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.
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.
Environment
Aditi Nag; Smriti Mishra
Abstract
The convergence of Mining Heritage Tourism (MHT) and Artificial Intelligence (AI) presents a transformative paradigm, reshaping heritage preservation, visitor engagement, and sustainable growth. This paper investigates the dynamic synergy between these realms, probing how AI-driven technologies can augment ...
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The convergence of Mining Heritage Tourism (MHT) and Artificial Intelligence (AI) presents a transformative paradigm, reshaping heritage preservation, visitor engagement, and sustainable growth. This paper investigates the dynamic synergy between these realms, probing how AI-driven technologies can augment the authenticity, accessibility, and educational significance of mining heritage sites. Focusing on the profound impact of AI on MHT, this study centers its examination on the Barr Conglomerate located in the culturally rich Pali District, India. Employing a mixed-methods approach involving survey data analysis and neural network modelling, the research work explores AI applications that enhance visitor experiences, interpret historical narratives, optimize resource allocation, and mitigate the adverse effects of over-tourism. The study meticulously navigates a vast landscape of AI technologies, spanning machine learning, natural language processing, and augmented reality, show-casing their potential to enrich encounters with mining heritage. While AI promises to revolutionize heritage management, the paper emphasizes the critical importance of ethical considerations and cultural sensitivities. Balancing innovation with preservation, the study advocates for an inclusive approach that honors diverse cultural values and encourages community engagement. Through this exploration, the paper delves into the practical implementation of AI, unveiling best practices lessons learned and illuminating challenges and opportunities. Ultimately, this research work envisions a future where AI empowers mining heritage to transcend temporal boundaries, cultivating immersive experiences resonating with authenticity, global understanding, and sustainable stewardship.
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.
Exploration
Shoopala Uugulu; Nazlene Poulton; Akaha Tse; Martin Harris; Taiwo Bolaji
Abstract
The long mining history in Namibia has resulted in numerous abandoned mining sites scattered throughout the country. Past research around the Klein Aub abandoned Copper mine highlighted environmental concerns related to past mining. Considering that residents of Klein Aub depend solely on groundwater ...
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The long mining history in Namibia has resulted in numerous abandoned mining sites scattered throughout the country. Past research around the Klein Aub abandoned Copper mine highlighted environmental concerns related to past mining. Considering that residents of Klein Aub depend solely on groundwater for their domestic, irrigation and other uses, there is a need to thoroughly investigate groundwater quality in the area to ascertain the extent of the contamination. This study characterises groundwater quality using a comprehensive quality assessment approach. On-site parameters reveal that pH ranges between 6.82-7.8, electrical conductivity ranges between 678 - 2270 μS/cm, and dissolved oxygen ranges between 1.4 -5.77 mg/L. With the exception of two samples, the onsite parameters indicate that water is of excellent quality according to the Namibian guidelines. The stable isotopic composition ranges from -7.26 to -5.82‰ and -45.1 to -35.9‰ for δ18O and δ2H, respectively. The groundwater plots on and above the Global Meteoric Water Line, and the best-fit line is characterised by a slope of 4.9, implying the evaporation effect. Hydrochemical analyses indicate bicarbonate and chloride as dominant anions, while calcium and sodium are dominant cations, indicating groundwater dissolving halite and mixing with water from a recharge zone. The Heavy Metal Pollution Index suggested that the water samples are free from heavy metal pollution. The Heavy Metal Evaluation Index clustered around 3, implying that heavy metals moderately affect groundwater. The groundwater quality is suitable for irrigation purposes. The findings offer valuable insights into the area's hydrochemistry and highlight potential environmental risks; hence, groundwater monitoring is recommended.
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.
