Mineral Processing
Chaimae Loudari; Moha Cherkaoui; Imad El Harraki; Rachid Bennani; Mohamed El Adnani; EL Hassan Abdelwahed; Intissar Benzakour; François Bourzeix; Karim Baina
Abstract
Energy efficiency and product quality control are critical concerns in grinding mill operations, particularly within the innovative context of Mine 4.0. This study introduces a novel Genetic Algorithm (GA)-based optimization framework specifically developed to address these challenges. Given the mining ...
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Energy efficiency and product quality control are critical concerns in grinding mill operations, particularly within the innovative context of Mine 4.0. This study introduces a novel Genetic Algorithm (GA)-based optimization framework specifically developed to address these challenges. Given the mining industry’s significant energy consumption, especially in grinding processes, the proposed approach optimizes key parameters such as feed composition, water flow rates, and power consumption levels, while maintaining sieve refusal near the target threshold of 20%. Using real operational data from a Moroccan plant, the GA achieved a Mean Absolute Error (MAE) of 0.47, outperforming Simulated Annealing (SA) and Particle Swarm Optimization (PSO), which yielded MAEs of 1.14 and 0.74, respectively. The GA also demonstrated superior convergence stability and robustness, as evidenced by lower variability in predicted power consumption. These results validate the effectiveness of the GA framework in navigating nonlinear, high-dimensional parameter spaces and improving energy efficiency while ensuring product quality consistency. Ultimately, this research confirms the potential of metaheuristic optimization in enhancing grinding mill efficiency and supports the broader shift towards intelligent and sustainable mining operations under the Mine 4.0 paradigm.
R. Marandi; F. Doulati Ardejani; H. Amir Afshar
Abstract
The biosorption of heavy metals can be an effective process for the removal of such metal ions from aqueous solutions. In this study, the adsorption properties of nonliving biomass of phanerochaete chrysosporium for Pb (II) and Zn (II) were investigated by the use of batch adsorption techniques. The ...
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The biosorption of heavy metals can be an effective process for the removal of such metal ions from aqueous solutions. In this study, the adsorption properties of nonliving biomass of phanerochaete chrysosporium for Pb (II) and Zn (II) were investigated by the use of batch adsorption techniques. The effects of initial metal ion concentration, initial pH, biosorbent concentration, stirring speed, temperature and contact time on the biosorption efficiency were studied. The experimental results indicated that the uptake capacity and adsorption yield of one the metal ion were reduced by the presence of the other one. The optimum pH was obtained as 6.0. The experimental adsorption data were fitted to both Langmuir and Frundlich adsorption models for Pb (II) and to the Langmuir model for Zn (II) ion. The highest metals uptake values of 57 and 87 mg/g were calculated for Zn (II) and Pb (II) respectively. Desorption of heavy metal ions was performed by 50 mM HNO3 solution. The results indicated that the biomass of phanerochaete chrysosporium is a suitable biosorbent for the removal of heavy metal ions from the aqueous solutions.
A. R. Arab-Amiri; A. Moradzadeh; N. Fathianpour; B. Siemon
Abstract
Helicopter-borne frequency-domain electromagnetic (HEM) surveys are used extensively for mineral and groundwater
exploration and a number of environmental investigations. To have a meaningful interpretation of the measured multi-
frequency HEM data, in addition to the resistivity maps which are ...
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Helicopter-borne frequency-domain electromagnetic (HEM) surveys are used extensively for mineral and groundwater
exploration and a number of environmental investigations. To have a meaningful interpretation of the measured multi-
frequency HEM data, in addition to the resistivity maps which are provided in each frequency or for some particular
depth levels, it is a necessity to have a suitable modeling technique to produce resistivity cross-section along some
specific profiles. This paper aims to: (1) develop a new inversion method to handle HEM data; (2) compare its results
with the well known Amplitude, Niblett-Bostick (NB), and Siemon inversion methods. The basic formulation of this
new inversion routine was provided based on the Zonge spatial filtering procedure to cure static shift effect on the
magnetotelluric (MT) apparent resistivity curves. When the relevant formulas and the required algorithm for the inverse
modeling of HEM data were provided, they were then coded in Matlab software environment. This new inversion
program, named as SUTHEM, was used to invert some sets of one and two dimensional (1D and 2D) model synthetic
data which were contaminated by random noise. It was also applied to invert one set of real field data acquired in the
NW part of Iran by the DIGHEM system. The obtained results of this method and their comparison with those of the
aforementioned methods indicate that SUTHEM is able to produce the results like those produced by the commercial
Siemon routine. In addition, the new inversion method is superior to the Amplitude and the NB methods particularly in
inversion of the noisy data.
Rock Mechanics
Barkat Ullah; Raja Khurram Mahmood Khan
Abstract
Uniaxial compressive strength (UCS) is an essential feature for characterizing and classifying rock masses, forming a critical component of rock failure criteria with extensive applications in mining and geotechnical engineering. This study aims to evaluate the performance of different machine learning ...
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Uniaxial compressive strength (UCS) is an essential feature for characterizing and classifying rock masses, forming a critical component of rock failure criteria with extensive applications in mining and geotechnical engineering. This study aims to evaluate the performance of different machine learning (ML) models in forecasting the UCS of sandstone obtained from the Murree and Kamlial formations in the Muzaffarabad area, northwestern Himalayas, Pakistan. The ML models—namely artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS), support vector regressor (SVR), random forest (RF), and extreme gradient boosting (XGBoost)—were developed to predict UCS (MPa) based on porosity (η), point load index (Is(50)), Schmidt hammer rebound value (Rn), and aggregate impact value (AIV) as input variables. A dataset containing 80 points was divided using a 70:30 split ratio for training and testing sets. K-fold cross-validation (with 5 to 10 folds) was employed to enhance the models' generalization ability. The performance of the models was evaluated using mean absolute error (MAE), mean square error (MSE), root mean square error (RMSE), and coefficient of determination (R²). Results revealed that the XGBoost model outperformed the other models, achieving a high R² value of 0.99 and low error values for MAE (0.789), MSE (1.168), and RMSE (1.080). The overall accuracy of the models can be ranked as follows: XGBoost > RF > ANN > ANFIS > SVR. This study provides a benchmark for predicting the UCS of sandstones and similar rocks where complex geology complicates the collection of intact samples.
S. Bahrami; F. Doulati Ardejani
Abstract
In this study, a hybrid intelligent model has been designed to predict groundwater inflow to a mine pit during its advance. Novel hybrid method coupling artificial neural network (ANN) with genetic algorithm (GA) called ANN-GA, was utilised. Ratios of pit depth to aquifer thickness, pit bottom radius ...
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In this study, a hybrid intelligent model has been designed to predict groundwater inflow to a mine pit during its advance. Novel hybrid method coupling artificial neural network (ANN) with genetic algorithm (GA) called ANN-GA, was utilised. Ratios of pit depth to aquifer thickness, pit bottom radius to its top radius, inverse of pit advance time and the hydraulic head (HH) in the observation wells to the distance of observation wells from the centre of pit were used as inputs to the network. An ANN-GA with 4-5-3-1 arrangement was found capable to predict the groundwater inflow to mine pit. The accuracy and reliability of model was verified by field data. Predicted results were very close to the field data. The correlation coefficient (R) value was 0.998 for training set, and in testing stage it was 0.99.
S. Hadi Hosseini; Mohammad Ataie; Hamid Aghababaie
Abstract
In this paper, after collecting the rock samples from eight mines and one high way slope, the tests for determination of dry density, Uniaxial Compressive Strength, tensile Strength (Brazilian Test), elastic modulus, Schmidt hammer rebound number have been done on samples. In addition, in order to calculating ...
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In this paper, after collecting the rock samples from eight mines and one high way slope, the tests for determination of dry density, Uniaxial Compressive Strength, tensile Strength (Brazilian Test), elastic modulus, Schmidt hammer rebound number have been done on samples. In addition, in order to calculating the mean size of rock grains, quartz content, hardness and abrasivity, a thin sections of each rock have been studied. Then, the rock samples have been drilled using actual pneumatic top hammer drilling machine with 3½ inches diameter cross type bit. The regression analyses showed that Brazilian tensile strength (R2=0.81), uniaxial compressive strength (R2=0.77) and Schmidt hammer rebound (R2=0.73) are the most effective parameters on drilling rate and have a partly good correlation with drilling rate.
M. Najafi; Seyed M. E. Jalali; F. Sereshki; A. Yarahmadi Bafghi
Abstract
Performing a probabilistic study rather than a determinist one is a relatively easy way to quantify the uncertainty in an engineering design. Due to the complexity and poor accuracy of the statistical moment methods, the Monte Carlo simulation (MCS) method is wildly used in an engineering design. In ...
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Performing a probabilistic study rather than a determinist one is a relatively easy way to quantify the uncertainty in an engineering design. Due to the complexity and poor accuracy of the statistical moment methods, the Monte Carlo simulation (MCS) method is wildly used in an engineering design. In this work, an MCS-based reliability analysis was carried out for the stability of the chain pillars in the Tabas coal mine, located in Iran. For this purpose, the chain pillar strengths were calculated using the Madden formula, the vertical stress on the chain pillars was determined by an empirical method, and a numerical modeling was performed using the FLAC3D software. The results obtained for the probabilistic stability analysis of the chain pillars showed that the failure probability obtained for the designed pillars by applying the MCS method were approximately the same as that obtained by the advanced second moment (ASM) method, and the values obtained varied between 12 and 18 percent.
S.M.A Hosseini; F Sereshki; M Shariati; S.M.E Jalali; F Crotogino
Abstract
Creep phenomenon in rock engineering plays a key role in development of underground spaces as they must be stable enough for a long period of time. Current research involved designing and manufacturing of a new creep testing machine. The equipment is capable to perform simultaneous light-duty creep tests ...
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Creep phenomenon in rock engineering plays a key role in development of underground spaces as they must be stable enough for a long period of time. Current research involved designing and manufacturing of a new creep testing machine. The equipment is capable to perform simultaneous light-duty creep tests on more than one cylindrical rock samples at a very low cost.To evaluate the equipment’s performance, a series of creep test was performed on salt rock samples and their axial and lateral deformations were measured by dial gauges. Measurements were taken under constant temperature, humidity and sustained loads. The results revealed that the creep rate in lateral direction was far greater than in the axial direction. Another important conclusion was that both axial and lateral creep curves follow the same pattern with an idealized salt rock creep curve. Also, experiments indicated that the steady state creep rate increases with increasing initial stress state. Also, initial stress state showed a great influence on salt primary creep response.
Reza Rahmannejad; A.I. Sofianos
Abstract
Wall displacements and ground pressure acting on the lining of a tunnel increase with time. These time-dependent deformations are both due to face advance effect and to the time-dependent behavior of the rock mass. Viscoelastic materials exhibit both viscous and elastic behaviors. Thorough this ...
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Wall displacements and ground pressure acting on the lining of a tunnel increase with time. These time-dependent deformations are both due to face advance effect and to the time-dependent behavior of the rock mass. Viscoelastic materials exhibit both viscous and elastic behaviors. Thorough this study, the effect of different linear viscoelastic models including Maxwell, Kelvin and Kelvin-Voigt bodies on the behavior of tunnel is studied and the interaction of rock mass with elastic lining is analyzed. The surrounding rock mass is assumed to be homogeneous, isotropic and continuous. Hydrostatic stress field is also considered. In this paper, a series of formula for the foregoing models is driven to predict the displacement of lined and unlined circular tunnel and the pressure on the lining. The effect of lining stiffness and delay in installation of lining is analyzed. The results of new analytical relations show good correspondence with existing solutions.
Rock Mechanics
Sh. Bacha; Z. Mu Long; A. Javed; Sh. Al Faisal
Abstract
Rock burst is the most attractive and hot research area in geomechanics, mining, and civil engineering due to the increasing depth of mines and construction of deep underground structures. It has also been a severe problem in ground control measures in the last few decades. Many studies have been done ...
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Rock burst is the most attractive and hot research area in geomechanics, mining, and civil engineering due to the increasing depth of mines and construction of deep underground structures. It has also been a severe problem in ground control measures in the last few decades. Many studies have been done by different researchers in order to minimize the hazards of rock burst and to provide a safe mining/working environment. It is important to review the current advancement of rock burst prediction and its preventive measures. This paper reviews the experimental progress of rock burst warning, prediction, control measures, and potential damage measures. Different effective methods of rock burst prediction and control are also described.
H. Sarfaraz; M. H. Khosravi; T. Pipatpongsa
Abstract
One of the most important tasks in designing the undercut slopes is to determine the maximum stable undercut span to which various parameters such as the shear strength of the soil and the geometrical properties of the slope are related. Based on the arching phenomenon, by undercutting a slope, the weight ...
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One of the most important tasks in designing the undercut slopes is to determine the maximum stable undercut span to which various parameters such as the shear strength of the soil and the geometrical properties of the slope are related. Based on the arching phenomenon, by undercutting a slope, the weight load of the slope is transferred to the adjacent parts, leading to an increase in the stability of the slope. However, it may also lead to a ploughing failure on the adjacent parts. The application of counterweight on the adjacent parts of an undercut slope is a useful technique to prevent the ploughing failure. In other words, the slopes become stronger as an additional weight is put to the legs; hence, the excavated area can be increased to a wider span before the failure of the slope. This technique could be applied in order to stabilize the temporary slopes. In this work, determination of the maximum width of an undercut span is evaluated under both the static and pseudo-static conditions using numerical analyses. A series of tests are conducted with 120 numerical models using various values for the slope angles, the pseudo-static seismic loads, and the counterweight widths. The numerical results obtained are examined with a statistical method using the response surface methodology. An analysis of variance is carried out in order to investigate the influence of each input variable on the response parameter, and a new equation is derived for computation of the maximum stable undercut span in terms of the input parameters.
K. Dachri; Kh. Naji; K. Nouar; I. Benzakour; Kh. Ouzaouit; M. Badri; A. Boussetta; H. Faqir; Kh. El Amari; M. Hibti
Abstract
This work aims to define an efficient and innovative tool in order to make early metallurgical predictions of the Tizert deposit in western Anti-Atlas-Morocco. To do this, the mineralogical approach is used as a tool of gometallurgical prediction using a combination of the lithological field observations ...
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This work aims to define an efficient and innovative tool in order to make early metallurgical predictions of the Tizert deposit in western Anti-Atlas-Morocco. To do this, the mineralogical approach is used as a tool of gometallurgical prediction using a combination of the lithological field observations on representative drill cores, microscopic characterization performed on 54 thin sections, and automated quantitative mineralogy (AQM) conducted on five composite samples. The metallurgical prediction of the Tizert ore is based on the liberation data, notably on the copper content locked in the gangue and on unrecoverable copper buried as a solid matrix in the gangue minerals (refractory copper). In order to ensure the validity of the proposed method, the results of mineralogical prediction are compared with the flotation test work performance. As a result, the predicted copper recovery results from the mineralogical data are practically the same as those obtained through the flotation tests, showing a maximum difference of 2.02%, an R2 value of 0.96, and a Root Mean Square Error of 1.64%. These results indicate that using the AQM data, the copper recovery could be predicted accurately for the Tizert ore. Furthermore, an early prediction of the flotation performance is very useful in the geo-metallurgical model conception. In addition, such an approach ensures visibility throughout the life of the mine, and provides quick and cost-effective data for processing the performance. On an industrial scale, the applicability of this method can be expanded further by integrating the mineralogical approach into all steady-state processes in order to cover the possible mineralogical variety during the operations, and ensure an industrial process control.
Edith Amoakie Amoatey; Eric Tetteh Glover; David Okoh Kpeglo; Francis Otoo; Dennis Kpakpo Adotey
Abstract
Knowledge of accurate radio-isotopic signatures of NORM waste disposal site is essential prior to the disposal, to ascertain the baseline radioactivity levels. In this work, soil and water from a NORM waste site situated at Sofokrom in the Sekondi-Takoradi Metropolis of Ghana is characterized and determined. ...
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Knowledge of accurate radio-isotopic signatures of NORM waste disposal site is essential prior to the disposal, to ascertain the baseline radioactivity levels. In this work, soil and water from a NORM waste site situated at Sofokrom in the Sekondi-Takoradi Metropolis of Ghana is characterized and determined. The mean activity concentration of 226Ra, 232Th, and 40K measured in the soil samples are 40.31 ± 13.93 Bq/kg, 63.29 ± 23.18 Bq/kg, and 198.71 ± 49.10 Bq/kg, respectively, with the 226Ra and 232Th average values being higher than the average worldwide values by UNSCEAR. Also, the average activity levels of water samples from monitoring borehole measured for 226Ra and 232Th are within the WHO guidance levels of 1 Bq/L. The radiological parameters such as internal and external hazard indices (Hin and Hex), absorbed dose rate (D), and radium equivalent activity (Raeq) are estimated to assess the radiological risk to human, and compared with other similar works. Except for the annual gonadal dose, the remaining parameters are less than the recommended values. Multivariate statistical analysis is done to establish the interrelations among the activity concentrations of the radionuclides and their radiological parameters using Pearson correlation coefficient and principal component analysis. Strong positive correlations between 226Ra, 232Th, and the radiological parameters are observed. These findings would serve as the reference point for assessing future variations in the background radioactivity level owing to the geological or human activities from the disposal of the oil waste in the environment, as well as to aid in improving the technical foundations for the management of the NORM waste.
Z. Bayatzadeh Fard; F. Ghadimi; H. Fattahi
Abstract
Determining the distribution of heavy metals in groundwater is important in developing appropriate management strategies at mine sites. In this paper, the application of artificial intelligence (AI) methods to data analysis,namely artificial neural network (ANN), hybrid ANN with biogeography-based optimization ...
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Determining the distribution of heavy metals in groundwater is important in developing appropriate management strategies at mine sites. In this paper, the application of artificial intelligence (AI) methods to data analysis,namely artificial neural network (ANN), hybrid ANN with biogeography-based optimization (ANN-BBO), and multi-output adaptive neural fuzzy inference system (MANFIS) to estimate the distribution of heavy metals in groundwater of Lakan lead-zinc mine is demonstrated.For this purpose, the contamination groundwater resources were determined using the existing groundwater quality monitoring data, and several models were trained and tested using the collected data to determine the optimum model that used three inputs and four outputs. A comparison between the predicted and measured data indicated that the MANFIS model had the mostpotential to estimate the distribution of heavy metals in groundwater with a high degree of accuracy and robustness.
Mineral Processing
V. Radmehr; Seyed Z. Shafaei; M. Noaparast; H. Abdollahi
Abstract
This paper presents a new approach for flotation circuit design. Initially, it was proven numerically and analytically that in order to achieve the highest recovery in different circuit configurations, the best equipment must be placed at the beginning stage of the flotation circuits. The size of the ...
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This paper presents a new approach for flotation circuit design. Initially, it was proven numerically and analytically that in order to achieve the highest recovery in different circuit configurations, the best equipment must be placed at the beginning stage of the flotation circuits. The size of the entering particles and the types of streams including pulp and froth were considered as the basis for specialization of the flotation processes. In the new approach, the flotation process plays as the two functions of primary and secondary concentrations. The proposed approach was applied to a lead flotation circuit of a lead-zinc flotation plant. The results obtained showed that in most traditional-oriented circuits, a large part of the streams containing valuable metals were returned to the rougher stage, which, in turn, reduced the efficiency and caused perturbation. In the new approach, providing more control over unit operations in the circuit could provide a higher performance. In addition, in cases where zinc minerals are liberated from their gangue in coarse size, the new approach, by generating coarse-grained tailing, can prevent excessive grinding of zinc minerals in the feed into the zinc flotation circuit.
Exploitation
Assefa Hailesilasie Wolearegay; Yowhas Birhanu Amare; Asmelash Abay Hagos; Kassa Amare Mesfin; Hagos Abraha; Bereket Gebresilassie; Nageswara Rao Cheepurupalli; Yewuhalashet Fissha
Abstract
The Dichinama area in northern Ethiopia is a potential source of dimension stone, but the quality of the marble has been a major challenge for mining operations. This research aims to evaluate the quality of dimension stone by conducting a comprehensive study involving geological mapping, geotechnical ...
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The Dichinama area in northern Ethiopia is a potential source of dimension stone, but the quality of the marble has been a major challenge for mining operations. This research aims to evaluate the quality of dimension stone by conducting a comprehensive study involving geological mapping, geotechnical testing, and geochemical analysis. The study collected nine rock samples from three active mining sites in the Dichinama area, analyzing properties such as density, water absorption, compressive strength, flexural strength, and abrasion resistance. Additionally, ten samples were collected for geochemical analysis, focusing on parameters like calcite, CaO values, LOI, SiO2 content, and other oxide concentrations. The geotechnical tests revealed that the properties of the marble in the Dichinama area were mainly calcite, with compressive strength values ranging from 29.6 to 74.5 MPa, flexural strength from 7 to 52.5 MPa, abrasion resistance from 8.3 to 17.2, density from 2257 to 2562 kg/m3, and water absorption from 0.12 to 0.93. However, most of these parameters fell below the minimum ASTM standards for marble dimension stone. The results suggest that these inferior characteristics negatively affect the recovery and quality of the dimension stone.
Exploitation
H. Aryanmehr; M. Hosseinjanizadeh; M. Honarmand; F. Naser
Abstract
In this work, we focus on investigating the Quickbird and Landsat-8 datasets for mapping hydrothermal and gossans alterations in reconnaissance porphyry copper mineralization in the Babbiduyeh area. This area is situated in the Central Iranian Volcano-sedimentary Complex, where large copper deposits ...
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In this work, we focus on investigating the Quickbird and Landsat-8 datasets for mapping hydrothermal and gossans alterations in reconnaissance porphyry copper mineralization in the Babbiduyeh area. This area is situated in the Central Iranian Volcano-sedimentary Complex, where large copper deposits like Sarcheshmeh as well as numerous occurrences of copper exist. The alteration zones are discriminated by implementation of band ratio and principal component analysis on the Quickbird and Landsat-8 datasets. The image processing results are evaluated by field surveys, X-ray diffraction (XRD), microscopic thin section, and spectroscopic studies of field samples as well as the 1:100000 Sarduiyeh and 1:5000 Babbiduyeh geological maps. In addition, the spectral characterizations of the samples are analyzed by visual inspection, and the PIMAView, SAMS, and ViewSpecpro software programs. The combined spectroscopic measurements, XRD analyses, and petrographic studies revealed mineral assemblages typical of the phyllic, phyllic-supergen, propylitic, argillic, and gossan alterations. The results obtained from image processing and analysis of field samples illustrated examples of effects of iron oxides and hydroxides on the surface of phyllic and argillic alterations. Hence, it can be concluded that the areas discriminated in Quickbird as gossans correspond to the phyllic and argillic alteration areas.
Exploration
Ajay Kumar
Abstract
Land use (LU) classification based on remote sensing images is a challenging task that can be effectively addressed using a learning framework. However, accurately classifying pixels according to their land use poses a significant difficulty. Despite advancements in feature extraction techniques, the ...
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Land use (LU) classification based on remote sensing images is a challenging task that can be effectively addressed using a learning framework. However, accurately classifying pixels according to their land use poses a significant difficulty. Despite advancements in feature extraction techniques, the effectiveness of learning algorithms can vary considerably. In this study conducted in Talcher, Odisha, India, the researchers proposed the use of Artificial Neural Networks (ANNs) to classify land use based on a dataset collected by the Sentinel-2 satellite. The study focused on the Talcher region, which was divided into five distinct land use classes: coal area, built-up area, barren area, vegetation area, and waterbody area. By applying ANNs to the mining region of Talcher, the researchers aimed to improve the accuracy of land use classification. The results obtained from the study demonstrated an overall accuracy of 79.4%. This research work highlights the importance of utilizing remote sensing images and a learning framework to address the challenges associated with pixel-based land use classification. By employing ANNs and leveraging the dataset from the Sentinel-2 satellite, the study offers valuable insights into effectively classifying different land use categories in the Talcher region of India. The findings contribute to the advancement of techniques for accurate land use analysis, with potential applications in various fields such as urban planning, environmental monitoring, and resource management.
Exploration
Satyajeet Parida; Abhishek Kumar Tripathi; Tarek Salem Abdennaji; Yewuhalashet Fissha
Abstract
Coal quality is predominantly determined by its Gross Calorific Value (GCV), which directly influences its economic valuation. Traditional empirical formulas for GCV estimation, though effective, become inefficient and laborious when handling large datasets. To address this, machine learning (ML) techniques ...
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Coal quality is predominantly determined by its Gross Calorific Value (GCV), which directly influences its economic valuation. Traditional empirical formulas for GCV estimation, though effective, become inefficient and laborious when handling large datasets. To address this, machine learning (ML) techniques offer a robust alternative for accurate and rapid predictions. This study employs seven coal quality parameters. Total Moisture (TM), Ash (ASH), Volatile Matter (VM), Hydrogen (H), Carbon (C), Nitrogen (N), and Sulphur (S), as independent variables to develop predictive models for GCV. Four conventional regression techniques, namely Support Vector Regression (SVR), K-Nearest Neighbors (KNN), Random Forest (RF), and Decision Tree (DT), along with two robust regression models Random Sample Consensus (RANSAC) and Huber Regressor (HR) are explored. The dataset comprises coal samples from five Asia-Pacific countries: China, Indonesia, Korea, the Philippines, and Thailand. Comparative performance analysis reveals that the robust regression models significantly outperform the conventional ML techniques. The RANSAC and Huber Regressor models achieve superior prediction accuracy with R² values of 0.9941 and 0.9952, respectively. These findings highlight the potential of robust regression approaches for reliable GCV estimation, facilitating efficient coal quality assessment in large-scale applications.
A Atrafi; H Hodjatoleslami; Mohammad Noaparast; Z Shafaei; A Ghorbani
Abstract
This study aimed to explore concentration of a low grade sulfide-oxide lead-zinc sample containing 2.3% Pb, 1.91% Zn taken from Changarzeh mine, South Natanz, Iran. The effects of different parameters such as type and dosage of collector, milling retention time, dosage of sodium sulfur and its preparation ...
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This study aimed to explore concentration of a low grade sulfide-oxide lead-zinc sample containing 2.3% Pb, 1.91% Zn taken from Changarzeh mine, South Natanz, Iran. The effects of different parameters such as type and dosage of collector, milling retention time, dosage of sodium sulfur and its preparation time, application of sodium silicate, pH and solid content were investigated in relation to flotation efficiencies. Optimum experiment was carried out in cumulative flotation with 200g/t KAX as collector, 2000g/t Na2S, 500g/t sodium silicate, 30g/t MIBC and at pH=10. This test yielded 94% of lead recovery under optimum condition performance, and a concentrate with 70%Pb was produced through cleaning stages. Eighteen minutes was found to be the optimum time for lead flotation in laboratory scale. Application of gravity method for the production of a middle product was also considered. For shaking table the effect of table slope and water flowrate and for jig the effect of water flowrate and frequency were studied. Gravity separation by shaking table resulted in a concentrate with 46%Pb and 80% recovery, so shaking table could be proposed for production of pre-concentrate.
Omid Frough; Seyed Rahman Torabi; Majid Tajik
Abstract
Successful application of a TBM in a project requires investigating both the ground conditions and the machine and backup system design features. Prediction of the machine performance is very important as it has a big effect on the duration of the project and the costs. In this respect, both penetration ...
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Successful application of a TBM in a project requires investigating both the ground conditions and the machine and backup system design features. Prediction of the machine performance is very important as it has a big effect on the duration of the project and the costs. In this respect, both penetration rate and advance rate must be estimated. Utilization factor, which depends on the type of operation, management, maintenance, geological conditions, mucking delays and other downtimes, correlates the advance rate and penetration rate. Adverse rock mass conditions such as mixed face condition, water problem and instability of rock have a great role in TBM downtimes and reduce the machine utilization considerably. Based on detailed engineering geological reports and maps and daily site reports taken from Karaj-Tehran Water Conveyance Tunnel ( Lots 1 and 2), this paper evaluates, main rock mass properties utilized for the estimation of TBM performance and discusses their effect on the machine utilization. . More specifically it uses the developed database also contains daily boring time, different rock mass related downtimes, daily advance and length of bored tunnel in each engineering geological units. It is concluded that the percentage of the rock mass related downtimes can be estimated via RMR within reliable coefficient of determination.
Amir Mollajan; Hossein Memarian; Behzad Tokhmechi
Abstract
Detection of Oil-Water Contacts (OWCs) is one of the primary tasks before evaluation of reservoir’s hydrocarbon in place, determining net pay zones and suitable depths for perforation operation. This paper introduces Bayesian decision making tool as an effective technique in OWC detecting using ...
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Detection of Oil-Water Contacts (OWCs) is one of the primary tasks before evaluation of reservoir’s hydrocarbon in place, determining net pay zones and suitable depths for perforation operation. This paper introduces Bayesian decision making tool as an effective technique in OWC detecting using wire line logs. To compare strengths of the suggested method in detecting OWC with conventional one, the same database was used. Proposed method was applied to wire line logs in three wells of a carbonate reservoir in an oil field of the southwestern Iran and its results have been evaluated by well testing results. Results indicate that the usage of Bayesian method in detecting OWC is more accurate than conventional method and may improve the results about 5% on average. In addition, using this method, any variation of water saturation (Sw) log and reservoir fluid types may be detectable.
H. Rezaee; O. Asghari; J.K. Yamamoto
Abstract
A simple but novel and applicable approach is proposed to solve the problem of smoothing effect of ordinary kriging estimate which is widely used in mining and earth sciences. It is based on transformation equation in which Z scores are derived from ordinary kriging estimates and then rescaled by the ...
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A simple but novel and applicable approach is proposed to solve the problem of smoothing effect of ordinary kriging estimate which is widely used in mining and earth sciences. It is based on transformation equation in which Z scores are derived from ordinary kriging estimates and then rescaled by the standard deviation of sample data and the sample mean is added to the result. It bears the great potential to reproduce the histogram and semivariogram of the primary data. Actually, raw data are transformed into normal scores in order to avoid asymmetry of ordinary kriging estimates. Thus ordinary kriging estimates are rescaled using the transformation equation and after that back-transformed into the original scale of measurement. For testing the proposed procedure stratified random samples have been drawn from an exhaustive data set. Corrected ordinary kriging estimates follow the semivariogram model and back-transformed values reproduce the sample histogram, while keeping local accuracy.
R. Rahmannejad; A. Kargar; V. Maazallahi; E. Ghotbi-Ravandi
Abstract
The ground reaction curve (GRC) is a vital component of the convergence-confinement method, which possesses many applications in the underground space designs. It defines a relation between the tunnel wall deformations and the ground pressure acting on the tunnel walls. Generally, GRC includes descending ...
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The ground reaction curve (GRC) is a vital component of the convergence-confinement method, which possesses many applications in the underground space designs. It defines a relation between the tunnel wall deformations and the ground pressure acting on the tunnel walls. Generally, GRC includes descending and ascending branches. According to many researchers, the descending branch trend for the ground pressure stops after the critical deformation, and thus the ground pressure on the support system increases due to the formation of a loosening zone and an ascending branch, and finally, the creation of an ultimate pressure on the support system. In this work, two relations are proposed to determine the ultimate ground pressure acting on a circular tunnel in a continuous medium. It is assumed that the rock mass obeys the elastic perfectly plastic model with a cohesionless behavior in the broken zone. This is accomplished by incorporating the Duncan-Fama solution and the two models of Yanssen-Kötter and Caquot rigid plastic. The ground pressure obtained by the Caquot model shows a better correlation with the Goel-Jethwa equation compared with the Yanssen-Kötter solution.
H. Bejari; A. A. Daya; A. Roudini
Abstract
Based on existence of the chromite deposits in the Sistan and Baluchestan province in Iran, and also various applications of chromite in different industries, it is expected that the establishment of chromite processing plant is required in the erelong. The geographical location of a processing plant ...
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Based on existence of the chromite deposits in the Sistan and Baluchestan province in Iran, and also various applications of chromite in different industries, it is expected that the establishment of chromite processing plant is required in the erelong. The geographical location of a processing plant can have a strong influence on the success of an industrial venture. The processing plant site selection is a multi-criteria decision problem. The conventional methods used for a plant location selection are inadequate for dealing with the imprecise or vague nature of a linguistic assessment. To overcome this difficulty, the fuzzy multi-criteria decision-making methods are proposed. This paper presents an application of the analytic hierarchy process (AHP) method based on the fuzzy sets (Fuzzy AHP) used to select an appropriate site for a chromite processing plant in the Sistan and Baluchestan province. For this purpose, based on the concentration of chromite deposits in different regions of the province, four feasible alternatives including the Zahedan, Khash, Iranshahr, and Nikshahr cities are selected for a chromite processing plant. The quantitative and qualitative criteria such as availability of raw materials, availability of labors, education, climatic conditions, environmental impacts, infra-structural facilities and security, and local community considerations are used to compare the feasible alternatives. Finally, the alternatives are ranked, and a convenient location is recommended for the construction of the chromite processing plant. The results obtained show that the city of Zahedan is the best alternative.
