Environment
S. Abbaszade; F. Mohammad Torab; A. Alikhani; H. Molayemat
Abstract
In geochemical exploration, there are various techniques such as univariate and multivariate statistical methods available for recognition of anomalous areas. Univariate techniques are usually utilized to estimate the threshold value, which is the smallest quantity among the values representing the anomalous ...
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In geochemical exploration, there are various techniques such as univariate and multivariate statistical methods available for recognition of anomalous areas. Univariate techniques are usually utilized to estimate the threshold value, which is the smallest quantity among the values representing the anomalous areas. In this work, a combination of the Sequential Gaussian Simulation (SGS) and Gap Statistics (GS) methods was utilized as a new technique to estimate the threshold and to visualize the anomalous regions in the Hararan area, which is located in SE Iran, and consists of copper mineralization that seems to be connected to a porphyry Cu-Mo system. Furthermore, the most important advantage of this method is the reliable assessment of the anomalous areas. In other words, the anomalous areas were discriminated in terms of their probability values. The regions with high probability values were reliable and appropriate to locate the drilling points for a detailed exploration. It not only decreases the risk, cost, and time of exploration but also increases the drilling point reliability and precision of reserve estimation after drilling. In this research work, the results of analysis of 607 lithogeochemical samples for the element Cu were used. The SGS method was performed on the transformed data and 50 realizations were obtained. In the next step, the back-transformed realizations were utilized to obtain an E-type map, which was the average of 50 realizations. Moreover, the results of the GS method showed that the Cu threshold value was 228 ppm in the area. Therefore, using the E-type map, areas with values greater than 228 ppm were introduced as the anomalous areas. Finally, the probability map of the exceeding threshold values was acquired, and the anomalous districts located in the southern part of the studied area were considered as more reliable regions for future detailed exploration and drilling.
Exploitation
Yehia Z. Darwish; Abdelrahem Khalefa Embaby; Samir Selim; Darwish El Kholy; Hani Sharafeldin; Hussin Farag
Abstract
The younger granites of Gabal Gattar area, Northern Eastern Desert of Egypt, host hydrothermal uranium mineralization at the northern segment of Gattar batholith and along its contacts with the oldest Hammamat sediments. The host rocks display many features of hydrothermal overprint results in changing ...
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The younger granites of Gabal Gattar area, Northern Eastern Desert of Egypt, host hydrothermal uranium mineralization at the northern segment of Gattar batholith and along its contacts with the oldest Hammamat sediments. The host rocks display many features of hydrothermal overprint results in changing their basic engineering characteristics as a function of variations of the degree of alteration. Progression from less altered to altered and mineralized rocks as the result of the alteration processes was assessed by the chemical index of alteration (CIA). The CIA numerical values were calculated by the molecular proportion of Al to the cations Ca, Na, and K. The studied rocks were divided into five grades according to degree of alteration and strength properties including: fresh (AG-I), slightly altered (AG-II), moderately altered (AG-III), highly altered (AG-IV) and very highly altered (AG-V). The strength properties of the studied rock units correlated well with the alteration grades assigned to them. That is, as the grade increased from AG-I to AG-V, abrasion resistance and crushability index increased, whereas compressive strength, slake durability and impact strength decreased.
Mohammad Reza Garmsiri; Hassan Haji Amin Shirazi
Abstract
The results of batch settling tests (BST) are used to investigate settling behavior of solids suspension, which contribute to sizing thickeners. Conventional methods in analyzing BST on the basis of visual and graphical procedures lead to sub-optimally sized and selected thickeners. A computational approach ...
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The results of batch settling tests (BST) are used to investigate settling behavior of solids suspension, which contribute to sizing thickeners. Conventional methods in analyzing BST on the basis of visual and graphical procedures lead to sub-optimally sized and selected thickeners. A computational approach based on quantitative analysis of BST can be beneficial. About 300 settling experiments were performed by varying conditions, including solids concentration, type and dosage of chemical aids. Solid samples were collected from iron, copper, coal, lead and zinc tailings and feed streams. Settling curves based on experimental data considering extreme limits were generated and analyzed. Therefore, a mathematical model, h(t), is introduced to define batch settling curves. Furthermore, it is shown that, on settling velocity curves a maximum value is likely to occur (except in extreme conditions such as very high or very low solids concentration suspensions or extremely high dosage of flocculant). In addition, to compare batch settling curves quantitatively, an index, Ii, based on parameters which can be obtained from the model h(t), is developed. The proposed model and index can simply be utilized in a computerized approach of settling curves analysis.
Amid Morshedlou; Hesam Dehghani; Seyed Hadi Hoseinie
Abstract
Utilizing the gathered failure data and failure interval data from Tabas coal mine in two years, this paper discusses the reliability of powered supports. The data sets were investigated using statistical procedures and in two levels: the existence of trend and serial correlation. The results show that ...
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Utilizing the gathered failure data and failure interval data from Tabas coal mine in two years, this paper discusses the reliability of powered supports. The data sets were investigated using statistical procedures and in two levels: the existence of trend and serial correlation. The results show that the powered supports follow the Gamma reliability function. The reliability of the machine decreases to almost zero after 520 operation hours and after 80 hours the probability of failure of powered supports increases to 60 percent. The failure rate of powered support shows an improving behavior and therefore a decreasing failure rate. In the beginning of the process, the failure rate is 0.021 failures per hour. This reaches the rate of 0.012 after a sudden decrease, thence forward on a gently decreasing rate and after 100 hours gets to the rate of 0.01. Regarding the maintenance policy and to protect the machine’s operation continuity, preventive maintenance strategy can be chosen. The reliability of the discussed machine can be maintained on a descent level by inspecting and controlling the parts in short term intervals. With regard to reliability plots of powered supports operation, preventive reliability-based maintenance time intervals for 80% reliability levels for powered supports is 15 hours.
F. Khorram; H. Memarian; B. Tokhmechi; H. Soltanian-zadeh
Abstract
In this study based on image analysis, an ore grade estimation model was developed. The study was performed at a limestone mine in central Iran. The samples were collected from different parts of the mine and crushed in size from 2.58 cm down to 15 cm. The images of the samples were taken in appropriate ...
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In this study based on image analysis, an ore grade estimation model was developed. The study was performed at a limestone mine in central Iran. The samples were collected from different parts of the mine and crushed in size from 2.58 cm down to 15 cm. The images of the samples were taken in appropriate environment and processed. A total of 76 features were extracted from the identified rock samples in all images. Neural network used as an intelligent tool for ore grade estimation and the features of every image were combined with weighted average method. In order to feature dimensional decrease, principal component analysis method was used. Six principal components, which were extracted from the feature vectors, captured 90.661% of the total feature variance. Components were used as the input to neural network and four grade attributes of limestone (CaCO3, Al2O3, Fe2O3 and MgCO3) were used as the output. The root of mean squared error between the observed values and the model estimated values for the test data set are 6.378, 4.847, 0.1513 and 0.0284, the R2 values are 0.7852, 0.8663, 0.7591and 0.8094 for the mentioned chemical composition respectively. The magnitude of R2 indicates the correlation between actual and estimated data. Therefore, it can be inferred that the model can successfully estimate the limestone chemical compositions percentage.
M. Noroozi; R. Kakaie; Seyed M. E Jalali
Abstract
Fault zones and fault-related fracture systems control the mechanical behaviors and fluid-flow properties of the Earth’s crust. Furthermore, nowadays, modeling is being increasingly used in order to understand the behavior of rock masses, and to determine their characteristics. In this work, fault ...
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Fault zones and fault-related fracture systems control the mechanical behaviors and fluid-flow properties of the Earth’s crust. Furthermore, nowadays, modeling is being increasingly used in order to understand the behavior of rock masses, and to determine their characteristics. In this work, fault zones and fracture patterns are reviewed, and also comprehensive studies are carried out on the fracture geometry and density variations. A model to describe damage zones around the strike-slip faults is developed, in which the range of damage zone styles commonly found around strike-slip fault zones are shown. A computer code, named DFN-FRAC3D, is developed for the two- and three-dimensional stochastic modeling of rock fracture systems in fault zones. In this code, the pre-existing and fault-related fractures are modeled by their respective probability distributions, and the joint density may be varied by the distance from the fault core. This work describes the theoretical basis and the implementation of the code, and provides a case study in the rock fracture modeling to demonstrate the application of the prepared code.
H. Moeini; A. Aryafar
Abstract
Anomaly recognition has always been a prominent subject in preliminary geochemical explorations. Among the regional geochemical data processing, there are a range of statistical and data mining techniques as well as different mapping methods, which serve as presentations of the outputs. The outlier’s ...
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Anomaly recognition has always been a prominent subject in preliminary geochemical explorations. Among the regional geochemical data processing, there are a range of statistical and data mining techniques as well as different mapping methods, which serve as presentations of the outputs. The outlier’s values are of interest in the investigations where data are gathered under controlled conditions. These values in exploration geochemistry indicate the mineralization occurrences, and therefore, their identification is vital. Both the robust parametric (based on Mahalanobis distance) and non-parametric (based on depth functions) techniques have been developed for a multivariate outlier identification in geochemistry data. In this research work, we applied the local multivariate outlier identification approach to delineate the geochemical anomaly halos in the Hamich region, which is located in the SE of Birjand, South Khorasn province, East of Iran. For this purpose, 396 litho-geochemical samples that had been analyzed for 44 elements were used. The obtained results show a good agreement with the geological and mineral indices of Pb, Zn, and Cu in the southern part of the area. Such studies can be used by a project director to optimize the core drilling places in detailed exploration steps.
Mineral Processing
M. Heshami; R. Ahmadi
Abstract
The aim of this work is to investigate the effect of thermal treatment on the grinding behavior of manganese ore in the various size fractions of -1.7+1.18, -1.18+0.6, -0.6+0.3 and -0.3+ 0.15 mm. Breakage Function Determination Software (BFDS) is used to calculate the selection function of the experiment. ...
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The aim of this work is to investigate the effect of thermal treatment on the grinding behavior of manganese ore in the various size fractions of -1.7+1.18, -1.18+0.6, -0.6+0.3 and -0.3+ 0.15 mm. Breakage Function Determination Software (BFDS) is used to calculate the selection function of the experiment. The results of SEM analysis show the micro-cracks in the thermally treated manganese sample, and DTA/TG analysis show that heating at 750 °C leads to dehydroxylation of montmorillonite, and decomposition of calcite and decomposition of montmorillonite to silicate minerals occur at 850 °C. Montmorillonite mineral with a hardness of 2 is turned into silicate minerals with an average hardness of 7. Therefore, it can be seen that the thermal treatment leads to a decrease in the specific rate of breakage from 1.04 min-1 to 0.65 min-1 (approximately to 37%) for a size fraction of -0.300+ 0.15 mm. It; can be expressed that the thermally treated sample is broken more slowly than the untreated sample. Also, parameter “A” is the maximum Si value, decreasing for the heated sample from 4.36 min-1 to 4.28 min-1. The selection function results show that all size fractions of this material follow a first-order kinetics.
M. Adil; S. Raza; I. Amin
Abstract
Despite the slope stability measures, rock falls are witnessed at section KM-37 of the Swat motorway (M-16), Khyber Pakhtunkhwa, Pakistan. The geotechnical data analysis of the site reveals that although the chances of plane/slope failures are reduced from 43% to 23% with the help of the existing design, ...
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Despite the slope stability measures, rock falls are witnessed at section KM-37 of the Swat motorway (M-16), Khyber Pakhtunkhwa, Pakistan. The geotechnical data analysis of the site reveals that although the chances of plane/slope failures are reduced from 43% to 23% with the help of the existing design, still there are possibilities of rock fall at the sight, which has also been witnessed during the field visits. The rock fall hazards are assessed through field tests and simulation, and significant stabilization measures are suggested. The rock fall tests are conducted, and then using the data obtained, the rock fall simulation is carried out using GeoRock 2D®. From a combination of the kinematic analysis and rock fall simulation, the hazard level along the slope ranges from moderate to high. The reason for this is the increasing velocity of the falling boulder and the impact of energy at the bottom of the slope. This is an indication of the risk, as the most hazardous area is at the toe of the slope, where the highway road is the main element at risk. Rock boulders of different shapes and sizes are released from a couple of benches in order to check their impacts on the highway. Based on the simulation, it is concluded that the spherical shaped boulders are released from higher benches covering more horizontal distances and reaching the highway with a higher bouncing heights at the toe of the slope than the cylindrical shaped boulders. The maximum bounce height of 7 m has been recorded at the toe of the slope. In order to reduce the impacts of energy and bounce heights of the boulders striking the slope surface, certain mitigation measures are suggested like a ditch of a specific size filled with sand or fine debris at the toe of the slope. Draping wire mesh on the slope surface and a retaining wall or fence would be greatly helpful and economical to reduce the rock falling hazards along the road side at section KM-37 of the Swat motorway.
M. Moghadasi; A. Nejati Kalateh; M. Rezaie
Abstract
Gravity data inversion is one of the important steps in the interpretation of practical gravity data. The inversion result can be obtained by minimization of the Tikhonov objective function. The determination of an optimal regularization parameter is highly important in the gravity data inversion. In ...
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Gravity data inversion is one of the important steps in the interpretation of practical gravity data. The inversion result can be obtained by minimization of the Tikhonov objective function. The determination of an optimal regularization parameter is highly important in the gravity data inversion. In this work, an attempt was made to use the active constrain balancing (ACB) method to select the best regularization parameter for a 3D inversion of the gravity data using the Lanczos bidiagonalization (LSQR) algorithm. In order to achieve this goal, an algorithm was developed to estimate this parameter. The validity of the proposed algorithm was evaluated by the gravity data acquired from a synthetic model. The results of the synthetic data confirmed the correct performance of the proposed algorithm. The results of the 3D gravity data inversion from this chromite deposit from Cuba showed that the LSQR algorithm could provide an adequate estimate of the density and geometry of sub-surface structures of mineral deposits. A comparison of the inversion results with the geologic information clearly indicated that the proposed algorithm could be used for the 3D gravity data inversion to estimate precisely the density and geometry of ore bodies. All the programs used in this work were provided in the MATLAB software environment.
Mineral Processing
M. Jahani Chegeni; S. Kolahi
Abstract
The shell liner type, rotation speed, and ball filling percent are the key factors influencing the charge behavior inside the SAG mills, and consequently, their performance. In this work, the milling operation of industrial SAG mills is investigated using the Discrete Element Method (DEM). First, an ...
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The shell liner type, rotation speed, and ball filling percent are the key factors influencing the charge behavior inside the SAG mills, and consequently, their performance. In this work, the milling operation of industrial SAG mills is investigated using the Discrete Element Method (DEM). First, an industrial SAG mill with dimensions of 9.50 m × 4.42 m that has a Smooth-type liner is simulated. Then by changing the liner types, i.e. Wave, Rib, Ship-lap, Lorain, Osborn, and Step liners, six other independent simulations are performed. In order to investigate the impact mechanism and improve the mill performance, two new parameters called ‘head height’ and ‘impact zone length’ are introduced. Then the effects of the mill shell liner type on those parameters at two different mill speeds, i.e. 70% and 80% of its critical speed (CS), are evaluated. Also for validation of the simulation results, a laboratory-scale SAG mill with dimensions of 57.3 cm × 16.0 cm is simulated. The results obtained indicate that the Osborn liner, due to the angularity of its lifters and their proper number and thickness, performs best because it increases both parameters more than the other liners. Thus this liner is recommended as the best and optimal liner in this research work and is suggested for installation inside the industrial SAG mills. Also the Wave liner, due to its specific geometrical shape and its wavy lifters as well as their low number and inadequate thickness, provides the lowest charge ‘head height’. Therefore, it is not recommended to install this liner inside the industrial SAG mills. Meanwhile, comparison of the simulations related to the laboratory-scale SAG mill with the experimental results demonstrates a good agreement that validates the DEM simulations and the software used.
Exploitation
R. Shamsi; M. S. Amini; H. Dehghani; M. Bascompta; B. Jodeiri Shokri; Sh. Entezam
Abstract
This paper attempted to estimate the amount of flyrock in the Angoran mine in Zanjan province, Iran using the gene expression programming (GEP) predictive technique. The input data, including flyrock, mean depth of the hole, powder factor, stemming, explosive weight, number of holes, and booster were ...
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This paper attempted to estimate the amount of flyrock in the Angoran mine in Zanjan province, Iran using the gene expression programming (GEP) predictive technique. The input data, including flyrock, mean depth of the hole, powder factor, stemming, explosive weight, number of holes, and booster were collected from the mine. Then, using GEP, a series of intelligent equations were proposed to predict flyrock distance. The best GEP equation was selected based on some well-established statistical indices in the next stage. The coefficient of determination for training and testing datasets of the GEP equation were 0.890 and 0.798, respectively. The model obtained from the GEP method was then optimized using teaching– learning-based optimization algorithm (TLBO). Based on the results, the correlation coefficient of training and testing data increased to 91% and 89%, which increased the accuracy of the Equation. This new intelligent equation could forecast flyrock resulting from mine blasting with a high level of accuracy. The capabilities of this intelligent technique could be further extended to the other blasting environmental issues.
M. Mohammadi Behboud; A. Ramezanzadeh; B. Tokhmechi
Abstract
Multiplicity of the effective factors in drilling reflects the complexity of the interaction between rock mass and drilling bit, which is followed by the dependence of parameters and non-linear relationships between them. Rock mass or, in other words, the formation intended for drilling, as the drilling ...
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Multiplicity of the effective factors in drilling reflects the complexity of the interaction between rock mass and drilling bit, which is followed by the dependence of parameters and non-linear relationships between them. Rock mass or, in other words, the formation intended for drilling, as the drilling environment, plays a very essential role in the drilling speed, depreciation of drilling bit, machines, and overall drilling costs. Therefore, understanding the drilling environment and the characteristics of the in-situ rock mass contributes a lot to the selection of the machines. In this work, a 1D geo-mechanical model of different studied wells is built by collecting the geological data, well logs, drilling data, core data, and pressure measurements of the formation fluid pressure in various wells. Having the drilling parameters of each part of the formation, its specific energy is calculated. The specific energy index can be used for predicting the amount of energy consumed for drilling. In order to find the relationship between the drilling specific energy (DSE) and its effective parameters, the multivariate regression model is used. Modeling DSE is done using the multivariate regression, which contains the parameters rock characteristics, well logs, and a combination of these two features. 70% and 30% of the data are, respectively, selected as the training and test for validation. After analyzing the model, the correlation coefficients obtained for the training and test data were, respectively, found to be 0.79 and 0.83. The parameters uniaxial compressive strength (UCS), internal friction angle, and fluid flow are among the most important factors found to affect DSE.
Demet Demir Sahin; Ibrahim Cavusoglu; Ali Osman Yilmaz
Abstract
Today, energy produced from coal is economical compared to other sources but it faces a very serious waste problem. However, these wastes are evaluated by using them as mineral additives in cement, which leads to lower cement costs, saving resources, producing environmentally friendly cement, reducing ...
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Today, energy produced from coal is economical compared to other sources but it faces a very serious waste problem. However, these wastes are evaluated by using them as mineral additives in cement, which leads to lower cement costs, saving resources, producing environmentally friendly cement, reducing CO2 gas, and producing high-strength cement. In this work, the pozzolanic properties of different types of fly ash (Afşin Elbistan C type and Çayırhan F type) are investigated. The fly ashes used in the study are first subjected to the milling process (10, 20, 30, 45, and 60 minutes), and then the 28 and 90-day pozzolanic activity index tests of the milled and unmilled ashes are performed. The results obtained show that the 28-day pozzolanic activity value of the ashes subjected to 20-, 30-, 45-, and 60-minute milling times are higher than the value specified in the standard, compared to the unmilled and 10 min milled fly ash. In addition, for all fly ash samples, the 90-day pozzolanic activity index results show that while the pozzolanic activity index value of Çayırhan (ÇYH) fly ash is higher than the standard value, that of Afşin Elbistan (AE) fly ash is lower than standard. The outcomes of the present study show that the mechanical properties of the fly ash are generated by the burning of coal increase after milling process, and thus can be used as a mineral additive. With the effect of grinding, both fly ash increase the pozzolanic activity. The results are determined with the experimental results obtained.
Environment
Aditi Nag; Anurag Singh Rathore
Abstract
The tourism industry is experiencing a profound transformation driven by digital innovations such as virtual reality (VR), augmented reality (AR), and interactive platforms. This paper explores how these technologies are reshaping destination competitiveness, with a specific focus on the mining heritage ...
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The tourism industry is experiencing a profound transformation driven by digital innovations such as virtual reality (VR), augmented reality (AR), and interactive platforms. This paper explores how these technologies are reshaping destination competitiveness, with a specific focus on the mining heritage sites (MHSs). By leveraging VR and AR, heritage sites can offer immersive and interactive experiences that enhance visitor engagement, and broaden their reach. Through a case-study analysis, this work examines successful implementations of digital tourism initiatives at various MHSs including the Big Pit National Coal Museum, the Mining Museum of Slovenia, the Mining Museum of the West, the Erzgebirge Mining Region, and the Mesabi Iron Ore Mines. The findings reveal that digital tools significantly improve accessibility, educational value, and global appeal of these sites. However, challenges such as the technical and financial constraints remain. The paper concludes with recommendations for practitioners on integrating digital technologies effectively and suggestions for future research to explore long-term impacts and emerging trends. This work underscores the transformative potential of digital innovation in enhancing the competitiveness and sustainability of tourism destinations.
Mine Economic and Management
Saira Sherin; Salim Raza
Abstract
Despite a decline in mining accidents and improvements in safety performance, the proportion of accidents in mines remains high in developing countries. Although underground mining is one of the most hazardous occupations, surface mining also carries multiple risks that receive comparatively less attention. ...
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Despite a decline in mining accidents and improvements in safety performance, the proportion of accidents in mines remains high in developing countries. Although underground mining is one of the most hazardous occupations, surface mining also carries multiple risks that receive comparatively less attention. In developing countries like Pakistan, research is focused mainly on fatal and serious accidents, often overlooking minor and near-miss accidents. This study assesses the risks of fatalities and injuries faced by occupational groups engaged in surface mining. For this purpose, an analytical hierarchy process is used to analyze fatalities data and Fuzzy TOPSIS for injuries data. It can be concluded that all occupational groups are exposed to fatalities and injuries risks due to various hazards. However, some activities are more prone to fatalities while others are to injuries. Laborers are most frequently involved in such accidents. Common risks such as falling rocks and slippage from the top affect all occupational groups equally. Incidents involving slippages from the tops result in more fatalities, whereas machinery-related risks lead to more injuries than fatalities. Hazards causing minor injuries are frequently overlooked in terms of prevention and control efforts until they lead to serious injuries/fatalities. It is suggested that every accident, regardless of severity, be reported and thoroughly analyzed regularly to minimize the recurrence of incidents. The essential measures for creating a safer mining environment include implementing appropriate mechanization, providing regular training to workers, enforcing the use of personal protective equipment, and strict adherence to mining laws.
Mineral Processing
F. Basirifar; M.R. Khalesi; M. Ramezanizadeh; M. Abdollahy; A. Hajizadeh
Abstract
Partition curves are widely used to determine the spiral separator efficiency. In this work, the partition curves were used in order to investigate the particle transportation to concentrate and tailing streams. Simulation of fine particle removal using the size-by-size partition curves showed that the ...
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Partition curves are widely used to determine the spiral separator efficiency. In this work, the partition curves were used in order to investigate the particle transportation to concentrate and tailing streams. Simulation of fine particle removal using the size-by-size partition curves showed that the recovery of gangue particles to concentrate can decrease 8.7%. It also showed that the recovery of valuable particles would increase by 6.5% and reaches 90%. Therefore, pilot-scale tests were conducted to verify the simulations. After removal of fine particles from the feed of spiral separator and treating the removed materials with high-intensity magnetic separator, total mass recovery, iron recovery, and iron grade increased from 71%, 85%, and 54% to 80%, 91%, and 56%, respectively.
Rock Mechanics
M. Zoorabadi
Abstract
Numerical modelling techniques are not new for mining industry and civil engineering projects anymore. These techniques have been widely used for rock engineering problems such as stability analysis and support design of roadways and tunnels, caving and subsidence prediction, and stability analysis of ...
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Numerical modelling techniques are not new for mining industry and civil engineering projects anymore. These techniques have been widely used for rock engineering problems such as stability analysis and support design of roadways and tunnels, caving and subsidence prediction, and stability analysis of rock slopes. Despite the significant advancement in the computational mechanics and availability of high speed computing hardware, the input data and constitutive models remain the main source of errors affecting the reliability of numerical simulations. The problem with the input data has been deepened more by introducing empirical-based methods such as GSI classification to downgrade the rock properties from laboratory scale to field scale. The deformability modulus and strength parameters are the main outputs of these downgrading techniques. Numerical modelling users simply apply these downgrading methods and run the model without considering the real mechanics behind the stress induced failure and deformation around the underground excavations. While to the contrary to the commonly used downgrading methods that produce a constant modulus for rock at all depths, the rock modulus is stress dependent and varies with depth. In addition to this, the mechanism of stress induced displacement is not similar to the deformation of a continuum model simulated with equivalent rock properties. Apart from the mechanical characteristics of rocks, the magnitude and orientation of in-situ stresses are two other important parameters that have significant impacts on stress induced rock fracturing. The impacts of these two parameters have also been neglected in many practical cases. This paper discuss this old fashioned topic in more details with presenting the known facts and mechanics which numerical modelling users ignore them due to the unquestioning acceptance of downgrading methods. It also covers the influence of the stress magnitude and orientation on stress induced rock fracturing.
Exploitation
H.R. Nezarat; Seyed M. E. Jalali; M. Nazari
Abstract
Knowledge of the airflow distribution inside a Tunnel Boring Machine (TBM) can create a safe working environment for workers and machinery. The airflow quality and the related mass flow rate in the ventilation system should be sufficient to dilute gases and remove dust inside the tunnel. In this work, ...
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Knowledge of the airflow distribution inside a Tunnel Boring Machine (TBM) can create a safe working environment for workers and machinery. The airflow quality and the related mass flow rate in the ventilation system should be sufficient to dilute gases and remove dust inside the tunnel. In this work, airflow distribution in the single shield TBM tunnel was studied using computational fluid dynamics. The finite volume-based finite element method was used in the simulation based on the 3D complex geometry of TBM. In order to validate the numerical results, the air velocity inside the Chamshir tunnel was measured experimentally at different sections. With a length of 7050 m and a final diameter of 4.6 m, the Chamshir water transport tunnel is located in the south of Iran. The results obtained show that there is not enough airflow in 59.6% of the TBM space in the current working conditions. In other words, there are many dead zones from the control cabin to the end of gantry 6 in the backup system. Several applicable scenarios were studied to remove the dead zone area and optimize the airflow velocity by employing high capacity jet fan in the ventilation system. The results show that the dead zone volume can be decreased by about 5.21% by increasing the airflow rate of the jet fan.
A. Srivastava; B. Singh Choudhary; M. Sharma
Abstract
Blast-induced ground vibration (PPV) evaluation for a safe blasting is a long-established criterion used mainly by the empirical equations. However, the empirical equations are again considering a limited information. Therefore, using Machine Learning (ML) tools [Support Vector Machine (SVM) and Random ...
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Blast-induced ground vibration (PPV) evaluation for a safe blasting is a long-established criterion used mainly by the empirical equations. However, the empirical equations are again considering a limited information. Therefore, using Machine Learning (ML) tools [Support Vector Machine (SVM) and Random Forest (RF)] can help in this context, and the same is applied in this work. A total of 73 blasts are monitored and recorded in this work. For the ML tools, the dataset is divided into the 80-20 ratio for the training and testing purposes in order to evaluate the performance capacity of the models. The prediction accuracies by the SVM and RF models in predicting the PPV values are satisfactory (up to 9% accuracy). The results obtained show that the coefficient of determination (R2) for RF and SVM is 0.81 and 0.75, respectively. Compared to the existing linear regressions, this work recommends using a machine learning regression model for the PPV prediction.
Reza Mikaeil; Mostafa Piri; Sina Shaffiee Haghshenas; Nicola Careddu; Hamid Hashemolhosseini
Abstract
The noise of drilling in the dimension stone business is unbearable for both the workplace and the people who work there. In order to reduce the negative effects drilling has on the health of the environment, the drilling noise has to be measured, assessed, and controlled. The main purpose of this work ...
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The noise of drilling in the dimension stone business is unbearable for both the workplace and the people who work there. In order to reduce the negative effects drilling has on the health of the environment, the drilling noise has to be measured, assessed, and controlled. The main purpose of this work is to investigate an experimental-intelligent method to predict the noise value of drilling in the dimension stone industry. For this purpose,135 laboratory tests are designed on five types of rocks (four types of hard rock and one type of soft rock), and their results are measured in the first step. In the second step, due to the unpredicted and uncertain issues in this case, artificial intelligence (AI) approaches are applied, and the modeling is conducted using three intelligent systems (IS), namely an adaptive neuro-fuzzy inference system-SCM (ANFIS-SCM), an adaptive neuro-fuzzy inference system-FCM (ANFIS-FCM), and the radial basis function network (RBF) neural network. 75% of the samples are considered for training, and the rest for testing. Several models are constructed, and the results indicate that although there is no significant difference between the models according to the performance indices, the proposed construction of ANFIS-SCM can be considered as an efficient tool in the evaluation of drilling noise. Finally, several scenarios are designed with different input modes, and the results obtained prove that the types of rock and the drill bits are more important than the operational characteristics of the machine.
F. Rastegar; H. R. Nejati; A. Ghazvinian; M. R. Hadei; A. Nazerigivi
Abstract
The tensile strength of rocks plays a noteworthy role in their failure mechanism, and its determination can be beneficial in optimizing the design of the rock structures. Schistose rocks due to their inherent anisotropy in different foliation directions show a diverse strength at each direction. The ...
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The tensile strength of rocks plays a noteworthy role in their failure mechanism, and its determination can be beneficial in optimizing the design of the rock structures. Schistose rocks due to their inherent anisotropy in different foliation directions show a diverse strength at each direction. The purpose of this work was to compare and assess the tensile strength of phyllite, which was obtained in direct and indirect tensile tests in different foliation directions. To this end, several phyllite specimens with different foliation angles (0º, 30º, 45º, 60º, and 90º) related to the loading axis (β) were prepared. Finally, the direct tensile test, diametrical and axial point load tests, Brazilian test, and Schmidt hammer test were conducted on 188 samples. The results of the experimental tests revealed that the maximum and minimum tensile strengths in direct tensile testing tension were directly related to the angles of 0º and 90º. Also it was observed that the Brazilian tensile strength overestimated the tensile strength. Furthermore, an exponential correlation was introduced between the direct tensile strength and the Brazilian tensile strength.
Lokeshwar Singh Dilta; Ravi Kumar Sharma
Abstract
This study highlights the results from a series of analytical model experiments that investigate the behaviour of a strip footing supported by hollow steel piles installed to stabilize a clay slope. The effects of changing the pile diameter, pile length, spacing between piles, slope angle, the position ...
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This study highlights the results from a series of analytical model experiments that investigate the behaviour of a strip footing supported by hollow steel piles installed to stabilize a clay slope. The effects of changing the pile diameter, pile length, spacing between piles, slope angle, the position of the pile row from the top of slope, and the footing placement are all examined. After determining the load-carrying capacity of unstabilized slopes, it is compared with the load-carrying capacity of stabilized slopes. The results are then analysed to see how each parameter affects the load carrying capacity of strip footing. The results of unstabilized cases reveal that the load carrying capacity of a footing decreases as the slope angle increases and increases when the footing is positioned away from the slope. In addition, the findings imply that by reinforcing clay slope with a sequence of hollow steel piles significantly enhances the load carrying capacity of strip footing. As the distance between piles is decreased and their length is increased, the bearing capacity of the footing increases, and this improvement is enhanced by increasing the diameter of the piles. When the row of pile is positioned away from the top of the slope, the footing’s load carrying capacity decreases. Also positioning the footing a quite distance apart from the crest slope shows reduction in bearing capacity ratio.
Rock Mechanics
E. Dadashi; A. Noorzad; K. Shahriar; K. Goshtasbi
Abstract
The utilization of the lining type in pressure tunnels is highly dependent on the geological and hydraulic conditions. There are two types of lining, namely concrete and steel lining but steel lining is one of the most expensive arrangements. To decrease the length of steel lining in these tunnels, the ...
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The utilization of the lining type in pressure tunnels is highly dependent on the geological and hydraulic conditions. There are two types of lining, namely concrete and steel lining but steel lining is one of the most expensive arrangements. To decrease the length of steel lining in these tunnels, the concrete lining, which prevents water seepage from the surrounding rock mass, is the appropriate alternative. In this work, a special attention is devoted to limit water losses in the concrete lining of pressure tunnel based on the critical reinforcing ratio in concrete lining. In order to evaluate the effect of internal water pressure on the permeability coefficient variation of the concrete lining and the surrounding rock mass, some simulations of reinforced concrete lining is implemented in the ABAQUS finite element software based on the coupled pore fluid-stress analysis. The results obtained indicate that although the critical reinforcing ratio has an important role in capturing the seepage flows and water losses, it is not sufficient to rely only on this parameter. However, among the various influential factors involved, a suitable arrangement of the reinforcement in the concrete lining should also be considered.
Environment
H. Nikoogoftar; A. Hezarkhani
Abstract
In this paper, we aim to achieve two specific objectives. The first one is to examine the applicability of the Artificial Neural Networks (ANNs) technique in ore grade estimation. Different training algorithms and numbers of hidden neurons are applied to estimate Cu grade of borehole data in the hypogene ...
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In this paper, we aim to achieve two specific objectives. The first one is to examine the applicability of the Artificial Neural Networks (ANNs) technique in ore grade estimation. Different training algorithms and numbers of hidden neurons are applied to estimate Cu grade of borehole data in the hypogene zone of porphyry copper-gold deposit, Masjed-Daghi, East Azerbaijan Province (Iran). The efficacy of ANNs in function-learning and estimation is compared with ordinary kriging (OK). As the kriging algorithms smooth the data, their applicability in the pre-processing of data for fractal analysis is not conducive. ANNs can be introduced as an alternative for this kind of problem. Secondly, we aim to delineate the potassic and phyllic alteration regions in the hypogene zone of Cu-Au porphyry deposit based on the estimation obtained by the ANNs and OK methods, and utilize the Concentration-Volume (C-V) fractal model. In this regard, at first, C-V log-log is generated based on the ANN results. The plots are then used to determine the Cu threshold values for the alteration zones. To investigate the correlation between the geological model and C-V fractal results, the log ratio matrix is applied. The results obtained show that Cu values less than 0.38% from ANNs have more overlapped voxels with phyllic alteration zone by an overall accuracy of 0.72. Spatial correlation between the potassic alteration zones resulting from 3D geological modeling and high concentration zones in C-V fractal model show that Cu values greater than 0.38% have more voxels overlapped with the potassic alteration zone by an overall accuracy of 0.76. Generally, the results obtained show that a combination of the ANNs and C-V fractal methods can be a suitable and robust tool for quantitative modeling of alteration zones instead of the qualitative methods.
