H. Dao; Th. L. Pham; N. Ph. Hung
Abstract
Blasting has become a crucial work in mining operation. However, it produces high-intensity seismic waves which cause some serious troubles such as injure people, fly-rock, cracking, breaking and reducing the lifetime of adjacent buildings. In Vietnam, there have been many conflicts between residents ...
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Blasting has become a crucial work in mining operation. However, it produces high-intensity seismic waves which cause some serious troubles such as injure people, fly-rock, cracking, breaking and reducing the lifetime of adjacent buildings. In Vietnam, there have been many conflicts between residents and government about the compensation policy for these damages. The solution is proposed, in which a similar explosion is made and an instantaneous concussion meter is used to record the magnitude of the generated shock wave. The results received from this operation will be used to determine the effects of mining blast. In fact, that is an incorrect method because just by changing the type of explosives, the order, the explosives, etc., the shock wave will be significantly reduced. Nothing is ensured that another explosion causing a shock wave amplitude will not occur in the future. To solve this problem, this paper presents an online seismic wave monitoring system operating 24/24h, to transmit the recorded signal to an independent server located around the boundary of the mine. On the basis of the mechanism of generating explosive waves and the recording mechanism of shock waves, the authors have built a program to store records according to the permissible influence of Vietnam Standard and Circular 32/2019/TT- Vietnam Board of Directors.
R. Morla; Sh. Karekal; A. Godbole
Abstract
Diesel-operated Load Haul Dumper (LHD) vehicles are commonly used in underground coal mines. Despite their value as utility vehicles, the main drawback of these vehicles is that they generate diesel particulate matter (DPM), a known carcinogenic agent. In this work, an attempt is made to model DPM flows ...
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Diesel-operated Load Haul Dumper (LHD) vehicles are commonly used in underground coal mines. Despite their value as utility vehicles, the main drawback of these vehicles is that they generate diesel particulate matter (DPM), a known carcinogenic agent. In this work, an attempt is made to model DPM flows generated by LHDs in an underground coal mine environment for different DPM flow and intake air flow directions. The field experiments are conducted and used to validate the computational fluid dynamics (CFD) models and used to map the DPM flow patterns. The results obtained show that if DPM and the intake air co-flow (flow in the same direction), DPM is confined predominantly in the middle of the roadway. To the contrary, if the DPM and intake air counter-flow (flow in the opposite directions), the DPM spread occurs throughout the entire cross-section of the roadway. In the latter case, the operator will be more susceptible to exposure to high concentrations of DPM. Overall, the DPM concentration decreases with an increase in the intake air velocities. For co-flow for intake air velocities of 2 m/s, 3 m/s, and 4 m/s, the DPM concentrations at 50 m downstream of the vehicles are 39 µg/m3, 23 µg/m3, and 19 µg/ m3, respectively. The DPM concentration is also influenced by the DPM temperature at the source. For the DPM temperatures of 30 oC, 40 oC, 50 oC, and 60 oC, the DPM concentrations at 50 m downstream of the source are 43 µg/m3, 34 µg/m3, 12 µg/m3, and 9 µg/m3, respectively.
Mineral Processing
H. Paryad; H. Khoshdast; V. Shojaei
Abstract
It is well-known that entrainment of particles into the froth is a key factor in the selectivity and performance of the flotation process, especially for fine particle recovery. Since flotation is a continuous process, in this work, the effects of operating parameters on the entrainment of ash materials ...
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It is well-known that entrainment of particles into the froth is a key factor in the selectivity and performance of the flotation process, especially for fine particle recovery. Since flotation is a continuous process, in this work, the effects of operating parameters on the entrainment of ash materials in a sample coal flotation is investigated from a time-sequence viewpoint. The effects of the pulp solid content, collector concentration, frother concentration, impeller speed, and particle size on the entrainment factor and water recovery at different flotation times are evaluated using a D-optimal response surface experimental design. The experimental work carried out shows that some parameters, especially particle size and pulp density, can yield completely different responses from those reported in the literature. The observed unusual behaviours can be attributed to the entrainment mechanisms and verified by the experimental results. It is also shown that the dominant entrainment mechanism can be varied by time. In addition, the statistical analyses of the experimental design show that the effects of some parameters change during time from the initial to the final stages of the flotation process. The results obtained indicate that the particle size and pulp density are the most important parameters influencing the entrainment rate and water recovery. The effects of the collector and frother concentrations are less on the entrainment and water recovery. In addition, the interaction between the solid percentage and particle size is the only significant mixed effect.
Kausar Sultan shah; Mohd Hazizan bin Mohd Hashim; Hafeez Ur Rehman; Kamar shah bin Ariffin
Abstract
The significance of rock failure can be found from the fact that microfracture genesis and coalescence in the rock mass results in macroscale fractures. Rock may fail due to an increase in the local stress, natural fractures, weathering inducing micro-crack genesis, coalescence, and propagation. Therefore, ...
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The significance of rock failure can be found from the fact that microfracture genesis and coalescence in the rock mass results in macroscale fractures. Rock may fail due to an increase in the local stress, natural fractures, weathering inducing micro-crack genesis, coalescence, and propagation. Therefore, a comprehensive understanding of the micro-scale failure mechanism of various weathering grade sandstones based on micro-level observation and microstructure-based simulation is essential. The microscale failure response of various weathering grade sandstones is studied under the wet and dry cycles. Each sample is tested for the micro-structure and micro-fracture characteristics using the image analysis. Furthermore, the micrographs obtained are also used to create the microstructure-based models, which are then simulated in the ANSYS software. The findings indicate that the moderately weathered sandstones indicate less weight reduction than the slightly weathered sandstone. The results obtained also demonstrate that the wet and dry cycles have little effect on the particle shape and size. However, variation in the particle shape and size implies that this is a result of the prevailing interaction of rock and water particle. The microscale simulation reveal that both UCS and BTS decrease from 37 MPa to 19 MPa and 9 MPa to 4 MPa as the density of the micro-structure increases. The results reveal that the primary fracture deviation from the loading axis increases with increasing density in the micro-structural micro-structures, although this effect reduces with further increasing density in the micro-structures.
M. Fayiah
Abstract
Sierra Leone is blessed with abundant natural resources but yet prone to environmental degradation due to the mining operations. Most often, the mining communities are faced with social tensions, as a result of the possible trade-off between the expected employment impact and the cost of mining operations ...
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Sierra Leone is blessed with abundant natural resources but yet prone to environmental degradation due to the mining operations. Most often, the mining communities are faced with social tensions, as a result of the possible trade-off between the expected employment impact and the cost of mining operations to the environment. Over the past decades, the contribution of the mining sector to the development of the country has been overshadowed by the fact that the mining operations have had adverse negative effects, mainly due to the country's weak environmental policies and the failure of the mine monitoring institutions, to supervise the operations of mining company operations. This article seeks to examine both the environmental and the social implication of mining operations on three mining edge communities in Sierra Leone. This paper also utilizes secondary data from the published articles, government’s reports, workshops and conference proceedings, policy documents of non-governmental organizations, newspapers, and the like to generate this writer's view on the topic under review. The thrust of the review will be on the following: Sierra Rutile Limited, Koidu Holdings Limited, and Shandong Iron Ore Mines. The above mining companies have been carefully selected due to the fact that they are located close to dwelling communities, and have been mining in Sierra Leone over a long period of time. The environmental performance index and the mining impact framework are used to clearly show the impact of mining operations on the environment in Sierra Leone. As a result of mining operations, deforestation is skyrocketing, public discomfort and air pollution has worsened, and social unrest has increased as a result of some unacceptable consequences including pollution of water source without recourse to short-term remedy. The literature reviewed by this writer reveals that the mining activities have two faces in Sierra Leone. One is that it serves as a resource curse. An example to this sad reality is the outbreak of civil war, social unrest among others. On the other hand, the mining sector is one of the principal backbones of the economy. It contributes to the livelihood of the country. This paper introduces three-way approaches of mining sector operation remedies that include but not limited to: 1) sound Environmental Impact Assessment (EIA) adoption before mining operations starts; 2) carrying out Strategic Environmental Assessment (SEA); 3) regular engagement with all stakeholders of mining-affected communities. This article recommends that restoration activities by mining companies go along with extraction and adequate compensation.
Devraj Dhakal; Salad Omar Abdi; Kanwarpreet Singh; Abhishek Sharma
Abstract
The highway contributes significantly to human existence by providing safe, dependable, and cost-effective services that are environmentally friendly and promote economic progress. Highway projects need extensive planning to prevent work revisions, save time and cost, and increase job efficiency. Without ...
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The highway contributes significantly to human existence by providing safe, dependable, and cost-effective services that are environmentally friendly and promote economic progress. Highway projects need extensive planning to prevent work revisions, save time and cost, and increase job efficiency. Without a doubt, Highway transportation system must be constantly updated to keep up with technology breakthroughs, environmental change, and rising client needs. Incorporating Remote Sensing (RS) and Geographic Information Systems (GISs) has the potential to go beyond the limitations of RS, which typically collects information about the earth and its peripheries from space, and does not alter, analyze, calculate, query or display geographic engineering maps. Over the last few decades, the fusion of RS and GIS has shown promise, and the researchers are employing it in different stages of the Highway Planning and Development Process (HPDP) such as optimal route analysis, geometric design, operation and management, traffic modeling, accident analysis, and environmental impact analysis (noise pollutions, air pollutions). This paper gives an overall review of the use of RS and GIS on HPDP at various stages of their lifecycles.
Environment
Ayodele Owolabi; Olumuyiwa Temidayo Ogunro; Gbenga Stephen Ayode
Abstract
Sustainable development is one that meets the needs of the current generation without compromising the ability of future generations to meet their own needs. The geospatial approach was used to evaluate the degree of sustainability of the mining operations in Okpella, Nigeria. 2011, 2016, and 2021. Normalized ...
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Sustainable development is one that meets the needs of the current generation without compromising the ability of future generations to meet their own needs. The geospatial approach was used to evaluate the degree of sustainability of the mining operations in Okpella, Nigeria. 2011, 2016, and 2021. Normalized Difference Vegetation Index (NDVI) revealed mean values of 0.36557, 0.32961, and 0.41674, respectively. This vegetation cover of shrubs, grassland, and relatively healthy vegetation remained after the mining activities in the research area. The surface water in the area is under stress due to the anthropogenic activities like mining, which is known to demand large amounts of water for mineral recovery and processing. Additionally, the Normalized Difference Moisture Index (NDMI) revealed that the mean values for the years 2011, 2016, and 2021 were, respectively, 0.01415, -0.32949, and -0.15331. The research area's NDMI showed little water stress. The Soil Moisture Index (SMI) for 2011, 2016, and 2021 indicated a moderate moisture content in the soil (0.73682, 0.58690, and 0.58897, respectively). The Land Surface Temperature (LST) data revealed that the LST levels (from 28.623 oC to 32.525 oC) had been rising. During the three years under study, aquatic bodies had the lowest LST values, whereas bare land and populated regions had the greatest LST values. According to the results of the NDVI, NDMI, and MNDWI investigations, this increase was caused by the intermediate vegetation levels and extremely low surface water. It is necessary to develop an environmental policy to mitigate the negative consequences of mining on land covers.
Exploration
Naman Chandel; Sushindra Kumar Gupta; Anand Kumar Ravi
Abstract
Groundwater is an essential resource for human survival, but its quality is often degraded by the human activities such as improper disposal of waste. Leachate generated from landfill sites can contaminate groundwater, causing severe environmental and health problems. Machine learning techniques can ...
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Groundwater is an essential resource for human survival, but its quality is often degraded by the human activities such as improper disposal of waste. Leachate generated from landfill sites can contaminate groundwater, causing severe environmental and health problems. Machine learning techniques can be used to predict groundwater quality and leachate characteristics to manage this issue efficiently. This study proposes a machine learning-based model for the prediction of groundwater quality and leachate characteristics using the effective water quality index (EWQI). The leachate dataset used in this study was obtained from a landfill site, and the groundwater quality dataset was collected from literature review. The mean values of TDS, Ca, Mg, NO3-, and PO4- exceeded the prescribed limit for drinking water purposes. The proposed model utilizes a machine learning architecture based on a convolutional neural network (CNN) to extract relevant features from the input data. The extracted features are then fed into a fully connected network to estimate the EWQI of the input samples. The model, trained and tested on leachate and groundwater quality datasets, achieves a high accuracy and computational efficiency, aiding in predicting groundwater quality and leachate characteristics for waste management.
Mineral Processing
Gh. A. Parsapour; S. DarvishTafvisi; E. Arghavani; M. J. Rajabi; A. Akbari; S. Banisi
Abstract
The new copper processing plant of the Sarcheshmeh copper complex consists of two parallel circuits. After a primary crushing, the ore is sent to a SAG mill, and the product is further ground in a ball mill. The overflow of the hydrocyclones is fed to a flotation circuit that contains 8 rougher tank ...
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The new copper processing plant of the Sarcheshmeh copper complex consists of two parallel circuits. After a primary crushing, the ore is sent to a SAG mill, and the product is further ground in a ball mill. The overflow of the hydrocyclones is fed to a flotation circuit that contains 8 rougher tank cells (RCS130), 3 cleaner cells (RCS50), 5 scavenger cells (RCS50), and a flotation column (as recleaner). The circuit was initially designed to process a feed containing 0.8% Cu but due to a change in the ore type, the feed grade decreased to 0.6% Cu. This resulted in a reduction in the final concentrate grade and the recovery from 28% and 85.5% to 24% and 84.4%, respectively. Based on the original design, the copper and silica recovery in the cleaner cells should be 69% and 55%, respectively, but these values increased to 85% and 75% due to a higher retention time. The rather high silica recovery was found to be the main source of the lower final concentrate grade. In order to reduce the retention time of particles in the cleaner cell from 13.7 to 6.9 min, the rougher concentrates of two parallel circuits were fed to only one cleaner-scavenger and regrind circuit. This modification increased the cleaner and final concentrate grade from 15.1% and 24.5% to 17% and 26%, respectively. The overall outcome of the circuit modification was evaluated to be a 10% reduction in the energy consumption without any loss in the overall copper recovery.
Sh. Sadat Etemadzadeh; G. Emtiazi; Z. Etemadifar
Abstract
Most studies on sulfur bioleaching from coal depend on an autotrophic microorganism with a low growth and a long leaching time. For this reason, heterotrophic heat and acidic pH-resistant Alicyclobacillus was used as the growing and resting cells for the sulfur and iron removal from coal. The results ...
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Most studies on sulfur bioleaching from coal depend on an autotrophic microorganism with a low growth and a long leaching time. For this reason, heterotrophic heat and acidic pH-resistant Alicyclobacillus was used as the growing and resting cells for the sulfur and iron removal from coal. The results obtained were analyzed by XRF. The data showed that 26.71% of sulfur was removed by Alicyclobacillus in a few days; however, 49.07% of sulfur was removed by Acidithiobacillus in 30 days. This was interesting since the leachings of zinc, strontium, titanium, and iron by Alicyclobacillus, obtained in a few days, were almost the same as the leachings by Acidithiobacillus in 30 days. The results obtained also showed that the Alicyclobacillus cells growing at 55 ˚C removed most of the coal impurities without any change in the carbon content of this fuel. To the best of our knowledge, coal leaching by Alicyclobacillus is reported for the first time.
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.
M. Kamran; Sh. Bacha; N. Mohammad
Abstract
This paper elucidates a new idea and concept for exploration of the gold ore deposits. The cyanidation method is traditionally used for gold extraction. However, this method is laborious, time-consuming, costly, and depends upon the availability of the processing units. In this work, an attempt ...
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This paper elucidates a new idea and concept for exploration of the gold ore deposits. The cyanidation method is traditionally used for gold extraction. However, this method is laborious, time-consuming, costly, and depends upon the availability of the processing units. In this work, an attempt is made in order to update the gold exploration method by the Monte Carlo-based simulation. An excellent approach always requires a high quality of the datasets for a good model. A total of 48 incomplete datasets are collected from the Shoghore district, Chitral area of Khyber, Pakhtunkhwa, Pakistan. The cyanidation leaching test is carried out in order to measure the percentage of the gold ore deposits. In this work, the mean, median, mode, and successive iteration substitute methods are employed in such a way that they can compute the datasets with missing attributes. The multiple regression analysis is used to find a correlation between the potential of hydrogen ion concentration (pH), solid content (in %), NaCN concentration (in ppm), leaching time (in Hr), particle size (in µm), and measured percentage of gold recovery (in %). Moreover, the normal Archimedes and exponential distributions are employed in order to forecast the uncertainty in the measured gold ore deposits. The performance of the model reveals that the Monte Carlo approach is more authentic for the probability estimation of gold ore recovery. The sensitivity analysis reveals that pH is the most influential parameter in the estimation of the gold ore deposits. This stochastic approach can be considered as a foundation to foretell the probabilistic exploration of the new gold deposits.
Morteza Karami; Shokrollah Zare; Jamal Rostami
Abstract
One of the important cost items in mechanized tunneling is the cost of repairing or replacing the disc cutters that have suffered from normal wear during the boring of the hard abrasive rocks. For inspecting the health of the disc cutters, the boring operation shall be stopped, and after checking, the ...
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One of the important cost items in mechanized tunneling is the cost of repairing or replacing the disc cutters that have suffered from normal wear during the boring of the hard abrasive rocks. For inspecting the health of the disc cutters, the boring operation shall be stopped, and after checking, the worn disc cutters may be replaced. In this work, the dynamic process of the TBM boring in the jointed rocks is simulated using a real-scale numerical analysis based on the rock fracturing factor using the discrete element method (DEM). The stress distributions induced within the disc cutters as well as the development of the plastic zones in the rock are investigated and compared with the actual results recorded in the Kerman water conveyance tunnel (KWCT). The numerical results indicate that the increase in the rock fracturing causes a decrease in the induced stresses and an increase in the size of the plastic zone. In other words, a higher penetration rate as well as more lifetime for disc cutters can be achieved in highly fractured rocks. Moreover, the average von Misses stress in the disc cutters in the highly fractured rocks is predicted about 16-23% less than stress induced in the slightly fractured rocks. Due to the TBM tunneling, the volume of the plastic zone as well as the actual penetration depth in the highly fracturing rocks are also about 40% and 42% higher than in the slightly fractured rocks under applying the same TBM parameters, respectively.
K.S. Shah; M. H. Mohd Hashim; K.S. Ariffin; N. F. Nordin
Abstract
The stability analysis of rock slopes is a complex task for the geotechnical engineers due to the complex nature of the rock mass in a tropical climate that often has discontinuities in several forms, and consequently, in several types of slope failures. In this work, a rock mass classification scheme ...
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The stability analysis of rock slopes is a complex task for the geotechnical engineers due to the complex nature of the rock mass in a tropical climate that often has discontinuities in several forms, and consequently, in several types of slope failures. In this work, a rock mass classification scheme is followed in a tropical environment using the Rock Mass Rating (RMR) and Geological Strength Index (GSI) combined with the kinematic investigation using the Rocscience Software Dips 6.0. The Lafarge quarry is divided into ten windows. In the RMR system, the five parameters uniaxial compressive strength (UCS), rock quality designation (RQD), discontinuity spacing, discontinuity condition, and groundwater conditions are investigated. The RMR values range from 51 to 70 (fair to good rock mass), and the GSI values range from 62 to 65 (good to fair rock mass). There is a good and positive correlation between RMR and GSI. The kinematic analysis reveals that window A is prone to critical toppling, window H to critical wedge-planar failure, and window G to critical wedge failure. From the results obtained, it can be concluded that the kinematic analysis combined with the rock mass classification system provides a better understanding to analyze the rock slope stability in a tropical climate compared with considering the rock mass classification system individually.
Yahia ElSayed Khamis; Shady Galal El-Rammah; Adel M Salem
Abstract
The rate of penetration plays a key role in maximizing drilling efficiency, so it is essential for the drilling process optimization and management. Traditional mathematical models have been used with some success to predict the rate of penetration in drilling. Due to the high complexity and non-linear ...
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The rate of penetration plays a key role in maximizing drilling efficiency, so it is essential for the drilling process optimization and management. Traditional mathematical models have been used with some success to predict the rate of penetration in drilling. Due to the high complexity and non-linear behavior of drilling parameters with the rate of penetration, these mathematical models cannot accurately and comprehensively predict the rate of penetration. Machine learning (ML) seems to be an attractive alternative to model this complicated physical process. This research paper introduces new data-driven models used to predict ROP using different parameters such as (depth, weight on bit (WOB), revolution per minute (RPM), Torque (T), standpipe pressure (SPP), flow in pump (pumping flow rate(Q), mud weight, hours on bit (HOB), revolutions on bit, bit diameter, total flow area (TFA), pore pressure, overburden pressure, and pit volume). Data-driven models are built using two different machine learning techniques, using 1771 raw real field data. The coding is built using the python programming language. The k-nearest neighbors (KNN) model predicting ROP for the training dataset show a correlation coefficient (R2) of 0.94. The multi-layer perceptron (MLP) model predicting ROP for the training dataset show a correlation coefficient (R2) of 0.98. We can conclude that MLP has a better accuracy, and removing outliers enhances model performance.
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.
Exploitation
Pouya Nobahar; Yashar Pourrahimian; Roohollah Shirani Faradonbeh; Fereydoun Mollaei Koshki
Abstract
Mineral reserve evaluation and ore type detection using data from exploratory boreholes are critical in mine design and extraction. However, preparing core samples and conducting chemical and physical tests is a time-consuming and costly procedure, slowing down the modeling process. This paper presents ...
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Mineral reserve evaluation and ore type detection using data from exploratory boreholes are critical in mine design and extraction. However, preparing core samples and conducting chemical and physical tests is a time-consuming and costly procedure, slowing down the modeling process. This paper presents a novel Deep Learning (DL)-based model to recognize the types of kaolinite samples. For this purpose, a dataset containing the images of drilled cores and their types determined from conventional chemical and physical analyses was used. Eight Convolutional Neural Network (CNN) topologies based on individual features were developed, named A, B, C, D, E, F, G, and H. Six of the eight proposed CNN topologies described above had accuracy below 80%, whereas two of them, model A and H, had higher accuracy than other topologies. Due to their similarity in results, both of them analyzed deeply. Model A was more efficient, with 90% accuracy, than model B, with 84% accuracy. Furthermore, the class detection performance of model A was further evaluated using different indices, including precision, recall, and F1-score, which resulted in values of 92%, 92%, and 90%, respectively, which are acceptable accuracies to identify the type of samples when using this approach on six different types of kaolinite.
A.O. Owolabi
Abstract
The vulnerability of water bodies to contamination within the neighbourhood of open mine cast environ cannot be overemphasized. Evidence of radioactive trace elements associated with the target minerals in the Plateau State (Nigeria) showed the extent of this vulnerability. In order to address this challenge, ...
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The vulnerability of water bodies to contamination within the neighbourhood of open mine cast environ cannot be overemphasized. Evidence of radioactive trace elements associated with the target minerals in the Plateau State (Nigeria) showed the extent of this vulnerability. In order to address this challenge, the radioactivity levels of water samples from mine ponds, streams, wells, and boreholes around mine sites in the Plateau State were assessed. The water samples were analysed for gross alpha and beta radiation activities using MPC 2000 radiation counter in accordance with the provisions of International Atomic Energy Agency (IAEA) at the Centre for Energy Research and Training (CERT) Zaria. The mean alpha radiation activity dose for the water samples collected from mine ponds, streams, wells, and boreholes was 0.63 + 0.1 Bq/l, 0.13 + 0.1 Bq/l, 0.34 + 0.1 Bq/l, and 0.51 + 0.2 Bq/l, respectively. The mean beta radiation activity dose for the water samples collected from mine ponds, streams, wells and boreholes was 4.1 + 1.8 Bq/l, 1.0 + 0.7Bq/l, 2.4 + 1.9 Bq/l, and 2.7 + 1.3 Bq/l, respectively. The water bodies were unwholesome for human consumption. The present use of water from the mine ponds for irrigation should be discontinued. The specific activities of alpha and beta radiations in the water samples decreased as distance from the mine increased. It is, therefore, clear that the mine sites were the sources of the high radiation values recorded in the water sources.
Exploration
Kaustubh Sinha; Priyangi Sharma; Anurag Sharma; Kanwarpreet Singh; Murtaza Hassan
Abstract
In this expansive study, a thorough analysis of land subsidence in the Joshimath area has been conducted, exercising remote sensing (RS) and Geographic Information System (Civilians) tools. The exploration encompasses colourful pivotal parameters, including Annual Rainfall, Geology, Geomorphology, and ...
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In this expansive study, a thorough analysis of land subsidence in the Joshimath area has been conducted, exercising remote sensing (RS) and Geographic Information System (Civilians) tools. The exploration encompasses colourful pivotal parameters, including Annual Rainfall, Geology, Geomorphology, and Lithology, rounded by the integration of different indicators. Joshimath, a fascinating city nestled within the rugged geography of the Indian state of Uttarakhand, stands out for its unique geographical features and its vulnerability to environmental vulnerabilities. The disquisition is carried out with the backing of ArcMap software, a technical Civilians tool, while exercising data sourced from the recognized Indian Space Research Organisation (ISRO) and the National Remote seeing Centre (NRSC). This comprehensive approach aims to give inestimable perceptivity into the dynamic processes associated with land subsidence in the region, offering critical data for disaster mitigation strategies and sustainable land operation in the area. It's noteworthy that the region endured a significant case of land subsidence in late December 2022, emphasizing the punctuality and applicability of this study. This event not only emphasizes the urgency of comprehending land subsidence in Joshimath but also underscores the necessity for ongoing monitoring and mitigation sweats. The integration of these different data sources and logical ways promises to enhance the understanding of land subsidence dynamics and inform decision- makers in the pursuit of flexible and sustainable land use practices in Joshimath and other also vulnerable regions.
Environment
G.U Sikakwe
Abstract
In this work, the concentrations of the potentially toxic elements in stream sediments in SE Nigeria were assessed for pollution monitoring in mining, quarrying, and farming areas. The levels of iron, molybdenum, vanadium, copper, lead, zinc, nickel, cobalt, manganese, chromium, barium, and beryllium ...
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In this work, the concentrations of the potentially toxic elements in stream sediments in SE Nigeria were assessed for pollution monitoring in mining, quarrying, and farming areas. The levels of iron, molybdenum, vanadium, copper, lead, zinc, nickel, cobalt, manganese, chromium, barium, and beryllium were determined. The concentrations of the elements were in the order of Fe > Ba > Mn > Cr > Zn > Pb > Cu > Co > Ni > As > Mo. There were significant positive correlations at P < 0.01 between Mo and Cu (r = 0.734), Mo and Pb (r = 0.811), and Cu and Pb (r = 0.836). The others were between Cu and V (r = 0.748), Pb and V (r = 0.793), Fe and V (r = 0.905), Fe and Be (r = 0.703), V and Be (r = 0.830), Cu and Pb (r = 0.778), and Fe and V (r = 0.905). The geoaccumulation index values were classified as polluted (0-1) to moderately polluted (1-2). The enrichment factors fell into moderate, significant, and very high enrichment. Pb, Co, and Ba attained significant enrichment factors. The potential ecological risk showed a strong risk level "C" in only three locations. Arsenic was a strong factor carrying risk. The potential ecological risk (EiR) trend was EiR (AS) > EiR (Pb)> EiR (Cu) > EiR (Co) > EiR (Cr) > EiR (V) > EiR (Ni) > EiR (Zn). Ba, Pb, and As should be monitored further to determine their source and recommend possible remedial measures. The result of this work could be used to improve water management efficiency and serve as a benchmark of vulnerability assessment of the studied area. This could also be useful for future impact assessment and adequate planning of mining and farming areas. In addition, the result obtained could assist the scientists to make appropriate environmental management strategies to reduce the influence of metal contamination triggered from the mining sites and farming areas both in Nigeria and globally.
S. Hussain; Z. Ur Rehman; N. Muhammad Khan; I. Ahmad; S. Raza; M. Tahir; A. Ullah; D. Afzal; A. Khan; M. Salman; S. Sherin
Abstract
The design of a stable slope in a rock mass environment is a quite complicated job due to the anisotropic behaviour of the rock mass. In this research work, the cut slopes at the Swat motorway in the weakest schist rock is numerically analyzed by the shear strength reduction (SSR) approach using the ...
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The design of a stable slope in a rock mass environment is a quite complicated job due to the anisotropic behaviour of the rock mass. In this research work, the cut slopes at the Swat motorway in the weakest schist rock is numerically analyzed by the shear strength reduction (SSR) approach using the Finite Element-based 2D RS2 software. The slope is divided into two cases according to the nature of the rock. Each case of the cut slope is analyzed by two stabilization methods: 1) changing the characteristics of the slope 2) support system installation based on the Mohr-Coulomb (MCC) and Generalized Hoek and Brown (GHB) failure criteria in order to propose the most appropriate method for slope stabilization. The results obtained reveal that the Critical Strength Reduction Factor (CSRF) before applying the stabilization methods is 1.34 (MCC) and 1.04 (GHB) for Case-I and 1.21 (MCC) and 0.53 (GHB) for Case-II. CSRF for Case-I after changing the characteristics of the slope is observed to be 2.43 (MCC) and 2.33 (GHB), while for Case-II is 1.82 (MCC) and 1.26 (GHB), respectively. CSRF for Case-I after the support installation criteria is 1.59 (MCC) and 1.07 (GHB), while for Case-II is 1.65 (MCC) and 0.5 (GHB), respectively. Based on the comparative analysis, it is revealed that changing the characteristics of the slope method shows prominent results in both cases; therefore, this method can be effectively used in order to stabilize the slope in the weakest rock mass environment.
Akhilesh Kumar; Ravi Kumar Sharma; Vijay Kumar Bansal
Abstract
The GIS-multi-criteria decision analysis (MCDA) techniques are increasingly used in landslide susceptibility mapping for predicting the future hazards, land use planning, and hazard preparedness. Identification of landslide susceptible regions helps in making a strategic plan for future developmental ...
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The GIS-multi-criteria decision analysis (MCDA) techniques are increasingly used in landslide susceptibility mapping for predicting the future hazards, land use planning, and hazard preparedness. Identification of landslide susceptible regions helps in making a strategic plan for future developmental activities in the landslide-prone areas. It enables the integration of different data layers with varying levels of uncertainty. In this work, GIS-MCDA is applied to landslide hazard zonation for the Kullu district in Himachal Pradesh, India. The current work aims to evaluate the performance of the analytical hierarchy process (AHP) for the development of a landslide hazard map. The geographical information system is used for the preparation of the database, analysis, modelling, and results. The ArcGIS 10.0 software is used to integrate the input layers by assigning appropriate weights. Six landslide causal factors are used, whereby the parameters are extracted from an associated spatial database. These factors are evaluated, and then the respective factor weight and class weight are assigned to each one of the associated factors. The developed landslide hazard map is categorized into three risk zones. The current work may be of great assistance to regional planners and decision-makers in deciding on the most suitable risk mitigation measures at the local level to prevent the potential losses and damages from landslides in the region.
Seyed A.R. Kaboli; M. Bahaaddini; Seyed M. Kaboli
Abstract
Traditionally, the earthmoving operations have been developed based on the minimum cost per production criterion. Nowadays, due to the negative impacts of the emissions on the environment, there is an increasing public awareness to reduce the emissions from the earthmoving operations. Different management ...
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Traditionally, the earthmoving operations have been developed based on the minimum cost per production criterion. Nowadays, due to the negative impacts of the emissions on the environment, there is an increasing public awareness to reduce the emissions from the earthmoving operations. Different management strategies can be employed to reduce emissions, amongst other things, which can also result in a reduction in the operational costs. This paper aims to examine the cost and emissions related to the earthmoving equipment from an operational standpoint. The queue theory is used in order to demonstrate that the optimum cost per production fleet size and the optimum emissions per production coincide. The linear and non-linear server utilization functions are employed to present a general optimization proof independent from any specific case study. The findings of this research work provide a better understanding of the relationship between the emissions and cost and how the under-trucking and over-trucking conditions affect the productivity and environmental affairs in the earthmoving operations.
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.
Exploration
Kamran Mostafaei; Mohammad Nabi Kianpour; Mahyar Yousefi; Meisam Saleki
Abstract
Discrimination of geochemical anomalies from background is a challenge in that elemental dispersion patterns are affected by a variety of geological factors, which vary from one to another area. While statistical and fractal methods are commonly employed for anomaly detection, they struggle with selecting ...
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Discrimination of geochemical anomalies from background is a challenge in that elemental dispersion patterns are affected by a variety of geological factors, which vary from one to another area. While statistical and fractal methods are commonly employed for anomaly detection, they struggle with selecting optimal thresholds. This study proposes the Grey Wolf Optimizer (GWO) algorithm as a novel approach for identifying the optimal boundary between anomalies and background. Stream sediment geochemical data from a copper-mineralized area of the Sarduiyeh-Baft sheets in southeast Iran were utilized for analysis. The Geochemical Mineralization Probability Index (GMPI) was first calculated for Cu-Au, Mo-As, Pb-Zn, and porphyry distributions. Subsequently, fractal methods were used to identify anomalous populations within each GMPI. The GWO algorithm was then applied to these distributions to determine the optimal thresholds. Risk analysis, calculated as the ratio of covered copper occurrences to the covered area, revealed superior reliability for the GWO-derived limit compared to those obtained using fractal methods. For porphyry GMPI values, while the fractal reliability indices are 0.127, 0.44, and 0.5, the GWO limit achieved a value of 0.66. Risk analysis for Cu-Au distribution also caused more desired result for GWO limit rather that fractal ones. This demonstrates the enhanced performance and superior reliability of the GWO algorithm for optimizing anomaly detection thresholds in GMPI data.
