Environment
Hamid Sarkheil; Shahram Alghasi; Ali Sadeghy Nejad
Abstract
Environmental degradation, particularly in marine ecosystems, has become a critical issue, due to industrial activities. Offshore areas are significantly impacted by the deep sea mining operations, leading to pollution and ecological imbalances. The existing environmental risk assessment models often ...
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Environmental degradation, particularly in marine ecosystems, has become a critical issue, due to industrial activities. Offshore areas are significantly impacted by the deep sea mining operations, leading to pollution and ecological imbalances. The existing environmental risk assessment models often fail to integrate the qualitative and quantitative data effectively, highlighting a significant research work gap. This work aims to address this gap by developing a comprehensive framework using the Bayesian Networks (BN), and the NETICA software to evaluate the risks associated with the installation of three-legged deep sea mining structures. The major goals are to systematically identify and prioritize the risks, and to develop effective mitigation strategies. The novelty of this work lies in its innovative use of the Bayesian modeling to combine the expert knowledge with the empirical data, providing a detailed categorization of risks into the low, medium, and high levels. The output parameters focus on the severity, likelihood, and detectability of risks. The results indicate that 40% of the habitat destruction risks are low, 46% fall within the ALARP region, and 14% are high, while the species destruction risks are 31% low, 50% ALARP, and 19% high. These findings guide the targeted mitigation measures to ensure effective protection of the offshore marine environment. Also the work concludes with a set of recommendations aimed at mitigating identified risks, and minimizing the environmental impacts. These include the implementation of advanced monitoring technologies, adoption of best management practices, and enforcement of stricter regulatory frameworks.
Exploitation
Hassanreza Ghasemitabar; Andisheh Alimoradi; Hamidreza Hemati Ahooi; Mahdi Fathi
Abstract
Drilling of exploratory boreholes is one of the most important and costly steps in mineral exploration, which can provide us with accurate and appropriate information to continue the mining process. There are limitations on drilling the target boreholes, such as high costs, topographical problems in ...
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Drilling of exploratory boreholes is one of the most important and costly steps in mineral exploration, which can provide us with accurate and appropriate information to continue the mining process. There are limitations on drilling the target boreholes, such as high costs, topographical problems in installation of drilling rigs, restrictions caused by previous mining operation etc. The advances in artificial intelligence can help to solve these problems. In this research, we used python as one of the most pervasive and the most powerful programming languages in the field of data analysis and artificial intelligence. In this method mean shift algorithms have been used to cluster data, random forest to estimate clusters, and gradient boosting to estimate iron grade. Finally, in the studied area of Choghart in Central Iran, more than 91% accuracy was achieved in detection of ore blocks. Also, the results of the neural network indicate the mean square error (MSE) and mean absolute error (MAE) in the training data, respectively equal to 0.001 and 0.029, in the test data is 0.002 and 0.03, and in the validation boreholes, we reached a maximum of 0.06 and 0.2.
Exploitation
J. Balaraju; M. Govinda Raj; C.H.S.N. Murthy
Abstract
Reliability estimation plays a significant role in the performance assessment of mining equipment, and aids in designing efficient and effective preventive maintenance strategies. Continuous and random/irregular occurrence of failures in a system could be the main cause for performance drop of machinery. ...
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Reliability estimation plays a significant role in the performance assessment of mining equipment, and aids in designing efficient and effective preventive maintenance strategies. Continuous and random/irregular occurrence of failures in a system could be the main cause for performance drop of machinery. The accomplishment of a projected level of production is possible only by an efficient operation of the equipment. In order to improve the equipment life, a critical analysis of failure/breakdown occurrences is required to be carried out, and appropriate remedial measures need to be designed and implemented to enhance reliability. This paper presents a reliability analysis of Load-Haul-Dumper (LHD) in an underground coal mine. The goodness-of-fit distribution of each LHD was made through the Cramer-Von-Mises statistic test. The parameters involved were estimated using both the maximum likelihood analytical estimation process and the graphical process. Further, an attempt was made to reduce the total cost of operation by estimating the reliability-based preventive maintenance time intervals.
Mineral Processing
K. Barani; M. Azghadi; M. R. Azadi; A. Karrech
Abstract
The influence of microwave treatment on the surface roughness, hydrophobicity, and chemical composition of galena was studied. The pure galena specimens and purified galena concentrate were used in this work. A conventional multi-modal oven (with a frequency of 2.45 GHz and a maximum power of 900 W) ...
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The influence of microwave treatment on the surface roughness, hydrophobicity, and chemical composition of galena was studied. The pure galena specimens and purified galena concentrate were used in this work. A conventional multi-modal oven (with a frequency of 2.45 GHz and a maximum power of 900 W) was used to conduct the experiments. The results obtained from the atomic-force microscopy analysis showed that the surface roughness of galena decreased after the microwave radiation. The results also showed that the surface hydrophobicity of galena increased with increase in the duration of the microwave radiation, which was in good agreement with the micro-flotation mass recovery results. The increased surface hydrophobicity may be attributed to the decreased surface roughness by microwave radiation or formation of sulfur on the surface. The results of the SEM/EDS analyses indicated that after microwave radiation, the amount of S increased, whereas Pb decreased on the surface of galena, indicating that the average atomic number of the galena surface changed due to microwave treatment.
H. Fattahi; M. Hasanipanah; N. Zandy Ilghani
Abstract
The mechanical characteristics of rocks and rock masses are considered as the determining factors in making plans in the mining and civil engineering projects. Two factors that determine how rocks responds in varying stress conditions are P-wave velocity (PWV) and its isotropic properties. Therefore, ...
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The mechanical characteristics of rocks and rock masses are considered as the determining factors in making plans in the mining and civil engineering projects. Two factors that determine how rocks responds in varying stress conditions are P-wave velocity (PWV) and its isotropic properties. Therefore, achieving a high-accurate method to estimate PWV is a very important task. This work investigates the use of different intelligent models such as multivariate adaptive regression splines (MARS), classification and regression tree (CART), group method of data handling (GMDH), and gene expression programming (GEP) for the prediction of PWV. The proposed models are then evaluated using several error statistics, i.e. squared correlation coefficient (R2) and root mean squared error (RMSE). The values of R2 obtained from the CART, MARS, GMDH, and GEP models are 0.983, 0.999, 0.995, and 0.998, respectively. Furthermore, the CART, MARS, GMDH, and GEP models predict PWV with the RMSE values of 0.037, 0.007, 0.023, and 0.020, respectively. According to the aforementioned amounts, the models presented in this work predict PWV with a good performance. Nevertheless, the results obtained reveal that the MARS model yields a better prediction in comparison to the GEP, GMDH, and CART models. Accordingly, MARS can be offered as an accurate model for predicting the aims in other rock mechanics and geotechnical fields.
H. Fattahi
Abstract
The tensile strength (σt) of a rock plays an important role in the reliable construction of several civil structures such as dam foundations and types of tunnels and excavations. Determination of σt in the laboratory can be expensive, difficult, and time-consuming for certain projects. Due ...
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The tensile strength (σt) of a rock plays an important role in the reliable construction of several civil structures such as dam foundations and types of tunnels and excavations. Determination of σt in the laboratory can be expensive, difficult, and time-consuming for certain projects. Due to the difficulties associated with the experimental procedure, it is usually preferred that the σt is evaluated in an indirect way. For these reasons, in this work, the adaptive network-based fuzzy inference system (ANFIS) is used to build a prediction model for the indirect prediction of σt of sandstone rock samples from their physical properties. Two ANFIS models are implemented, i.e. ANFIS-subtractive clustering method (SCM) and ANFIS-fuzzy c-means clustering method (FCM). The ANFIS models are applied to the data available in the open source literature. In these models, the porosity, specific gravity, dry unit weight, and saturated unit weight are utilized as the input parameters, while the measured σt is the output parameter. The performance of the proposed predictive models is examined according to two performance indices, i.e. mean square error (MSE) and coefficient of determination (R2). The results obtained from this work indicate that ANFIS-SCM is a reliable method to predict σt with a high degree of accuracy.
Mineral Processing
Aghil Haghdadi; Sima Mohammadnejad
Abstract
The presence of copper bearing minerals in cyanidation of gold ores may lead to several challenges in the CIP/CIL circuits. Many solutions have been proposed to address these problems, one being the use of glycine in the cyanidation process. Here, the experimental as well as molecular modelling studies ...
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The presence of copper bearing minerals in cyanidation of gold ores may lead to several challenges in the CIP/CIL circuits. Many solutions have been proposed to address these problems, one being the use of glycine in the cyanidation process. Here, the experimental as well as molecular modelling studies using Density Functional Theory (DFT) have been conducted to investigate the glycine role in cyanidation of copper bearing gold ores. The results show that in the presence of glycine in the solution containing copper-cyanide species and in very low or zero free cyanide content, the dissolution rate of gold is significantly improved (3.02 vs. 0.23 ppm), while no improvement is observed in copper free or cyanide enriched solutions. Molecular modeling has been performed to interpret the laboratory results as well as to identify the mechanisms. The modeling results demonstrate that in cyanide deficient solutions, cyanide complex of copper complexes (E = -319 kCal.mol-1) is replaced by glycine, and the free cyanide produced results in higher gold cyanidation as well as lower copper cyanide formation.
Mineral Processing
M. Salehfard; M. Noaparast; Seyed Z. Shafaei; H. Abdollahi
Abstract
A lead-zinc carbonate ore sample containing 2.5% Pb and 9.39% Zn was used in this research work. The sample was prepared from the Darreh-Zanjir mine located in the Yazd province (Iran). Influences of the influential factors on flotation of smithsonite and cerussite were investigated. Among the different ...
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A lead-zinc carbonate ore sample containing 2.5% Pb and 9.39% Zn was used in this research work. The sample was prepared from the Darreh-Zanjir mine located in the Yazd province (Iran). Influences of the influential factors on flotation of smithsonite and cerussite were investigated. Among the different parameters involved, dosages of the dispersant, depressants, sulfidizing agent, and collectors de-sliming prior to lead or zinc flotation were essential for the effective recovery and grade of the Zn and Pb flotation concentrates. In addition, the anionic, cationic, and mixed (cationic/anionic) collectors were employed for flotation of smithsonite. The results of reverse and cumulative flotation of both Zn and Pb were relatively low in comparison with the direct process without depressant. Flotation of smithsonite using mixed collectors (Armac C+KAX) showed promising results. Also dosages of chemicals in the cleaning stage for the Zn and Pb concentrates were optimized, and finally, after the cleaner stage for both lead and zinc, a cerussite concentrate with Pb grade and recovery of 49.82% and 60.06%, respectively, and smithsonite concentrate with Zn grade and recovery of 35.47% and 68.56%, respectively, were obtained under the optimal conditions. Furthermore, kinetics of Zn and Pb oxide mineral flotations in the rougher and cleaner stages were studied, which showed that some kinetics models, especially the classical first-order model, could predict the flotation behaviour of the Zn and Pb oxide minerals.
Exploitation
A. Mozafari; A. H. Bangian Tabrizi; M. Taji; A. Parhizkar
Abstract
In this paper, we present an integrated model to find the optimum size of blast block that uses (i) a multi-criteria decision-making method to specify the applicable size of the mineable block; (ii) a linear programming method for the selection of the blasted areas to be excavated and in deciding the ...
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In this paper, we present an integrated model to find the optimum size of blast block that uses (i) a multi-criteria decision-making method to specify the applicable size of the mineable block; (ii) a linear programming method for the selection of the blasted areas to be excavated and in deciding the quantity of ores and wastes to be mined from each one of the selected blocks. These two methods use improved estimates of the orebody characteristics utilizing the blast hole data in addition to the usual borehole statistics to improve the prediction accuracy of the block level ore body characteristics. This work aims to make a mathematical model to figure out the ideal width and length of the blast block in order to curtail drilling and blasting expenses in open-pit mines. As a consequence, the effective blast block size is heeded so as to decrease the expenses of drilling and blasting. Furthermore, a complete set of actual principles is presented to specify the applicable size of the mineable block by means of the multi-criteria decision-making method of fuzzy logic. The aforementioned model is practiced to forecast the block size necessary for the purpose of production planning. Next, a mixed integer programming model is developed to blast planning in order to select the optimal size of the blast block by considering the mineable block. The proposed model is applied in the Chadormalu iron ore mine and the rationality of the model is demonstrated by the outcomes of dissimilar circumstances.
Mineral Processing
Seyyed Mohsen Zamzami; Javad Vazifeh Mehrabani
Abstract
In this research, solid phase settling process from the liquid phase were optimized simultaneously on the different responses, using the response surface methodology (RSM). The effect of solid percentage, flocculant dosage, temperature, and pulp pH were evaluated on the responses of solid settling velocity, ...
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In this research, solid phase settling process from the liquid phase were optimized simultaneously on the different responses, using the response surface methodology (RSM). The effect of solid percentage, flocculant dosage, temperature, and pulp pH were evaluated on the responses of solid settling velocity, water turbidity, viscosity and density of settled pulp. The results showed that by increasing the flocculant dosage from 0.5 to 3.5 g/ton, settled pulp viscosity decreases from 49.05 cSt to 17.54 cSt. The higher values of pulp pH as well as low amount of solid percentage resulted in high water turbidity, which shows the lack of contact between flocs and suspended particles. The results indicated that the pulp solid percentage and the flocculants dosage are the most significant parameters on the responses. Optimum test conditions were obtained in industrial mode by using 5 g/t flocculant, solid percentage 23.96%, pH=7.5 temperature of the pulp 21.5°C in which condition, settling rate, pulp viscosity, pulp density and water turbidity were predicted to be 13.23 cm/min, 5.1 cSt, 1.61 g/cm3 and 15.7 NTU respectively. Repetition test in the model predicted optimum condition was carried out and verified the predicted optimized condition.
Mineral Processing
Reza Khodadadi Bordboland; Asghar Azizi; Mohammad Reza Khani
Abstract
The global growth of aluminum demand with the modernization of our society has led to the interest in developing alternative methods to produce aluminum from non-bauxite and low-grade resources such as shale bauxites. For such reserves, the conventional Bayer process is challenging and is not efficient ...
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The global growth of aluminum demand with the modernization of our society has led to the interest in developing alternative methods to produce aluminum from non-bauxite and low-grade resources such as shale bauxites. For such reserves, the conventional Bayer process is challenging and is not efficient to extract aluminum, and the sintering process is known to be effective. Thus, this study aimed to scrutinize the technical feasibility of alumina extraction from an Iranian low-grade (shale) bauxite ore containing 36.22% Al2O3, 22.11% SiO2, 20.42% Fe2O3, 3.33% TiO2, and 3.13% CaO. In this regard, the sintering process with lime-soda followed by alkaline leaching was adopted to extract alumina, and response surface modeling was employed to assess the important parameters such as the sintering temperature, Na2O(caustic) concentration, CaO/SiO2 molar ratio, and Na2O/Al2O3 molar ratio. The findings indicated that the extraction rate improved by increasing the sintering temperature and CaO/SiO2 ratio and decreasing the Na2O(caustic) dose and Na2O/Al2O3 ratio. It was also found that the Na2O(caustic) concentration, sintering temperature, and interactive effect of Na2O(caustic) concentration with Na2O/Al2O3 ratio had the greatest influence on the extraction efficiency. The process optimization was conducted applying the desirability function approach, and more than 71% of Al2O3 was extracted at 1150 °C sintering temperature, 2.1 CaO/SiO2 molar ratio, 0.9 Na2O/Al2O3 molar ratio and 30 g/L Na2O(caustic) dose. Ultimately, it was concluded that a lime-soda sintering process at 1150 °C followed by one-step alkaline leaching with Na2O(caustic) at 90 °C could be metallurgically efficient for treating the low-grade (shale) bauxites.
M. M. Nazempour; A. Majdi
Abstract
Prediction of the length of grout penetration and assessment of the groutability around the boreholes in the jointed rocks have a crucial effect on the planning and execution of grouting. Grout distribution in jointed rocks is a function of the geo-mechanical properties of rock mass, grout properties, ...
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Prediction of the length of grout penetration and assessment of the groutability around the boreholes in the jointed rocks have a crucial effect on the planning and execution of grouting. Grout distribution in jointed rocks is a function of the geo-mechanical properties of rock mass, grout properties, and grout operational performance. This paper describes an analytical model based on the Newton’s second law, with the assumption of disk-shape model for the joints in order to calculate the maximum length of grout penetration in the horizontal and angled joints. It is shown that the proposed formulas can predict the length of grout penetration in rock masses with numerous joint sets as well. In order to validate the proposed model, it is compared with the existing analytical and empirical criteria, showing a very good accordance with their calculated results. Finally, the proposed analytical model is used to design the grout planning of a water conveying tunnel that is subjected to a heavy inflow. The design results in a successful filling of the vacant space behind the segmental lining and sealing the tunnel to stop the inrush water. These show that the model proposed in this paper can be successfully applied in practice.
E. Pouresmaeili; A. Ebrahimabadi; H. Hamidian
Abstract
Sustainability assessment has received numerous attentions in the mining industry. Mining sustainability includes the environmental, economic, and social dimensions, and a sustainable development is achieved when all these dimensions improve in a balanced manner. Therefore, to measure the sustainability ...
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Sustainability assessment has received numerous attentions in the mining industry. Mining sustainability includes the environmental, economic, and social dimensions, and a sustainable development is achieved when all these dimensions improve in a balanced manner. Therefore, to measure the sustainability score of a mine, we require an approach that evaluates all these three dimensions of mining sustainability. Some frameworks have been developed to compute the sustainability score of mining activities; however, some of them are very complicated and the others do not cover all the environmental, economic, and social aspects of sustainability. In order to fill this gap, this work was designed to introduce a practical approach to determine the score of mining sustainability. In order to develop this approach, initially, 14 negative and positive influential macro factors in the sustainability of open-pit mines were identified. Then the important levels of the factors were estimated based on the comments and scores of some experts. Two checklists were constructed for the negative and positive factors. The sustainability score was computed using these checklists and the importance levels of the factors. The score range was between -100 and +100. In order to implement the proposed approach, the Angouran lead and zinc mine was selected. The sustainability score of the Angouran mine was +47.91, which indicated that the this mine had a sustainable condition. This score could increase through modification of some factors.
Sirvan Moradi; Seyed Davoud Mohammadi; Abbas Aghajani Bazzazi; Ali Aali Anvari; Ava Osmanpour
Abstract
Feasibility studies of mining and industrial investment projects are usually associated with uncertain parameters; hence, these investigations rely on prediction. In these particular conditions, simulation and modelling techniques remain the most significant approaches to reduce the decision risk. Since ...
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Feasibility studies of mining and industrial investment projects are usually associated with uncertain parameters; hence, these investigations rely on prediction. In these particular conditions, simulation and modelling techniques remain the most significant approaches to reduce the decision risk. Since several uncertain parameters are incorporated in the modelling process, distribution functions are employed to explain the parameters. However, due to the usual constrain of limited data, these functions cannot significantly explain the variation of those uncertain parameters. Support vector machine, one of the efficient techniques of artificial intelligence, provides the appropriate results in the classification and regression tasks. The principal aims of this research work are to integrate the simulation and artificial intelligence methods to manage the risk prediction of an economic system under uncertain conditions. The financial process of the Halichal mine in the Mazandaran province, Iran, is considered a case study to prove the performance of the support vector machine technique. The results show that integrating the simulation and support vector machine techniques can provide more realistic results, especially when including uncertain parameters. The correlation between the net present value obtained from the simulation and the net present value is about 0.96, which shows the capability of artificial intelligence methods and the simulation process. The root mean square error of the support vector machine prediction is about 0.322, which indicates a low error rate in the net present value estimation. The values of these errors prove that this method has a high accuracy and performance for predicting a net present value in the Halichal granite mine.
Rock Mechanics
Erfan Amini; Masoud Mojarab; Hossein Memarian
Abstract
Landslides are defined as the downward movement of a portion of land materials under the direct influence of gravity. Landslides would get triggered by a wide spectrum of initiative factors such as earthquakes as a site effect of that event. In the vicinity of Tehran, significant historical earthquakes ...
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Landslides are defined as the downward movement of a portion of land materials under the direct influence of gravity. Landslides would get triggered by a wide spectrum of initiative factors such as earthquakes as a site effect of that event. In the vicinity of Tehran, significant historical earthquakes have occurred; therefore, tracing them could enhance the Tehran’s historical earthquake catalogue, due to the reason Tehran is a metropolitan and capital of Iran. However, paleoseismology could not determine the magnitude and seismic characteristics of historical earthquakes. Mobarak Abad landslide is a large and historical landslide located on Haraz road, a vital artery connecting Tehran to the Mazandaran Province, and there are significant faults like Mosha, North Alborz, and Khazar in its neighborhood. Hence, it is probable that this landslide occurred due to the generation of dynamic force resulting from an earthquake. Therefore, in this study, the geometrical characteristics of the landslide were measured by field surveying. Then with the empirical equations proposed by various researchers, we estimated the landslide volume and the magnitude of the corresponding earthquake, respectively. In the following, the epicenter and hypocenter of all the historical earthquakes within 200 kilometers of the landslide were identified. Then we utilized some conditions such as Keefer's graphs, error value in epicenter location, and peak ground acceleration to omit earthquakes and identify the corresponding earthquake event. The results demonstrate that two earthquakes of 1830 AD and 855 AD with a maximum acceleration of 0.16g are more probable than the 743 AD earthquake.
Environment
Amirhossein Karimi; Amin Falamaki; Farid Soltani; Mehdi Homaee; Nader Shariatmadari
Abstract
Mining activities have led to the accumulation of large quantities of mineral tailings containing potentially hazardous metals, contaminating the surrounding soil. This study investigated the effectiveness of electrokinetic remediation combined with washing solvents for the decontamination of zinc and ...
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Mining activities have led to the accumulation of large quantities of mineral tailings containing potentially hazardous metals, contaminating the surrounding soil. This study investigated the effectiveness of electrokinetic remediation combined with washing solvents for the decontamination of zinc and lead from mine tailings. Samples were collected from various locations within the Angouran mine in Zanjan, Iran, and analyzed for total metal concentration using the standard ICP method. Electrokinetic tests were conducted using different washing solutions—hydrochloric acid, nitric acid, acetic acid, and sulfuric acid—each at a concentration of 0.1 M and mixed with soil in a 1:2 solution-to-solid ratio. A voltage of 1.5 V/cm was applied throughout the experiments. To mitigate heavy metal precipitation near the cathode, the same chemical solutions were used in the cathode chamber. The results demonstrated that distilled water resulted in the lowest removal efficiency for zinc (16%) and lead (11.5%), while hydrochloric acid showed the highest removal efficiencies of 64% for zinc and 45% for lead. These findings indicated that electrokinetic remediation, particularly when using hydrochloric acid as a complexing agent, was an effective method for removing significant quantities of zinc and lead from contaminated soil.
Exploitation
Elham Lotfi; Javad Gholamnejad; Mehdi Najafi; Mohammad Sadegh Zamani
Abstract
In the context of open pit mining operations, long-term production scheduling faces significant challenges due to inherent uncertainties, particularly in commodity prices. Traditional mathematical models often adopt a single-point estimation strategy for commodity price, leading to suboptimal mine plans ...
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In the context of open pit mining operations, long-term production scheduling faces significant challenges due to inherent uncertainties, particularly in commodity prices. Traditional mathematical models often adopt a single-point estimation strategy for commodity price, leading to suboptimal mine plans and missed production targets. The simultaneous effect of commodity price uncertainty on the cut-off grade and long-term production scheduling is less considered. This paper introduces a novel model for optimizing open pit mine long-term production scheduling under commodity price uncertainty considering a dynamic cut-off grade strategy, based on a two-stage Stochastic Production Programming (SPP) framework. The presented model seeks to identify optimal mining block sequences, maximizing total discounted cash flow while penalizing deviations from production targets. To illustrate the model's efficiency, it was implemented in a copper mine. First, the Geometric Brownian Motion (GBM) model is used to quantify the future commodity price. Then, both deterministic and SPP models were solved using GAMS software. The results showed that the practical NPV obtained from the SPP model is approximately 3% higher than the DPP model, while all constraints are satisfied.
Rock Mechanics
Amin Maleki; Hamid Chakeri; Hadi Shakeri; Erfan Khoshzaher; Mohammad Darbor
Abstract
Today, due to technological advancements and increasing demand, various types of Tunnel Boring Machines (TBM) are extensively used for tunneling in both soil and rock. The mechanical excavation method has become attractive in tunnel excavation and underground spaces due to its high safety, rapid progress ...
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Today, due to technological advancements and increasing demand, various types of Tunnel Boring Machines (TBM) are extensively used for tunneling in both soil and rock. The mechanical excavation method has become attractive in tunnel excavation and underground spaces due to its high safety, rapid progress rate, low human labor requirement, and mechanization capability. The high capital costs of mechanical excavation make it essential to conduct laboratory tests, such as linear cutting tests on rocks, before selecting the machine type and adjusting the cutter head blade. The main objective of this study is to investigate the impact of rock mechanical properties on the cutting tool wear using a newly developed small-scale Linear Cutting Machine (LCM). To achieve this, laboratory linear cutting tests on rocks were conducted after constructing the small-scale linear cutting machine. To evaluate the rock cuttability and analyze the performance of disc cutters, 5 rock samples were used at three different penetration depths of 1, 1.5, and 2 mm. The results showed that the wear values of the cutting discs increased with penetration depth in all rock types, with the highest wear observed in basalt. Additionally, Brazilian tensile strength exhibited the highest correlation with cutting disc wear parameters. Furthermore, these studies indicated that determining the mineralogical and physical characteristics of rocks, such as texture, crystal size, and porosity, alongside their mechanical properties, is crucial for predicting rock wear.
Maysam Abedi; Gholam-Hossain Norouzi; Nader Fathianpour; Ali Gholami
Abstract
This paper describes the application of approximate methods to invert airborne magnetic data as well as helicopter-borne frequency domain electromagnetic data in order to retrieve a joint model of magnetic susceptibility and electrical resistivity. The study area located in Semnan province of Iran consists ...
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This paper describes the application of approximate methods to invert airborne magnetic data as well as helicopter-borne frequency domain electromagnetic data in order to retrieve a joint model of magnetic susceptibility and electrical resistivity. The study area located in Semnan province of Iran consists of an arc-shaped porphyry andesite covered by sedimentary units which may have potential of mineral occurrences, especially porphyry copper. Based on previous studies, which assume a homogenous half-space earth model, two approximate methods involving the Siemon and the Mundry approaches are used in this study to generate a resistivity-depth image of underground geologically plausible porphyry unit derived from airborne electromagnetic data. The 3D visualization of the 1D inverted resistivity models along all flight lines provides a resistive geological unit which corresponds to the desired porphyry andesite. To reduce uncertainty arising from single geophysical model, i.e., the resistivity model acquired from the frequency domain electromagnetic data, a fast implementable approach for 3D inversion of magnetic data called the Lanczos bidiagonalization method is also applied to the large scale airborne magnetic data in order to construct a 3D distribution model of magnetic susceptibility, by which the obtained model consequently confirms the extension of an arc-shaped porphyry andesite at depth. The susceptible-resistive porphyry andesite model provided by integrated geophysical data indicates a thicker structure than what is shown on the geological map while extends down at depth. As a result, considering simultaneous interpretation of airborne magnetic and frequency domain electromagnetic data certainly yield lower uncertainty in the modeling of andesite unit as a potential source of copper occurrences.
Exploitation
B. Sohrabian; R. Mikaeil; R. Hasanpour; Y. Ozcelik
Abstract
The quality properties of andesite (Unit Volume Weight, Uniaxial Compression Strength, Los500, etc.) are required to determine the exploitable blocks and their sequence of extraction. However, the number of samples that can be taken and analyzed is restricted, and thus the quality properties should be ...
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The quality properties of andesite (Unit Volume Weight, Uniaxial Compression Strength, Los500, etc.) are required to determine the exploitable blocks and their sequence of extraction. However, the number of samples that can be taken and analyzed is restricted, and thus the quality properties should be estimated at unknown locations. Cokriging has been traditionally used in the estimation of spatially cross-correlated variables. However, it can face unsolvable matrices in its algorithm. An alternative to cokriging is to transform variables into spatially orthogonal factors, and then to apply kriging to them. Independent Component Analysis (ICA) is one of the methods that can be used to generate these factors. However, ICA is applicable to zero lag distance so that using methods with distance parameter in their algorithms would be advantageous. In this work, Minimum Spatial Cross-correlation (MSC) was applied to six mechanical properties of Cubuk andesite quarry located in Ankara, Turkey, in order to transform them into approximately orthogonal factors at several lag distances. The factors were estimated at 1544 (5 m × 5 m) regular grid points using the kriging method, and the results were back-transformed into the original data space. The efficiency of the MSC-kriging was compared with Independent Component kriging (IC-kriging) and cokriging through cross-validation test. All methods were unbiased but the MSC-kriging outperformed the IC-kriging and cokriging because of having the lowest mean errors and the highest correlation coefficients between the estimated and the observed values. The estimation results were used to determine the most profitable blocks and the optimum direction of extraction.
Exploitation
I. Masoumi; Gh.R. Kamali; O. Asghari
Abstract
Dilution can best be defined as the proportion of waste tonnage to the total weight of ore and waste in each block. Predicting the internal dilution based on geological boundaries of waste and ore in each block can help engineers to develop more reliable long-term planning designs in mining activities. ...
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Dilution can best be defined as the proportion of waste tonnage to the total weight of ore and waste in each block. Predicting the internal dilution based on geological boundaries of waste and ore in each block can help engineers to develop more reliable long-term planning designs in mining activities. This paper presents a method to calculate the geological internal dilution in each block and to correct the ultimate grade of each geological block according to the internal dilution values that have already been calculated for each one of them. In this regard, the input data is first indexed based on the lithological logs of drill holes. The occurrence probabilities of ore and waste in each block are calculated via 100 realizations using the sequential indicator simulation. Dilution is computed as the ratio of waste rock tonnage to the total tonnage of ore and waste. Furthermore, joint simulation of the continuous variables is performed for each mining block using the minimum/maximum auto-correlation factors. In the next step, for each block, the final grade variables including iron and iron oxide are computed by considering the calculated internal dilution. These analyses are applied to the Gohar Zamin iron ore deposit, and the actual internal dilution calculated based on the lithological logs of blast holes is compared with the same values obtained based on the proposed method in each block. The results obtained were found to be satisfactory.
Y. Asgari Nezhad; A. Moradzadeh
Abstract
One of the most essential factors involved in unconventional gas reserves for drilling and production is a suitable quality facies determination. The direct core and geochemical analyses are the most common methods used for studying this quality. Due to the lack of this data and the high cost, the researchers ...
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One of the most essential factors involved in unconventional gas reserves for drilling and production is a suitable quality facies determination. The direct core and geochemical analyses are the most common methods used for studying this quality. Due to the lack of this data and the high cost, the researchers have recently resorted to the indirect methods that use the common data of the reservoir (including petro-physical logs and seismic data). One of the major problems in using these methods is that the complexities of these reproducible repositories cannot be accurately modeled. In this work, the quality of facies in shale gas is zoned using the deep learning technique. The applied method is long short-term memory (LSTM) neural network. In this scheme, the features required for zoning are automatically extracted and used to model the reservoir complexities properly. The results of this work show that zoning is done with an appropriate accuracy (86%) using the LSTM neural network, while it is 78% for a conventional intelligent MLP network. This specifies the superior accuracy of the deep learning method.
J. Zadhesh; A. Majdi
Abstract
The mechanisms of deformation and failure of the structures in and on the jointed rock masses are often governed by the characteristics of the geometrical properties of joints. Since the joint geometry properties have a range of values, it is helpful to understand the distribution of these values in ...
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The mechanisms of deformation and failure of the structures in and on the jointed rock masses are often governed by the characteristics of the geometrical properties of joints. Since the joint geometry properties have a range of values, it is helpful to understand the distribution of these values in order to predict how the extreme values may be compared with the values obtained from a small sample. This work studies three datasets of joint systems (1652 joint data) from nine outcrops of igneous, sedimentary, and metamorphic rocks in order to determine the probability distribution function of the rock joint geometry properties. Consequently, the goodness-of-fit (GOF) tests are applied to obtain the data. According to these GOF tests, the Lognormal is the best probability distribution function representing the joint spacing, aperture, and trace length. The Cauchy is the best probability distribution function for the joint dip angle. It is found that the Cauchy distribution function is the best probability distribution function to represent the joint dip direction of igneous rocks, and the Burr distribution function is the best probability distribution function to define the joint dip direction of the sedimentary and metamorphic rocks.
Rock Mechanics
L. Nikakhtar; Sh. Zare; H. Mirzaei Nasir Abad
Abstract
One of the main issues involved during tunnel construction with tunnel boring machines is the tail gap grouting. This gap is between the external diameter of tunnel lining and the excavation boundary that is filled with high-pressure grouting materials. In this work, three different approaches of gap ...
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One of the main issues involved during tunnel construction with tunnel boring machines is the tail gap grouting. This gap is between the external diameter of tunnel lining and the excavation boundary that is filled with high-pressure grouting materials. In this work, three different approaches of gap grouting modeling in the FLAC3D software are investigated with a special attention to the influence of the grout material hardening process. In the first approach, the grout is modeled as a liquid during injection, and considering the TBM advancement and its hardening time, the grout characteristics are changed to the properties of the solid grouting. In the second approach, the grouting material from the beginning of injection is considered with the properties of solid grouting in the model, and the liquid phase is ignored. In the third approach, without considering the back-filled grouting area in the model geometry, only the injection pressure is applied to the end of the shield and behind the installed segments. The validity of the approaches is evaluated with respect to the maximum ground surface settlement. All the three approaches estimate different surface settlement but the result of the first approach is closer to the monitoring data. Also as a sensitivity analysis, in this work, we investigate the effect of the elastic modulus of liquid and solid grouting materials on the amount of surface settlement that can help to gain a more accurate insight into the effect of grout mixture.
Mohammad Rezaei; Navid Nyazyan
Abstract
Rock drilling is one of the most important processes in the mining operations, which involves high costs. Deep knowledge of the drilling conditions and rock mass properties can help the optimum selection of drilling system, precise determination of type and number of drilling equipment, and accurate ...
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Rock drilling is one of the most important processes in the mining operations, which involves high costs. Deep knowledge of the drilling conditions and rock mass properties can help the optimum selection of drilling system, precise determination of type and number of drilling equipment, and accurate prediction of drilling rate. The above process leads to enhance the drilling efficiency and mining productivity. In this work, relationships between the rock the physico-mechanical properties and horizontal drilling rate (HDR) are investigated. For this purpose, HDR is firstly measured during the drilling process at the Malawi marble quarry mine, Islamabad-e-Gharb, Iran. Then core samples are prepared from the representative minor rock blocks to conduct the laboratory tests and evaluate the influence of rock properties on HDR. The experimental results prove that natural density (ρn), dry density (ρd), slake durability index (Id), Schmidt hammer rebound (SHR), compression wave velocity (Vp), point load index (PLI), uniaxial compressive strength (UCS), and modulus of elasticity (E) have inverse relationships with HDR. Conversely, HDR has a direct relationship with porosity (n), water content (Wa), Los Angeles abrasion (LAA), and Poisson ratio (ν). Generally, it is proved that HDR is more associated with the rock's physical properties than the mechanical characteristics. Moreover, sensitivity analysis confirm that n and ρd are the most and least effective variables on HDR. Furthermore, new optimum empirical equations with acceptable accuracy are proposed to predict HDR based on the statistical modeling. Finally, experimental verification analysis confirm the superiority of this study compared to the prior similar studies.
