Journal of Mining and EnvironmentJournal of Mining and Environment
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Feed provided by Journal of Mining and Environment. Click to visit.Combining fuzzy RES with GA for predicting wear performance of circular diamond saw in hard ...
http://jme.shahroodut.ac.ir/article_986_0.html
Predicting the wear performance of circular diamond saw in the process of sawing hard dimensional stone is an important step in reducing production costs in the stone sawing industry. In the present research work, the effective parameters on circular diamond saw wear are defined, and then the weight of each parameter is determined through adopting a fuzzy rock engineering system (Fuzzy RES) based on defining an accurate Gaussian pattern in fuzzy logic with analogous weighting. After this step, genetic algorithm (GA) is used to determine the levels of the four major variables and the amounts of the saw wear (output parameter) in the classification operation based on the fixed, dissimilar, and logarithmic spanning methods. Finally, a mathematical relationship is suggested for evaluation of the accuracy of the proposed models. The main contribution of our method is the novelty of combination of these methods in fuzzy RES. Before this work, all Fuzzy RESs only use simple membership functions and uniform spanning. Using GA for spanning and normal distribution as membership function based upon our latest work is the first work in fuzzy RES. To verify the selected proposed model, rock mechanics tests are conducted on nine hard stone samples, and the diamond saw wear is measured and compared with the proposed model. According to the results obtained, the proposed model exhibits acceptable capabilities in predicting the circular diamond saw wear.Mon, 31 Jul 2017 19:30:00 +0100Fault orientation modeling of Sonda- Jherruck coalfield, Pakistan
http://jme.shahroodut.ac.ir/article_1402_165.html
Faults are the most critical tectonic factors in geological structures, which have major economic impacts on mining economics. Thus it is necessary to understand faults in order to identify the actual risks and complications associated with mining. In the preliminary investigation of the Sonda-Jherruck coalfield, 3D geological modeling was not performed. The purpose of this work was to perform fault orientation modeling in order to document pre-mine planning information and discuss the obstacles that may cause problems in mine planning and development stages. Using the drill hole data, 3D fault models based on the calculation of dip angle and dip direction were established. In the first step, surface models of coal seams were established by applying the triangulation method to the coal seam roof elevations. Then an appropriately oriented grid was overlain to regularize the data and to find the unknown points. The calculation of dip and dip direction was done using an algorithm. The models showing the variation in the dip and dip direction were generated using the inverse distance squared weighted (ID2W) interpolation technique. The generated 3D models were compared with the pre-existing fault lines (based on the aerial map). An attempt was made to create comprehensive models that demonstrate a better understanding of the faults in the studied area.Sun, 31 Mar 2019 19:30:00 +0100Performance evaluation of chain saw machines for dimensional stones using feasibility of neural ...
http://jme.shahroodut.ac.ir/article_1246_0.html
Prediction of the production rate of the cutting dimensional stone process is crucial, especially when chain saw machines are used. The cutting dimensional rock process is generally a complex issue with numerous effective factors including variable and unreliable conditions of the rocks and cutting machines. The Group Method of Data Handling (GMDH) type of neural network and Radial Basis Function (RBF) neural network, as two kinds of the soft computing method, are powerful tools for identifying and assessing the unpredicted and uncertain conditions. Hence, this work aims to develop prediction models for estimating the production rate of chain saw machines using the RBF neural network and GMDH type of neural network, and then to compare the results obtained from the developed models based on the performance indices including value account for, root mean square error, and coefficient of determination. For this purpose, the parameters of 98 laboratory tests on 7 carbonate rocks are accurately investigated, and the production rate of each test is measured. Some operational characteristics of the machines, i.e. arm angle, chain speed, and machine speed, and also the three important physical and mechanical characteristics including uniaxial compressive strength, Los Angeles abrasion test, and Schmidt hammer (Sch) are considered as the input data, and another operational characteristic of the machines, i.e. production rate, is considered as the output dataset. The results obtained prove that the developed GMDH model is able to provide highly promising results in order to predict the production rate of chain saw machines based on the performance indices.Tue, 03 Jul 2018 19:30:00 +0100DPM flow pattern of LHD in underground mines with different ventilation conditions
http://jme.shahroodut.ac.ir/article_1406_165.html
Diesel-operated Load Haul Dumper (LHD) vehicles are commonly used in underground coal mines. Despite their value as utility vehicles, the main drawback of these vehicles is that they generate diesel particulate matter (DPM), a known carcinogenic agent. In this work, an attempt is made to model DPM flows generated by LHDs in an underground coal mine environment for different DPM flow and intake air flow directions. The field experiments are conducted and used to validate the computational fluid dynamics (CFD) models and used to map the DPM flow patterns. The results obtained show that if DPM and the intake air co-flow (flow in the same direction), DPM is confined predominantly in the middle of the roadway. To the contrary, if the DPM and intake air counter-flow (flow in the opposite directions), the DPM spread occurs throughout the entire cross-section of the roadway. In the latter case, the operator will be more susceptible to exposure to high concentrations of DPM. Overall, the DPM concentration decreases with an increase in the intake air velocities. For co-flow for intake air velocities of 2 m/s, 3 m/s, and 4 m/s, the DPM concentrations at 50 m downstream of the vehicles are 39 µg/m3, 23 µg/m3, and 19 µg/ m3, respectively. The DPM concentration is also influenced by the DPM temperature at the source. For the DPM temperatures of 30 oC, 40 oC, 50 oC, and 60 oC, the DPM concentrations at 50 m downstream of the source are 43 µg/m3, 34 µg/m3, 12 µg/m3, and 9 µg/m3, respectively.Sun, 31 Mar 2019 19:30:00 +0100Application of non-linear regression and soft computing techniques for modeling process of ...
http://jme.shahroodut.ac.ir/article_1127_165.html
The process of pollutant adsorption from industrial wastewaters is a multivariate problem. This process is affected by many factors including the contact time (T), pH, adsorbent weight (m), and solution concentration (ppm). The main target of this work is to model and evaluate the process of pollutant adsorption from industrial wastewaters using the non-linear multivariate regression and intelligent computation techniques. In order to achieve this goal, 54 industrial wastewater samples gathered by Institute of Color Science & Technology of Iran (ICSTI) were studied. Based on the laboratory conditions, the data was divided into 4 groups (A-1, A-2, A-3, and A-4). For each group, a non-linear regression model was made. The statistical results obtained showed that two developed equations from the A-3 and A-4 groups were the best models with R2 being 0.84 and 0.74. In these models, the contact time and solution concentration were the main effective factors influencing the adsorption process. The extracted models were validated using the t-test and F-value test. The hybrid PSO-based ANN model (particle swarm optimization and artificial neural network algorithms) was constructed for modelling the pollutant adsorption process under different laboratory conditions. Based on this hybrid modeling, the performance indices were estimated. The hybrid model results showed that the best value belonged to the data group A-4 with R2 of 0.91. Both the non-linear regression and hybrid PSO-ANN models were found to be helpful tools for modeling the process of pollutant adsorption from industrial wastewaters.Sun, 31 Mar 2019 19:30:00 +0100Delineation of alteration zones based on kriging, artificial neural networks, and ...
http://jme.shahroodut.ac.ir/article_1275_0.html
This paper presents a quantitative modeling for delineating alteration zones in the hypogene zone of the Miduk porphyry copper deposit (SE Iran) based on the core drilling data. The main goal of this work was to apply the Ordinary Kriging (OK), Artificial Neural Networks (ANNs), and Concentration-Volume (C-V) fractal modelings on Cu grades to separate different alteration zones. Anisotropy was investigated and modeled based on calculating the experimental semi-variograms of Cu value, and then the main variography directions were identified and evaluated. The block model of Cu grade was generated using the kriging and ANN modelings followed by log-log plots of the C-V fractal modeling to determine the Cu threshold values used in delineating the alteration zones. Based on the correlation between the geological models and the results derived via C-V fractal modeling, Cu values less than 0.479% resulting from kriging modeling had more overlapped voxels with the phyllic alteration zone by an overall accuracy (OA) of 0.83. The spatial correlation between the potassic alteration zone in a 3D geological model and the high concentration zones in the C-V fractal model showed that Cu values between 0.479% and 1.023%, resulting from kriging modeling, had the best overall accuracy (0.78). Finally, based on the correlation between classes in the binary geological and fractal models of the hypogene zone, this research work showed that kriging modeling could delineate the phyllic (with lower grades) and potassic (with higher grades) alteration zones more effectively compared with ANNs.Wed, 25 Jul 2018 19:30:00 +0100Application of fractal modeling to delineate alteration zones and lithological units in ...
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In this paper, we aim to present a quantitative modeling for delineating the alteration zones and lithological units in the hypogene zone of Masjed-Daghi Cu-Au porphyry deposit (NW Iran) based on the drill core data. The main goal of this work is to apply Ordinary Kriging (OK) and concentration-volume (C-V) fractal model based on Cu grades in order to separate the different alteration zones and lithological units. Initially, anisotropy was investigated and modeled based on calculating the experimental semi-variograms of the Cu values, and the main variography directions were identified and evaluated. Then a block model of the Cu grades was generated using the kriging, and the estimation obtained for OK was applied to the C-V fractal model. The C–V log–log plot based on the estimation method represents the various alteration and lithological zones via threshold values. The comparison and interpretation of the alteration zones and lithological units based on the C–V fractal modeling proved that the method was acceptable and capable of correctly delineating the alteration and lithological units. Regarding the correlation derived from log ratio matrix (used to compare the geological model with the C-V fractal results), it was observed that Cu values less than 0.4% were obtained for OK overlapped voxels with the phyllic alteration zone by an overall accuracy (OA) of 0.737. The spatial correlation between the potassic alteration zones resulting from a 3D geological modeling and the high concentration zones in the C-V fractal model based on OK indicated that the alteration zone contained Cu values greater than 0.4% with OA of 0.791. Also using this method, trustworthy results were obtained for the rock units.Sun, 31 Mar 2019 19:30:00 +0100Risk management in urban tunnels using methods of game theory and multi-criteria decision-making
http://jme.shahroodut.ac.ir/article_1391_0.html
In general, underground spaces are associated with high risks because of their high uncertainty in geotechnical environments. Since most accidents and incidents in these structures are often associated with uncertainty, the development of risk analysis and management methods and prevention of accidents are essential. A deeper recognition of the factors affecting the implementation process can pave the way for this purpose. Risk rating of projects is a key part of the risk assessment stage in the risk management process of each project. Various multi-criteria decision-making methods, as quantitative approaches, are used to allow them to be used in the risk rating issue of each project. In this work, a new model is provided for risk management of Mashhad Urban Railway Line 3 using the game theory and multi-criteria decision-making methods. Based on the answers of the specialists and experts to the prepared questionnaires, various risk groups identified using the TOPSIS and AHP multi-criteria decision-making methods are ranked. Accordingly, the group of economic risks, as the most important risk and social risk group, is ranked as the least significant in both methods. In the following, the appropriate response to the main risks of the ratings is proposed based on the modeling of the game theory, and ranked in terms of importance. Also the worst risk scenario in the project is identified, and the appropriate responses for this state are also expressed in order of importance. The results obtained indicate that the risk of financing problems is the most significant risk, and other risks are ranked in terms of importance in the next ranks. Additionally, the use of new financing methods at times of credit scarcity and project financial problems is also considered as the most important response to the risk in this project.Fri, 22 Feb 2019 20:30:00 +0100Automatic estimation of regularization parameter by active constraint balancing method for 3D ...
http://jme.shahroodut.ac.ir/article_1428_165.html
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.Sun, 31 Mar 2019 19:30:00 +0100A programming method to estimate proximate parameters of coal beds from well-logging data using ...
http://jme.shahroodut.ac.ir/article_1433_0.html
This paper presents an innovative solution for estimating the proximate parameters of coal beds from the well-logs. To implement the solution, the C# programming language was used. The data from four exploratory boreholes was used in a case study to express the method and determine its accuracy. Then two boreholes were selected as the reference, namely the boreholes with available well-logging results and the proximate analysis data. The values of three well-logs were selected to be implemented in a system of equations that was solved, and the effect of each well-log on the estimated values of the proximate parameter was expressed as a coefficient called the effect factor. The coefficients were incorporated in an empirical relationship between the parameter and the three well-logs. To calculate the coefficients used for the most accurate estimation, a total of 22960 systems of equations were defined and solved for every three logs. As there was the possibility of 560 combinations for selecting three logs from all the available 16 logs, the three equation-three variable systems were solved more than 12 million times. The programming methods were utilized to achieve the final results. The results of each system were tested for deviation of the estimated values of volatile matter, ash, and moisture, and the coefficients of the lowest deviation were accepted to be applied in the relation. Implementing this method for estimating the volatile matter resulted in an average deviation of 10.5%. The corresponding estimated values of the ash and moisture contents were 22% and 14%, respectively.Sat, 30 Mar 2019 19:30:00 +0100Changing sag mill liners type from Hi-Low to Hi-Hi at Sarcheshmeh copper complex based on ...
http://jme.shahroodut.ac.ir/article_1401_165.html
Liner design has become an increasingly more important tool for the AG/SAG mill performance optimization. The Sarcheshmeh copper complex concentration plant uses a SAG mill lined with 48 rows of Hi-Low type liners. Because of breakage of Low type liners and cold welding, the liner replacement task of Low with new Hi type liners has become very difficult and time-consuming. With the objective of finding a new design for liners, numerical (3D DEM; discrete element method) simulation and physical modelling in a laboratory mill were used. It was found that changing the liner type from Hi-Low to Hi-Hi could provide an appropriate charge trajectory. The new Hi-Hi type shell liners were designed, manufactured, and installed. With the new liners, the number of broken liners over liner life reduced from 6 to 0 piece, the total changing time for one liner decreased from 21 to 16 minutes, and no cold welding of shell liners was observed. Comparison of the feed rate before and after installation of the new liners for a period of liner life showed an increase from 750 to 850 t/h, which was indicative of a higher flexibility of the mill in encountering ore hardness variations.Sun, 31 Mar 2019 19:30:00 +0100Ant Colony Algorithm as a High-Performance Method in Resource Estimation Using LVA Field, Case ...
http://jme.shahroodut.ac.ir/article_1445_0.html
Kriging is an advanced geostatistical procedure that generates an estimated surface or 3D model from a scattered set of points. This method can be used for estimating resources using a grid of sampled boreholes. However, conventional ordinary kriging is unable to take locally varying anisotropy into account. A numerical approach has been presented that generates a locally varying anisotropy (LVA) field by calculating the anisotropy parameters (direction and magnitude) in each cell of the estimation grid. After converting the shortest anisotropic distances to Euclidean distances in the grid, they can be used in kriging equations. Ant colony optimization (ACO) algorithm is a nature-inspired metaheuristic method that was applied to extract image features. A program was developed based on the ACO algorithm in which the ants choose their paths based on LVA parameters and act as a moving average window on a primary interpolated grid element map. If initial parameters of the ACO algorithm are properly set, the ants would be able to simulate the mineralization paths along continuities. In this research, Choghart iron ore deposit with 2,447 composite samples taken from boreholes, studied with LVA-kriging and ACO algorithm. The outputs were cross-validated with 111,131 blast hole samples and Jenson-Shannon (JS) criteria. The results showed that ACO algorithm outperformed both LVA- and conventional kriging (with correlation coefficient value of 0.65 and JS value of 0.025). Setting the parameters by trial and error is the main problem of the ACO algorithm.Wed, 24 Apr 2019 19:30:00 +0100Mechanical activation of phosphate concentrates to enhance dissolution efficiency of rare earth ...
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The Esfordi phosphate concentrate mainly contains fluorapatite, monazite, and xenotime as rare earth element (REE) minerals, accounting for 1.5% of rare earth metals. The monazite and xenotime minerals are refractory and their decomposition is only possible at high temperatures. Thus mechanical activation was used in the present work for this purpose. After 90 minutes of mechanical activation, the X-ray amorphization phase and the maximum BET surface area were increased to 93.4% and 8.4 m2/g, respectively. The Williamson-Hall plot indicated that the crystallite size was decreased and the lattice strain was increased as a function of the milling intensity. A volume-weighted crystallite size of 64 nm and a lattice strain of 0.9% were achieved from the mechanically activated sample for 90 minutes. The leaching efficiency of REEs with 32% nitric acid at 85 °C was increased from 25% for the initial sample to about 95% for the activated samples. The first stage reaction rate constants for La, Nd, and Ce were increased from 8 × 10-7, 9 × 10-7,and 6 × 10-7 for the initial sample to 1.3 × 10-3, 9 × 10-4, and 7 × 10-4 for the mechanically activated samples at 60 °C, respectively. Also the apparent activation energy for La, Nd, and Ce for the initial sample was found to be about 210, 231, and 229 kJ/mol, which were decreased to 120, 91, and 80 kJ/mol, respectively, after 20 minutes of mechanical activation in an argon atmosphere. The results obtained suggested mechanical activation as an appropriate pre-treatment method for dissolution of REEs from phosphate concentrates containing refractory REE minerals at a lower cost and a higher recovery rate.Sun, 31 Mar 2019 19:30:00 +0100Geostatistical estimation to delineate oxide and sulfide zones using geophysical data; a case ...
http://jme.shahroodut.ac.ir/article_1432_0.html
Delineation of oxide and sulfide zones in mineral deposits, especially in gold deposits, is one of the most essential steps in an exploration project that has been traditionally carried out using the drilling results. Since in most mineral exploration projects there is a limited drilling dataset, application of geophysical data can reduce the error in delineation of the sulfide and oxide zones. For this purpose, we produced a 3D model of Induced Polarization (IP) data using the ordinary kriging technique. Then the modelling results were compared with the drilling data. The results obtained showed that the 3D geophysical models would properly delineate the sulfide and oxides zones. This work presents a new application of the IP results for separation of these zones. In addition, the conducted variography in this work suggests reducing the profile spacing of dipole-dipole IP arrays down to 25 m. This would properly enrich the integration of geophysical and geological results in the modelling of gold deposits.Mon, 18 Mar 2019 20:30:00 +0100Impact of gasoline contamination on mechanical behavior of sandy clay soil
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Oil leakage causes soil contamination and induces changes in the physical and mechanical properties of soils. In areas contaminated with oil products such as gasoline, the implementation of civilian operations requires determination and prediction of soil behavior in the existing conditions. In this research work, the effect of oil contamination by gasoline obtained from the National Oil Company in the Yazd Province is considered to investigate the effect of contaminants on the geotechnical properties of fine-grained sand. In order to examine the geotechnical characteristics of contaminated soil, compaction, undrained triaxial (CU), and consolidation tests are conducted. The tests are carried out on the samples of clean soil and contaminated soil with 1, 3, and 5% gasoline. The results obtained show that added gasoline reduces the optimum moisture content and increases the maximum dry density. In addition, based on the results of the triaxial test, the amount of friction angle and the cohesion of clay sand decrease by 21% and 14% with increasing contamination up to 5%, respectively, compared to the clean soil sample. Furthermore, adding gasoline significantly increases the compressibility and compression index.Sun, 31 Mar 2019 19:30:00 +0100Potential of OM of Iranian peat and swamp and characterization of physico-chemical properties ...
http://jme.shahroodut.ac.ir/article_1431_165.html
The objective of this work was to investigate the potential of three different kinds of Iranian peat and swamp soils as sources of organic matter (OM) in the Golestan Province, Northern Iran. Comparison of the peats was done in terms of the degree of humification on the von Post scale. Moreover, the X-ray fluorescence, X-Ray Diffractometry, and Fourier transform infra-red (FT-IR) techniques were used to investigate their mineralogical and geochemical properties. Also a method was tested for the sequential extraction of OM from Suteh peat, in which the following organic solvents were utilised in sequence: (I) ethyl ether, (II) ethanol, (III) 1,4-dioxane, and (IV) n-hexane; each extract was analysed by FT-IR spectroscopy, and the residue was used in the next phase. The results obtained indicated that OMOM extracted during each step was different; nevertheless, some spectral features such as those attributable to lignin, carbohydrate, phenol, wax, and fats were common to all phases. Major absorbance spectra were related to specific extraction steps, namely polysaccharide, proteins, alkyne, humic acids, esters, aldehydes, and cellulose.Sun, 31 Mar 2019 19:30:00 +0100Using an experimental drilling simulator to study operational parameters in drilled-cutting ...
http://jme.shahroodut.ac.ir/article_1379_165.html
Inadequate hole cleaning can lead to many problems in horizontal and directional wells. In this work, we tried to investigate the cutting transport phenomenon by an experimental directional drilling simulator, considering the differences between the operational and experimental conditions. The inclination, fluid type (water, foam, viscous, and dense), rotary speed (0 and 110 rpm), nozzle bit size (4, 6, and 8 mm), and stabilizer location (8 and 95 cm from the bit) were included in the tests as the main parameters. It could be concluded that the nozzle size and the stabilizer position influenced the hole cleaning time. In vertical wells, by decreasing the nozzle size from 8 mm to 4 mm, the hole cleaning time was increased. The presence of stabilizer reduced the cleaning time, and optimizing the stabilizer position reduced the probability of cutting bed formation in all inclinations. Finally, a third polynomial equation was fitted between the dimensionless mass and the dimensionless cleaning time.Sun, 31 Mar 2019 19:30:00 +0100Evaluation of effects of operating parameters on combustible material recovery in coking coal ...
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In this research work, the effects of flotation parameters on coking coal flotation combustible material recovery (CMR) were studied by the artificial neural networks (ANNs) method. The input parameters of the network were the pulp solid weight content, pH, collector dosage, frother dosage, conditioning time, flotation retention time, feed ash content, and rotor rotation speed. In order to select the most efficient model for this work, the outputs of different models were compared with each other. A five-layer ANN was found to be optimum with the architecture of 8, 15, 10, and 5 neurons in the input layer, and the first hidden, second hidden, and third hidden layers, respectively, as well one neurons in the output layer. In this work, the training, testing, validating, and data square correlation coefficients (R2) were achieved to be 0.995, 0.999, 0.999, and 0.998, respectively. The sensitivity analysis showed that the rotor speed and the solid weight content had the highest and lowest effects on CMR, respectively. It was verified that the predicted ANN values coincided very well with the experimental results.Sun, 31 Mar 2019 19:30:00 +0100Use of density tracers in evaluating performance of Tri-Flo circuits Case study: Tabas (Iran) ...
http://jme.shahroodut.ac.ir/article_1382_165.html
In the Tabas coal preparation plant (SE Iran), -50 + 6 mm raw coal was treated in a 700 mm two-stage two-density Tri-Flo dynamic dense medium separator. In order to study the circuit performance and to evaluate the separator efficiency, 32 mm cubic density tracers were used in the range of 1.28-2.1 g/cm3 and under different operational conditions. The performance of Tri-Flo was evaluated in a rapid manner, and an acceptable partitioning performance was observed under the process regime; the misplacements were in the normal range. Contrary to the dense media cyclones where the cut point shift (CPS) is usually positive, the results of this work showed that CPS was negative in both stages of the Tri-Flo separator. The Ecart probable value for the first stage of the separator (Epf = 0.023) was rather greater than the second stage (Eps = 0.018), representing the higher performance achieved in the second stage. In addition, the Tri-Flo operational parameters were found to be adjustable on the basis of raw coal specifications in order to reach good metallurgical results. Therefore, the optimum operational feed capacities of the Tri-Flo separator were determined to be in the range of 80-140 t/h, depending on the type of raw coal.Sun, 31 Mar 2019 19:30:00 +0100Hydraulic fracture propagation: analytical solutions versus Lattice simulations
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In this work, we used a grain-based numerical model based on the concept of lattice. The modelling was done to simulate the lab experiments carried out on the mortar samples. Also the analytical solutions corresponding to the viscosity-dominated regime were used to estimate the fracture length and width, and the results obtained were compared with the numerical simulations. As the analytical solutions are proposed for a penny-shaped fracture with no presence of any obstacle such as natural interfaces, in this work, we presented the results of lattice simulations for hydraulic fracturing in the cement sample, similar to the lab, but with no natural fractures, and compared the results obtained with analytical solutions. The results indicated that in the case of a continuous medium, the analytical solutions may present a reasonable estimation of the fracture geometry. Also the viscosity-dominated leak-off model showed a better match between the analytical solutions and the numerical simulation results, confirmed by observing fluid loss into the sample in the lab post-experiment. In the case of assuming leak-off, the results indicated that the fracture width and length would reduce. However, it should be noted that in real cases, rock formations exhibit fractures and inhomogeneity at different scales so that the applications of the analytical solutions are limited.Sun, 31 Mar 2019 19:30:00 +0100Effect of large blocks position on stability analysis of block-in-matrix slopes
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Bimrocks are complex geomaterials that are defined as mixtures of rocks composed of geotechnically significant blocks within a matrix of finer texture. Bimslopes are made from bimrocks and are usually seen in weathered and shallow environments. Some characteristics of blocks affecting the strength of bimrocks include VBP (Volumetric Block Proportion), orientation, and arrangement, which have important roles in the stability of bimslopes. Previous studies show that bimrocks usually have a specific block size distribution, and for a bimslope with height of “H”, the size of blocks is changed from 0.05H to 0.75H. In this paper, the influence of large blocks position on bimslope stability was investigated by the physical and numerical models. The blocks that had a dimension larger than 0.5H were considered as “large blocks”. In this work, first, thirty physical models were created and tested using a titling table machine. These models have a specific block size distribution and VBP with ellipsoidal blocks. The main variable of the models is large blocks position, where three categories including lower part of bimslope, upper part of bimslope, and sporadic state are considered. Based on the results of physical trials, thirty numerical models at the laboratory scale were generated using the finite element method. After comparing the physical and numerical models, which showed a good accordance, the numerical models were developed to the natural scale. The theoretical bimslopes investigated in this work showed that the position of large blocks had a significant influence on the stability of bimslopes.Sun, 31 Mar 2019 19:30:00 +0100Study of convergence confinement method curves considering pore-pressure effect
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The design of underground spaces is mainly carried out using empirical, analytical, and numerical methods. The convergence confinement method (CCM) is an analytical technique that is widely utilized in analyzing the stability of underground spaces. However, the main challenge in the stability analysis is the selection of an accurate constitutive model for rock mass, and particularly, its post-failure behavior. The existence of water plays a significant role in the stability analysis, whereas this effect is not usually considered in the CCM method. In this research work, a circular tunnel in a saturated medium is modelled and compared with its dry condition. Two types of constitutive models namely elastic perfectly plastic (EPP) and strain softening (SS) are used and compared in order to investigate the effect of water and post-failure behavior on the stability of tunnels. With this respect, the codes are written and incorporated in the constitutive models and various analyses are carried out. The results achieved from the analyses show that the elastic reaction of ground in the presence of water in both constitutive models are the same and that the ground reaction curves (GRCs) and longitudinal deformation profiles (LDPs) are similar. However, the trend of GRC is different in the case where the rock failure occurs and the face of the tunnel goes beyond 0.5D. According to the results obtained, the maximum displacement in a saturated medium with different K values for the SS model is more than that for the EPP model.Sun, 31 Mar 2019 19:30:00 +0100Using a combination of genetic algorithm and particle swarm optimization algorithm for GEMTIP ...
http://jme.shahroodut.ac.ir/article_1388_165.html
The generalized effective-medium theory of induced polarization (GEMTIP) is a newly developed relaxation model that incorporates the petro-physical and structural characteristics of polarizable rocks in the grain/porous scale to model their complex resistivity/conductivity spectra. The inversion of the GEMTIP relaxation model parameter from spectral-induced polarization data is a challenging issue because of the highly non-linear dependency of the observed data on the model parameter and non-uniqueness of the problem. To solve these problems as well as scape the local minima of the highly complicated cost function, the genetic algorithm (GA) can be applied but it has proven to be time-intensive computationally. However, this drawback can be resolved by incorporating a faster algorithm, e.g. particle swarm optimization (PSO). The aim of this work is to investigate whether recovering the model parameter of the ellipsoidal GEMTIP model from SIP data using the combined GA and PSO algorithms is possible. To achieve this aim, we set the best calculated individuals using GA as the search space of PSO, and then the best location achieved by PSO in each iteration is assigned as the updated model parameters. The results of our research work reveal that the model parameters can effectively be recovered using the approach proposed in this paper but the time constant of a noisy data that arises from the adverse dependency of this parameter on the ellipticity of a polarizable grain. Moreover, the execution time of the ellipsoidal GEMTIP modeling of complex resistivity data can be significantly improved using the proposed algorithm.Sun, 31 Mar 2019 19:30:00 +0100Bayesian prediction of rotational torque to operate horizontal drilling
http://jme.shahroodut.ac.ir/article_1389_165.html
Horizontal directional drilling is usually used in drilling engineering. In a variety of conditions, it is necessary to predict the torque required for performing the drilling operation. Nevertheless, there is presently not a convenient method available to accomplish this task. In order to overcome this difficulty, the current work aims at predicting the required rotational torque (RT) to operate horizontal directional drilling on the 7 effective parameters including the length of drill string in the borehole (L), axial force on the cutter/bit (P), total angular change of the borehole (KL), radius for the ith reaming operation (Di), rotational speed (rotation per minute) of the bit (N), mud flow rate (W), and mud viscosity (V). In this paper, we propose an approach based on the model selection criteria such as various statistical performance indices mean squared error (MSE), variance account for (VAF), root mean squared error (RMSE), squared correlation coefficient (R2), and mean absolute percentage error (MAPE) to select the most appropriate model among a set of 20 candidate ones to estimate RT, given a set of observed data. Once the most appropriate model is selected, a Bayesian framework is employed to develop the predictive distributions of RT, and to update them with new project-specific data that significantly reduce the associated predictive uncertainty. Overall, the results obtained indicate that the proposed RT model possesses a satisfactory predictive performance.Sun, 31 Mar 2019 19:30:00 +0100Metal(loid) uptake of Sonchus oleraceus grown around Cheshmeh-Konan copper deposit, NW Iran
http://jme.shahroodut.ac.ir/article_1390_165.html
Heavy metal(loid) contamination in the environment of mining areas has become an important problem. Cheshemeh-Konan is one of the main copper deposits in NW Iran that is currently abandoned. In the present work, the intensity of some metal(loid) pollutions in the soil of the mining area was assessed using three reliable indices. In addition, the potential of Sonchus oleraceus L., as the dominant plant grown in the area, in the uptake of some metal(loid)s from the soil was evaluated. The plant and soil samples were collected from the mining area and analyzed by inductively coupled plasma-mass spectrometry (ICP-MS). The results obtained revealed that the soil of the studied mining area was considerably contaminated by As (CF = 3.1), Cr (CF = 3.8), and Ni (CF = 4.07). It was confirmed that S. oleraceus had a good ability to accumulate Cd (0.74 mg/kg), Mo (0.67 mg/kg), Sr (285.80 mg/kg), Sn (161.10 mg/kg), and Sc (30.35 mg/kg) when mean concentrations of these metals in the soil were 0.14, 0.12, 161.05, 1.94, and 17.9 mg/kg, respectively. The plant biological absorption coefficient for these 5 elements was more than 1. The correlations between the Mo and Sr contents in the soil and plant were significantly positive. According to the results obtained, the present work provides some geochemical findings about the substrate, and leads to the increasing information about the relationship between the element concentrations in the plants and different soils.Sun, 31 Mar 2019 19:30:00 +0100Efficiency of seismic wave velocity and electrical resistivity in estimation of limestone rock ...
http://jme.shahroodut.ac.ir/article_1429_165.html
In this research, the relationship between P-wave velocity (Vp) and Electrical Resistivity (ER) parameters with rock mass quality indices is investigated; parameters such as rock mass quality classification (Q) and modified system for sedimentary rocks, known as Qsrm. For making predictive models, about 1200 data-sets extracted from sections drilled in Seymareh and Karun 2 Dam Sites (SDS and KDS) in Asmari Formation, south-west Iran. Statistical and fuzzy methods used to study the relationships between physical characteristics and rock mass quality. Since in Qsrm classification, the existence of cavities, layering and rock texture is considered in addition to the parameters considered in the Q classification; therefore, it provides a better description of rock mass and is closely related with Vp and ER parameters. The obtained equations for predicting Q and Qsrm showed the determination coefficients (R2) 0.48 and 0.67, respectively, and the coefficient of determination 0.86 for Qsrm calculated from the fuzzy model. Finally, Mean Absolute Deviation (MAD), Variance Accounted For (VAF) and Root Mean Square Error (RMSE) used to check the prediction performance of statistical and fuzzy methods. The results of the calculated errors also showed that fuzzy models are interesting because they have good accuracy for predicting Qsrm. In addition, by increasing the degree of karstifiction, the efficiency of the geophysical method for estimate of Q decreases rapidly, this is due to ignoring the cavities in these categories.Sun, 31 Mar 2019 19:30:00 +0100Performance evaluation of gang saw using hybrid ANFIS-DE and hybrid ANFIS-PSO algorithms
http://jme.shahroodut.ac.ir/article_1152_165.html
One of the most significant and effective criteria in the process of cutting dimensional rocks using the gang saw is the maximum energy consumption rate of the machine, and its accurate prediction and estimation can help designers and owners of this industry to achieve an optimal and economic process. In the present research work, it is attempted to study and provide models for predicting the maximum energy consumption of the gang saw during the process of soft dimensional rocks with the help of an intelligent optimization model such as random non-linear techniques, i.e. the Hybrid ANFIS-DE and Hybrid ANFIS-PSO algorithms based upon 4 physical and mechanical parameters including uniaxial compressive strength, Mohs hardness, Schimazek’s F-abrasiveness factors, Young modulus, and an operational characteristic of the machine, i.e. production rate. During this research work, 120 samples are tested on 12 carbonate rocks. The maximum energy consumption of the cutting machine during this work is measured and used as a modeling output for evaluating the performance of cutting machine. Also meta-heuristic algorithms including DE and PSO algorithms are used for training the Adaptive Neural Fuzzy Inference System (ANFIS). In addition, the PSO algorithm has a higher ability in terms of model output and performance indices and has a superiority over the differential evolution algorithm. Furthermore, comparison between the measured datasets with the ANFIS-DE and ANFIS-PSO models indicate the accuracy and ability of the ANFIS-PSO model in predicting the performance of gang saw considering the machine’s properties and the cut rock.Sun, 31 Mar 2019 19:30:00 +0100