiee Haghshenas; Reza Mikaeil; Giuseppe Guido; Roohollah Shirani Faradonbeh; Roozbeh Abbasi Azghan; Amir Jafarpour; Shadi Taghizadeh
Abstract
Iran is one of the countries with the largest number of quarry mines in the world. Diamond cutting wire is usually used in quarries to cut dimension stone cubes, which is accompanied by hazardous events. Therefore, detecting and investigating the possible quarry risks is crucial to have a safe and sustainable ...
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Iran is one of the countries with the largest number of quarry mines in the world. Diamond cutting wire is usually used in quarries to cut dimension stone cubes, which is accompanied by hazardous events. Therefore, detecting and investigating the possible quarry risks is crucial to have a safe and sustainable mining operation. In mine exploitation, maintaining the safety of vehicles and increasing the knowledge of personnel regarding safety issues can considerably mitigate the number or radius of effect of hazards. Hence, the incidents and risks in the West-Azerbaijan quarries in Iran are investigated in this work. To do so, a list of the hazards and their descriptions are first prepared. Then the hazard risk rating is conducted using the Failure Modes and Effects Analysis (FMEA) method. The number of priorities is calculated for each incident based on probability, intensity, and risk detection probability. Finally, the main causes of risks in the studies quarries are identified. The results obtained show that the most likely dangers in dimensional stone mines in West Azerbaijan are diamond cutting wire breaking, rock-fall, and car accidents, with the priority numbers of 216, 180, and 135, respectively. These hazards can be mitigated by applying some preservative activities such as timely cutting wire replacement, utilizing an intelligent system for cutting tool control, necessary personal training, and considering some preservative points.
K. Tolouei; E. Moosavi; A.H. Bangian Tabrizi; P. Afzal; A. Aghajani Bazzazi
Abstract
It is significant to discover a global optimization in the problems dealing with large dimensional scales to increase the quality of decision-making in the mining operation. It has been broadly confirmed that the long-term production scheduling (LTPS) problem performs a main role in mining projects to ...
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It is significant to discover a global optimization in the problems dealing with large dimensional scales to increase the quality of decision-making in the mining operation. It has been broadly confirmed that the long-term production scheduling (LTPS) problem performs a main role in mining projects to develop the performance regarding the obtainability of constraints, while maximizing the whole profits of the project in a specific period. There is a requirement for improving the scheduling methodologies to get a good solution since the production scheduling problems are non-deterministic polynomial-time hard. The current paper introduces the hybrid models so as to solve the LTPS problem under the condition of grade uncertainty with the contribution of Lagrangian relaxation (LR), particle swarm optimization (PSO), firefly algorithm (FA), and bat algorithm (BA). In fact, the LTPS problem is solved under the condition of grade uncertainty. It is proposed to use the LR technique on the LTPS problem and develop its performance, speeding up the convergence. Furthermore, PSO, FA, and BA are projected to bring up-to-date the Lagrangian multipliers. The consequences of the case study specifies that the LR method is more influential than the traditional linearization method to clarify the large-scale problem and make an acceptable solution. The results obtained point out that a better presentation is gained by LR–FA in comparison with LR-PSO, LR-BA, LR-Genetic Algorithm (GA), and traditional methods in terms of the summation net present value. Moreover, the CPU time by the LR-FA method is approximately 16.2% upper than the other methods.
Imran Khan; Ravi Kumar Sharma
Abstract
An experimental study is carried out to improve the bearing capacity of soils by using geotextile. In the present study geotextile (tire reinforcement) is used as geotextile, whereas sand is used as a soil medium. This research work presents the results of laboratory load tests on model square footings ...
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An experimental study is carried out to improve the bearing capacity of soils by using geotextile. In the present study geotextile (tire reinforcement) is used as geotextile, whereas sand is used as a soil medium. This research work presents the results of laboratory load tests on model square footings supported on reinforced sand beds. A total of twenty-seven load tests are conducted to evaluate the effects of single layer reinforcement placed below square model footings. The parameters of the testing program of the research work are the depth of reinforcement, the plan area of reinforcement, and the number of reinforcements. From the experimental data, it is indicated that there is an optimum reinforcement depth at which the bearing capacity is the highest. Also, the optimum size of reinforcement is found to be 1.5 B×1.5 B irrespective of the type of reinforcing materials used. The bearing capacity of reinforced sand is also found to increase with the number of reinforcement layer and reinforcement size when the reinforcement is placed within a certain effective zone with high relative density. The optimum placement position of geotextile is found to be 0.5B to 0.75B from the base of the footing .The tests are done at two different relative densities, i.e., 40% and 60%. The bulk unit weight of sandy soil is 14.81 KN/m³. Maximum gain in load carrying capacity is obtained when depth of reinforcement/width of footing (Dr/B) is 0.5 at relative density of 40% and 0.75 at a relative density of 60%.In addition, the data indicate that increasing reinforcement beyond a certain value would not bring about further increase in the bearing capacity of the soil.
J. Ghiasi-Freez; M. Ziaii; A. Moradzadeh
Abstract
An accurate reservoir characterization is a crucial task for the development of quantitative geological models and reservoir simulation. In the present research work, a novel view is presented on the reservoir characterization using the advantages of thin section image analysis and intelligent classification ...
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An accurate reservoir characterization is a crucial task for the development of quantitative geological models and reservoir simulation. In the present research work, a novel view is presented on the reservoir characterization using the advantages of thin section image analysis and intelligent classification algorithms. The proposed methodology comprises three main steps. First, four classes of reservoir intervals are defined using a limited number of porosity and permeability values obtained from the core plugs of Kangan and Dalan formations. Then seven micro-scale features including distribution of pore types (interparticle, interaparticle, moldic, and vuggy), pore complexity, and cement distribution as well as textural characteristics are extracted from thin section images. Finally, the features extracted from each photomicrograph and its corresponding reservoir class are used as the training data for several intelligent classifiers including decision trees, discriminant analysis functions, support vector machines, K-nearest neighbor models and two ensemble algorithms, named bagging and boosting. The relationship between the micro-scale features and the reservoir classes was studied. Performance of all classifiers is evaluated using the concepts of accuracy, precision, recall, and harmonic average. The results obtained showed that the bagging decision tree delivered the best performance among the models and improved the accuracy of simple models up to 7.7% compared with the best single classifier.
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.
Muhammad Ahsan M.; T. Celik; B. Genc
Abstract
The distribution of stream sediments is usually considered as an important and very useful tool for the early-stage exploration of mineralization at the regional scale. The collection of stream samples is not only time-consuming but also very costly. However, the advancements in space remote sensing ...
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The distribution of stream sediments is usually considered as an important and very useful tool for the early-stage exploration of mineralization at the regional scale. The collection of stream samples is not only time-consuming but also very costly. However, the advancements in space remote sensing has made it a suitable alternative for mapping of the geochemical elements using satellite spectral reflectance. In this research work, 407 surface stream sediment samples of the zinc (Zn) and lead (Pb) elements are collected from Central Wales. Five machine learning models, namely the Support Vector Regression (SVR), Generalized Linear Model (GLM), Deep Neural Network (DNN), Decision Tree (DT), and Random Forest (RF) regression, are applied for prediction of the Zn and Pb concentrations using the Sentinel-2 satellite multi-spectral images. The results obtained based on the 10 m spatial resolution show that Zn is best predicted with RF with significant R2 values of 0.74 (p < 0.01) and 0.7 (p < 0.01) during training and testing. However, for Pb, the best prediction is made by SVR with significant R2 values of 0.72 (p < 0.01) and 0.64 (p < 0.01) for training and testing, respectively. Overall, the performance of SVR and RF outperforms the other machine learning models with the highest testing R2 values.
Kamran Abbas; Adeel Nawazish; Navid Feroze; Nasar Male Ahmed
Abstract
In this work, an attempt is made to fit and identify the most appropriate probability distribution(s) for the analysis of seventeen rock samples including diorite, gypsum, marble, basalt, sandstone, limestone, apatite, slate, dolomite, granite-II, schist, gneiss, amphibolite, hematitle, magnetite, Shale, ...
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In this work, an attempt is made to fit and identify the most appropriate probability distribution(s) for the analysis of seventeen rock samples including diorite, gypsum, marble, basalt, sandstone, limestone, apatite, slate, dolomite, granite-II, schist, gneiss, amphibolite, hematitle, magnetite, Shale, and granite-I using laser-induced breakdown spectroscopy. The graphical assessment and visualization endorse that the rock dataset series are positively skewed. Therefore, Frechet, Weibull, log-logistic, log-normal, and generalized extreme value distributions are considered as candidate distributions, and the parameters of these distributions are estimated by maximum likelihood and Bayesian estimation methods. The goodness of fit test and model selection criteria such as the Kolmogorov-Smirnov test, Akaike Information Criterion, and Bayesian Information Criterion are used to quantify the accuracy of the predicted data using theoretical probability distributions. The results show that the Frechet, Weibull, and log-logistic distributions are the best-fitted probability distribution for rock dataset. Cluster analysis is also used to classify the selected rocks that share common characteristics, and it is observed that diorite and gypsum are placed in one cluster. However, slate, dolomite, marble, basalt, sandstone, schist, granite-II, and gneiss rocks belong to different clusters. Similarly, limestone and apatite appeare in one cluster. Likewise, shale, granite-I, magnetite, amphibolite, and hematitle appeare in a different cluster. The current work demonstrate that coupling of laser-induced breakdown spectroscopy with suitable statistical tools can identify and classify the rocks very efficiently.
V. Sarfarazi; A. Tabaroei
Abstract
In this work, the effect of rock bolt angle on the shear behavior of Rock Bridges is investigated using the particle flow code in two dimensions (PFC2D) for three different Rock Bridge lengths. Firstly, the calibration of PF2D is performed to reproduce the gypsum sample. Then the numerical models with ...
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In this work, the effect of rock bolt angle on the shear behavior of Rock Bridges is investigated using the particle flow code in two dimensions (PFC2D) for three different Rock Bridge lengths. Firstly, the calibration of PF2D is performed to reproduce the gypsum sample. Then the numerical models with the dimensions of 100 mm * 100 mm are prepared. The Rock Bridge is created in the middle of the model by removal of the narrow bands of discs from it. The uniaxial compressive strength of the Rock Bridge is 7.4 MPa. The Rock Bridge lengths are 30 mm, 50 mm, and 70 mm. The rock bolt is calibrated by a parallel bond. The tensile strength of the simulated rock bolt is 360 MPa.One rock bolt is implemented in the Rock Bridge. The rock bolt angles related to the horizontal axis are the changes from 0 to 75 degrees. Totally, 18 models are prepared. The shear test condition is added to the models. The normal stress is fixed at 2 MPa, and the shear load is added to the model till failure occurs. The results obtained show that in a fixed rock bolt angle, the tensile crack initiates from the joint tip and propagates parallel to the shear loading axis till coalescence to rock bolt. In a constant Rock Bridge length, the shear strength decreases with increase in the rock bolt angle. The highest shear strength occurs when the rock bolt angle is 0°.
Environment
Şener Ceryan; Pijush Samui; Osman Samed Özkan; Samet Berber; Şule Tüdeş; Hakan Elci; Nurcihan Ceryan
Abstract
Balikesir province Akcay district (Biga Peninsula, South Marmara Region, Turkey); the studied area is located on the southern branch of the North Anatolian Fault Zone, where some earthquake, 1867 Edremit (Mw =7.0), 1919 Ayvalik-Sarmisakli (Mw = 7.0), 1944 Edremit (Mw =6.4) and 1953 Yenice (Mw = 7.2) ...
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Balikesir province Akcay district (Biga Peninsula, South Marmara Region, Turkey); the studied area is located on the southern branch of the North Anatolian Fault Zone, where some earthquake, 1867 Edremit (Mw =7.0), 1919 Ayvalik-Sarmisakli (Mw = 7.0), 1944 Edremit (Mw =6.4) and 1953 Yenice (Mw = 7.2) earthquakes occurred in the historical and the instrumental period. In the said area, generally, the groundwater level is high and sandy soils are widespread. In this study, therefore topography, depth of groundwater table and soil characteristics of the said area were investigated in terms of susceptibility to liquefaction. In addition, the safety factor against liquefaction (FL) for the soil layers were determined by using simple procedure based on SPT-N values. Then the spatial distributions of the safety factor at 3 m, 6 m, 9 m, 12 m, 15 m and 18 m depths were obtained. Taking into considering FL values obtained, the liquefaction potential index and the liquefaction severity index of soil profile in the location of boring were calculated, then the spatial distributions of these index were obtained. According to the maps obtained, 5.8% of the studied area has low liquefaction potential, 10.7% medium liquefaction potential, 18.3% high liquefaction potential, and 53.8% very high liquefaction potential, and 22.7% of the study area has very low liquefaction severity, 17.1% low liquefaction severity, 47.7% moderate liquefaction severity, and 1.1% high liquefaction severity and 11.4% of the studied area has none-liquefiable soil.
E. von Sperling; C.A.P. Grandchamp
Abstract
The paper presents the case study of the current formation of a Brazilian pit lake from an iron ore mining activity. The water used for the filling of the lake comes from rain, ground water and the complementary pumpage from a close river. At its final stage, which will be reached around year 2018, Lake ...
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The paper presents the case study of the current formation of a Brazilian pit lake from an iron ore mining activity. The water used for the filling of the lake comes from rain, ground water and the complementary pumpage from a close river. At its final stage, which will be reached around year 2018, Lake Aguas Claras will have a surface area of 0.67 km2 and the depth of 234 m, which will make it the deepest lake in the country. The filling of the lake began in the year 2001 and a monthly monitoring programme (physical, chemical and biological characteristics) is since then in course Theanalyses show that Lake Âguas Claras presents a very good water quality (well oxygenated, low values of colour and turbidity, limited degree of mineralization, pH slightly alkaline, low nutrient concentrations, excellent bacteriological conditions), together with a remarkable shift in the dominance of phytoplanktonic groups, indicating the high instability of lakes that are undergoing a process of formation. One relevant point in the management of this valuable water resource is to create adequate conditions for the protection of the aquatic environment. Considering the very probable maintenance of these favourable characteristics in future years, the possible uses of the lake will be directed to recreation (swimming, diving, sailing and fishing), amenity value and water supply.
J. Gholamnejad; A.R. Mojahedfar
Abstract
The determination of the Ultimate Pit Limit (UPL) is the first step in the open pit mine planning process. In this stage
that parts of the mineral deposit that are economic to mine are determined. There are several mathematical, heuristic
and meta-heuristic algorithms to determine UPL. The optimization ...
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The determination of the Ultimate Pit Limit (UPL) is the first step in the open pit mine planning process. In this stage
that parts of the mineral deposit that are economic to mine are determined. There are several mathematical, heuristic
and meta-heuristic algorithms to determine UPL. The optimization criterion in these algorithms is maximization of the
total profit whilst satisfying the operational requirement of safe wall slopes. In this paper the concept of largest pit with
non- negative value is suggested. A mathematical model based on integer programming is then developed to deal with
this objective. This model was applied on an iron ore deposit. Results showed that obtained pit with this objective is
larger than that of obtained by using net profit maximization and contains more ore, whilst the total net profit of
ultimate pit is not negative. This strategy can also increase the life of mine which is in accordance to the sustainable
development principals.
Z. Bahri; S.Z. Shafaei; M. Karamoozian
Abstract
Investigations were carried out on coal tailings by conventional cell and column flotation techniques. Tests were conducted to assess processing coal tailings of Alborz Markazi coal washing plant in Iran by column flotation. The effects of reagent type/dosage were investigated with conventional flotation ...
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Investigations were carried out on coal tailings by conventional cell and column flotation techniques. Tests were conducted to assess processing coal tailings of Alborz Markazi coal washing plant in Iran by column flotation. The effects of reagent type/dosage were investigated with conventional flotation and their results were used in the performance of column flotation. Also the effects of the air rate, the feeding rate, the wash water rate, the frother concentration, the collector dosage were evaluated with column flotation. These coal tailings have an average of 56% ash. This paper used factorial design to optimize grade and recovery of coal tailings. The column flotation results indicated concentrate produced under optimum conditions, kerosene, 2909 g/t; superficial air velocity, 0.96 cm/s; feeding rate, 3.6 lit/min; superficial wash water velocity, 0.98 lit/min; frother dosage, 350 g/t having an ash content of 12.11% and a combustible recovery of 28.51% was obtained.
Rock Mechanics
Jitendra Singh Yadav; Anant Saini
Abstract
The goal of this research work was to use an Artificial Neural Network (ANN) model to predict the ultimate bearing capacity of circular footing resting on recycled construction waste over loose sand. A series of plate load tests were conducted by varying the thickness of two sizes of recycled construction ...
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The goal of this research work was to use an Artificial Neural Network (ANN) model to predict the ultimate bearing capacity of circular footing resting on recycled construction waste over loose sand. A series of plate load tests were conducted by varying the thickness of two sizes of recycled construction waste (5 mm and 10.6 mm) layer (0.4d, 0.6d, 0.8d, 1d, and 1.2d, d: diameter of footing) prepared at different relative densities (30%, 50%, and 70%) overlaying. The ultimate bearing capacity obtained for various combinations was used to develop the ANN model. The input parameters of the ANN model were thickness of recycled construction waste layer to diameter of circular footing ratio, angle of internal friction of sand, unit weight of sand, angle of internal friction of recycled construction waste and unit weight of recycled construction waste, and the model's output parameter was ultimate bearing capacity. The FANN-SIGMOD_SYMMETRIC model with topology 3-2-1 provided a higher estimate of the ultimate bearing capacity of circular footing, according to the ANN findings. The sensitivity analysis also revealed that the unit weight of sand and angle of internal friction of sand had insignificant effects on ultimate bearing capacity. The estimated ultimate bearing capacity was most affected by the angle of internal friction of recycled construction waste. The result of multiple linear regression analysis was not as good as the ANN model at predicting the ultimate bearing capacity.
Ali Asghar khodaiari; A Jafarnejad
Abstract
Maximizing economic earnings is the most common goal in cut-off grade optimization of open-pit mining operations. When this is the case, the price of the product has a critical effect on optimum value of cut-off grade. This paper investigates the relationship between optimum cut-off grade and price to ...
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Maximizing economic earnings is the most common goal in cut-off grade optimization of open-pit mining operations. When this is the case, the price of the product has a critical effect on optimum value of cut-off grade. This paper investigates the relationship between optimum cut-off grade and price to maximize total cash flow and net percent value (NPV) of operation. In order to visualize this relationship, two hypothetical mines were employed. To determine the optimum value of cut-off grade in different cases, two nonlinear programming models were formulated, and then, all models were solved using Solver in Excel. The results show that the optimum cut-off grade would always be a descending function of price when we intend to maximize total cash flow. On the other hand, this function may be descending or ascending when we intend to maximize NPV. This result also reveals that both maximum cash flow and maximum NPV always increase and decrease, respectively when the price of product increases or decreases.
S. Mohammadi; M. Ataei; R. Khalokakaei; E. Pourzamani
Abstract
Optimization of the exploitation operation is one of the most important issues facing the mining engineers. Since several technical and economic parameters depend on the cut-off grade, optimization of this parameter is of particular importance. The aim of this optimization is to maximize the net present ...
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Optimization of the exploitation operation is one of the most important issues facing the mining engineers. Since several technical and economic parameters depend on the cut-off grade, optimization of this parameter is of particular importance. The aim of this optimization is to maximize the net present value (NPV). Since the objective function of this problem is non-linear, three methods can be used to solve it: analytical, numerical, and meta-heuristic. In this study, the Golden Section Search (GSS) method and the Imperialist Competitive Algorithm (ICA) are used to optimize the cut-off grade in mine No. 1 of the Golgohar iron mine. Then the results obtained are compared. Consecuently, the optimum cut-off grades using both methods are calculated between 40.5% to 47.5%. The NPVs obtained using the GSS method and ICA were 18487 and 18142 billion Rials, respectively. Thus the value for GSS was higher. The annual number of iterations in the GSS method was equal to 18, and that for ICA was less than 18. Also computing and programming the process of golden section search method were easier than those for ICA. Therefore, the GSS method studied in this work is of a higher priority.
A. Zarean; R. Poormirzaee
Abstract
Shear-wave velocity ( ) is an important parameter used for site characterization in geotechnical engineering. However, dispersion curve inversion is challenging for most inversion methods due to its high non-linearity and mix-determined trait. In order to overcome these problems, in this study, a joint ...
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Shear-wave velocity ( ) is an important parameter used for site characterization in geotechnical engineering. However, dispersion curve inversion is challenging for most inversion methods due to its high non-linearity and mix-determined trait. In order to overcome these problems, in this study, a joint inversion strategy is proposed based on the particle swarm optimization (PSO) algorithm. The seismic data considered for designing the objects are the Rayleigh wave dispersion curve and seismic refraction travel time. For joint inversion, the objective functions are combined into a single function. The proposed algorithm is tested on two synthetic datasets, and also on an experimental dataset. The synthetic models demonstrate that the joint inversion of Rayleigh wave and travel time return a more accurate estimation of VS in comparison with the single inversion Rayleigh wave dispersion curves. To prove the applicability of the proposed method, we apply it in a sample site in the city of Tabriz located in the NW of Iran. For a real dataset, we use refraction microtremor (ReMi) as a passive method for getting the Rayleigh wave dispersion curves. Using the PSO joint inversion, a three-layer subsurface model was delineated.The results obtained for the synthetic datasets and field dataset show that the proposed joint inversion method significantly reduces the uncertainties in the inverted models, and improves the revelation of boundaries.
H. R. Nejati; Seyed A. Moosavi
Abstract
Assessment of the correlation between rock brittleness and rock fracture toughness has been the subject of extensive research works in the recent years. Unfortunately, the brittleness measurement methods have not yet been standardized, and rock fracture toughness cannot be estimated satisfactorily by ...
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Assessment of the correlation between rock brittleness and rock fracture toughness has been the subject of extensive research works in the recent years. Unfortunately, the brittleness measurement methods have not yet been standardized, and rock fracture toughness cannot be estimated satisfactorily by the proposed indices. In the present study, statistical analyses are performed on some data collected from the literature to develop two equations for estimation of modes I and II fracture toughness. Then a probabilistic sensitivity analysis is performed to determine the impact of the input parameters on the output ones. Based on the results obtained for the probabilistic analysis, a new empirical brittleness index including tensile strength, uniaxial compressive strength, and elastic modulus is suggested for estimating modes I and II fracture toughness. The analyses results reveal that the proposed index is capable of estimating rock fracture toughness with more satisfactory correlation compared to the previous indices.
L. Akpan; A. Celestine Tse; F. dumbari Giadom; C. Iorfa Adamu
Abstract
In this study, the chemical composition of water and soils contiguous to two abandoned coal mines in southeastern Nigeria, was assessed to evaluate the impact of water flow from the mines ponds on the geoenvironment and potential for acid mine drainage (AMD). Parameters including the pH, anions and cations, ...
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In this study, the chemical composition of water and soils contiguous to two abandoned coal mines in southeastern Nigeria, was assessed to evaluate the impact of water flow from the mines ponds on the geoenvironment and potential for acid mine drainage (AMD). Parameters including the pH, anions and cations, and the heavy metals were measured. These were used to evaluate contamination/pollution using hybrid factors including Pollution Load Index, factors, enrichment factors, pollution load index and index of geoaccumulation. The pH range of 3.4 to 5.9 classified the water as weakly to strongly acidic, typical of AMD. The SO42– ion, which indicates pollution by mine waters, showed moderate to high concentrations. Iron, zinc lead and copper were the most abundant heavy metals. Pollution Load Index values were greater than unity which show progressive deterioration in water and sediment quality. The Enrichment Factor values of up to 1 indicated enrichment through lithogenic and anthropogenic sources. The mine dumps serve as pools that can release toxic heavy metals into the water bodies by various processes of remobilization. Based on the lithology, mineralogy, chemical concentrations and environmental factors, the study has shown that there exists a potential for the generation of AMD. The heavy metals enriched mine flow, especially iron, empty into the nearby water bodies which serve as sources of municipal water supply. Consumption of untreated water over a prolonged period from these water sources may be detrimental to health. Remedial measure and continuous monitoring are recommended for good environmental stewardship.
Rock Mechanics
S. Moshrefi; K. Shahriar; A. Ramezanzadeh; K. Goshtasbi
Abstract
A rock failure criterion is very important for prediction of the ultimate strength in rock mechanics and geotechnics; it is determined for rock mechanics studies in mining, civil, and oil wellborn drilling operations. Also shales are among the most difficult to treat formations. Therefore, in this research ...
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A rock failure criterion is very important for prediction of the ultimate strength in rock mechanics and geotechnics; it is determined for rock mechanics studies in mining, civil, and oil wellborn drilling operations. Also shales are among the most difficult to treat formations. Therefore, in this research work, using the artificial neural network (ANN), a model was built to predict the ultimate strength of shale, and comparison was made with support vector machine (SVM), multiple linear regression models, and the widely used conventional polyaxial failure criteria in the stability analysis of rock structures, Drucker-Prager, and Mogi-Coulomb. For building the model, the corresponding results of triaxial and polyaxial tests have been performed on shales by various researchers. They were collected from reliable published articles. The results obtained showed that a feed forward back propagation multi-layer perceptron (MLP) was used and trained using the Levenberg–Marquardt algorithm, and the 2-4-1 architecture with root-mean-square-error (RMSE) of 24.41 exhibits a better performance in predicting the ultimate strength of shale in comparison with the investigated models. Also for further validation, triaxial tests were performed on the deep shale specimens. They were prepared from the Ramshire oilfield in SW Iran. The results obtained were compared with ANN, SVM, multiple linear regression models, and the conventional failure criterion prediction. They showed that the ANN model predicted ultimate strength with a minimum error and RMSE being equal to 43.81. Then the model was used for prediction of the threshold broken pressure shale layer in the Gachsaran oilfield in Iran. For this, a vertical and horizontal stress was calculated based on a depth of shale layer. The threshold broken pressure was calculated for the beginning and ending of a shale layer to be 154.21 and 167.98 Mpa, respectively.
