University of TehranInternational Journal of Mining and Geo-Engineering2345-693055120210601Application of Artificial Neural Network for Stability Analysis of Undercut Slopes167713210.22059/ijmge.2020.292606.594832ENHassanSarfarazSchool of Mining Engineering, College of Engineering, University of Tehran,Tehran, Iran0000-0002-1100-6921Mohammad HosseinKhosraviSchool of Mining Engineering, College of Engineering, University of Tehran,Tehran, Iran0000-0002-7600-5786ThirapongPipatpongsaDepartment of Urban Management, Kyoto University, JapanHassanBakhshandeh AmniehSchool of Mining Engineering, College of Engineering, University of Tehran,Tehran, Iran0000-0003-4075-0589Journal Article20191116One of the significant tasks in undercut slopes is determining the maximum stable undercut span. According to the arching effect theory, undercut excavations cause the weight of the slope to be transmitted to the adjacent stable regions of the slope, which will increase the stability of the slope. In this research, determining the maximum width of undercut slopes was examined through numerical modeling in the FLAC3D software. For this purpose, a series of undercut slope numerical models, with various slope angles, horizontal acceleration coefficients, and counterweight balance widths was conducted, and the results were validated using the corresponding experimental test results. The effect of each parameter on the maximum stable undercut span was investigated with an artificial neural network, where a multi-layer perceptron (MLP) model was performed. The results showed good accuracy of the proposed MLP model in the prediction of the maximum stable undercut span. In addition, a sensitivity analysis demonstrated that the dip angle and horizontal acceleration coefficient were the most and least effective input variables on the maximum stable undercut span, respectively.University of TehranInternational Journal of Mining and Geo-Engineering2345-693055120210601Crude oil Effects on Some Engineering Properties of Sandy Alluvial Soil7107713110.22059/ijmge.2020.283051.594815ENIbrahim AdewuyiOyediranDepartment of Geology, Faculty of Science, University of Ibadan, Ibadan, Nigeria0000-0002-4100-3393Nchewi IdebaEnyaDepartment of Geology, Faculty of Science, University of Ibadan, Ibadan, Nigeria0000-0002-0847-1777Journal Article20190608<span lang="EN-GB">Sandy alluvial soils contaminated with crude oil were investigated with a view to understanding the effects of crude oil contamination on their engineering properties. Bulk samples of alluvial soils compacted in layers were admixed thoroughly with 10% by volume of the contaminant and were cured for 63 days under room temperature in the laboratory and outside in the open to simulate field conditions. Mineralogical and chemical compositions of soils were obtained using X-ray diffraction and X-ray fluorescence analyses, and specific gravity, hydraulic conductivity, and compaction tests were conducted on the soils before and after contamination. Results show that the soil is silica-rich with SiO<sub>2 </sub>content of 96.24g/g. This is corroborated by the high quartz content (96.62%) observed from the mineralogical composition with minor amounts of kaolinite (6.04%), and trace amounts of haematite (0.02%). The addition of crude oil resulted in an increase in maximum dry density (MDD) with a corresponding decrease in hydraulic conductivity, optimum moisture content (OMC), and specific gravity for both laboratory and outside cured samples. Hence, crude oil contamination can be said to modify the engineering properties of sandy soils, and the environment of samples’ emplacement also contributed to the alteration pattern observed.</span>University of TehranInternational Journal of Mining and Geo-Engineering2345-693055120210601Sustainable Development Assessment in Underground Coal mining by Developing a Novel Index11177844110.22059/ijmge.2020.293603.594834ENRaziyeNorouzi MasirFaculty of Mining Engineering, Petroleum and Geophysics, Shahrood University of Technology, Shahrood, Iran0000-0001-8646-7717MohammadAtaeiFaculty of Mining Engineering, Petroleum and Geophysics, Shahrood University of Technology, Shahrood, Iran0000-0002-7016-8170RezaKhalo KakaeiFaculty of Mining Engineering, Petroleum and Geophysics, Shahrood University of Technology, Shahrood, IranSadjadMohammadiFaculty of Mining Engineering, Petroleum and Geophysics, Shahrood University of Technology, Shahrood, IranJournal Article20191206<span lang="EN-GB">A novel index is presented in this paper to evaluate sustainable development in underground coal mining. Eleven parameters were chosen as impacting factors that define three aspects of sustainable development, including environmental, economic, and social. Fuzzy Delphi Analytical Hierarchy Process (FDAHP) was used to develop a new rating system in the form of a classification system. Subsequently, a sustainable development index (SDi) was defined as a simple summation of ratings for all parameters to classify the sustainability level of underground coal mining qualitatively. Applicability of the new index was examined through applying it to a case study, and the results were compared with a benchmark model. </span>The results indicate that SDi possesses a higher performance in sustainable development evaluation in the actual case when compared to common models. This performance is because it is developed for underground coal mining, especially in a scientific manner that<span lang="EN-GB"> considers three aspects of sustainable development together.</span>University of TehranInternational Journal of Mining and Geo-Engineering2345-693055120210601A hybrid-based clustering algorithm for targeting porphyry copper mineralization at Chahargonbad district in SE Iran19287844210.22059/ijmge.2020.295510.594837ENHosseinRahimiSchool of Mining Engineering, College of Engineering, University of Tehran, Tehran, IranMaysamAbediSchool of Mining Engineering, College of Engineering, University of Tehran, Tehran, Iran0000-0002-5365-0694AbbasBahroudiSchool of Mining Engineering, College of Engineering, University of Tehran, Tehran, Iran0000-0002-2866-3813Mohammad JavadRezapourGeo-Exploration Targeting Lab (GET-Lab), School of Mining Engineering, College of Engineering, University of Tehran, Tehran, IranGholam-RezaElyasiGeo-Exploration Targeting Lab (GET-Lab), School of Mining Engineering, College of Engineering, University of Tehran, Tehran, IranSoheilaAslaniSchool of Mining Engineering, College of Engineering, University of Tehran, Tehran, Iran0000-0003-4755-0512Journal Article20200107This work presents a hybrid-based clustering approach for mineral potential mapping (MPM) of porphyry-type Cu mineralization at Kerman province in the SE of Iran. Whereby a multidisciplinary geospatial data set was processed and integrated in the Chahargonbad district. Data-driven prediction-area (P-A) plots were drawn for each evidence layer derived from geological, geochemical, geophysical and satellite imagery data. The P-A plots provide insight into the weight of evidence for synthesizing all geospatial layers. Out of many knowledge-driven methods which biasing from experts' opinions, index overlay and fuzzy operators were employed to find out an optimum Cu favorability map through calculating an efficiency index representing the performance of each MPM. A concentration-area (C-A) fractal model was implemented to separate the mineral favorability map into some populations to ensure correct determining the cluster numbers. Clusters number is a prerequisite which must be defined correctly to increase the performance of clustering analysis for generating reliable results in MPM. Such an appropriate number of clusters can be incorporated in running three prevalent groups of clustering methodologies as data-driven approaches in MPM. They are self-organizing map, fuzzy c-means, and k-means algorithms. One of the reasons for this tendency to consider a hybrid-based method is that it overcomes the shortcomings of the both methods (bias of experts’ opinions and unknown clusters number) in mineral favorability mapping. The unknown number of clusters was determined through a knowledge-driven method, and then it was passed to an unsupervised data-driven method, i.e. clustering algorithm. This hybrid method produces synthesized maps in close association with known porphyry-Cu mineralization in the Chahargonbad area.University of TehranInternational Journal of Mining and Geo-Engineering2345-693055120210601New reagents for controlling of H2O2 by metal sulfide and its effect in sulfide mineral floatation29327885010.22059/ijmge.2020.295911.594838ENAlirezaJavadiDepartment of Engineering, University of Kashan, 8731753153 Kashan, Iranhttps://orcid.org/0000-0001-6239-7160Journal Article20200114Our recent studies revealed that the ground sulphide minerals in contact with water generate H<sub>2</sub>O<sub>2</sub> but its effect on the oxidation of pulp components and hence in deteriorating the concentrate grade and recovery in flotation has not been explored yet. The use of Na<sub>2</sub>S reductant at the grinding stage is thought to control the deleterious effects of H<sub>2</sub>O<sub>2</sub> in the pulp liquid. Therefore, the effect of Na<sub>2</sub>S addition during grinding stage on the formation of H<sub>2</sub>O<sub>2</sub> and its influence on sulphide complex ore flotation was investigated. The results showed that the presence of Na<sub>2</sub>S increases the formation of H<sub>2</sub>O<sub>2</sub> but decreases the dissolved oxygen. An increase in Na<sub>2</sub>S dosage in grinding, the Pb grade and recovery in Cu-Pb concentrate is decreased while pyrite is depressed marginally better. These changes in flotation response of sulphides have been discussed and explained with the formation of H<sub>2</sub>O<sub>2</sub> quantitatively.University of TehranInternational Journal of Mining and Geo-Engineering2345-693055120210601Estimating groundwater inflow into Dorud-Khorramabad railway tunnel using analytical and numerical methods33418062110.22059/ijmge.2020.306044.594856ENEbrahimGhorbaniSchool of Mining Engineering, College of Engineering, University of Tehran, Tehran, Iran0000-0003-0735-4824SalehGhadernejadSchool of Mining Engineering, College of Engineering, University of Tehran, Tehran, Iran0000-0001-5262-7188DornaEmamiDepartment of Petroleum Engineering, Amirkabir University of Technology, Tehran, IranHamidrezaNejatiRock Mechanics Division, School of Engineering, Tarbiat Modares University, Tehran, IranJournal Article20200711The main objective of this study is to estimate the amount of groundwater inflow into Dorud-Khorramabad railway tunnel. To this end, in the first place, existing approaches of predicting groundwater inflow into tunnel was reviewed. According to the literature, up to now, a wide range of approaches have been proposed in order to predict the groundwater inflow into tunnel which can be classified into three distinct groups including, analytical solutions, empirical equations, and numerical modeling. Analytical solutions and empirical equations are mainly developed based on the given hypotheses and specific data sets, respectively, and should be applied in similar conditions. On the other hand, results obtained from numerical modeling are generally dependent on a wide range of parameters. Literature review revealed that one of the most effective parameters on the numerical modeling results is model extent, which controls not only final results but also numerical runtime. Hence, a sensitivity analysis is performed in order to investigate the effect of model extent on numerical results. The results demonstrated that increasing model extent decreases the groundwater inflow rate, and for a large model extent (greater than 1000), the amount of groundwater inflow tends to a constant value. In the second part, analytical solutions and finite element numerical modeling are applied for estimating the amount of groundwater inflow into Dorud–Khorramabad railway tunnel. The results indicate that the groundwater inflow into the tunnel, based on analytical methods, gives higher values than the numerical modeling. Assumptions and simplifications may justify this difference in analytical methods, accordingly, it can be inferred that if an appropriate model extent selected, the results of the numerical model based on the fact in the project can be more reliable.University of TehranInternational Journal of Mining and Geo-Engineering2345-693055120210601Ultimate Pit Limit Determination Using Flashlight Algorithm43488098810.22059/ijmge.2020.296120.594840ENBehshadJodeiriDepartment of Mining Engineering, Hamedan University of Technology (HUT), Hamedan, Iran0000-0002-2074-1004HesamDehghaniDepartment of Mining Engineering, Hamedan University of Technology (HUT), Hamedan, IranMohammadrezaSadeghiDepartment of Mining Engineering, Hamedan University of Technology (HUT), Hamedan, IranJournal Article20200118In this paper, the flashlight (FL) algorithm, which is categorized as a heuristic method, has been suggested to determine the ultimate pit limit (UPL). In order to apply the suggested algorithm and other common algorithms, such as the dynamic programming, the Korobov, and the floating cone, and to validate the capability of the proposed method, the ultimate pit limit was determined in a cross-section of the Korkora reserve, which is located in Kurdistan province, northwestern of Iran and consists of 3080 blocks. The comparison of the FL algorithm and other methods revealed that same as high accuracy dynamic programming methods, the proposed algorithm could find the optimum value, while the Korobov and the floating cone algorithms failed to determine the optimum limit.University of TehranInternational Journal of Mining and Geo-Engineering2345-693055120210601Detection of Effective Porosity and Permeability Zoning in an Iranian Oil Field Using Fractal Modeling49588098910.22059/ijmge.2019.278652.594795ENArdalanKianersiDepartment of Petroleum and Mining Engineering, South Tehran Branch, Islamic Azad University, Tehran, IranAhmadAdibDepartment of Petroleum and Mining Engineering, South Tehran Branch, Islamic Azad University, Tehran, IranPeymanAfzalDepartment of Petroleum and Mining Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran0000-0002-4833-8778Journal Article20190403Identification and delineation of different zones in oil fields are among the fundamental tasks in petroleum explorations. Fractal methods are useful tools for such purposes. The aim of this paper is to conduct a comparative study of Concentration-Area (C-A) and Number-Size (N-S) fractal models to separate effective porous and permeable zones based on core logging samples collected from one of the oilfields in southern Iran. However, permeability and porosity threshold values were calculated based on the C-A and N-S log-log plots. A comparison between the C-A and N-S fractal results showed that the C-A method is more compatible with reality, and it is capable of separating permeable and porous zones in this oilfield.University of TehranInternational Journal of Mining and Geo-Engineering2345-693055120210601Predicting slake durability of carbonate rocks using geomechanical properties (Case study: Durood-Khorramabad highway, Iran)59638124310.22059/ijmge.2019.271517.594770ENSomayeFarashiDepartment of Geology, Faculty of Sciences, Bu-Ali Sina University, Hamedan, Iran0000-0002-4182-9814Gholam RezaKhanlariDepartment of Geology, Faculty of Sciences, Bu-Ali Sina University, Hamedan, Iran0000-0001-9062-2054FatemeNaseriDepartment of Geology, Faculty of Sciences, Ferdowsi University of Mashhad, Mashhad, IranJournal Article20181214This study investigates the relationship between slake durability indices and geomechanical characteristics of five types of carbonate rocks situated in the west of Iran along the Doruod-Khorramabad highway. In this study, five types of limestone rocks were selected, including grey limestone (A), marly limestone (B, C, D), and sandy limestone (E). The geomechanical characteristics of the studied limestones were calculated based on the ISRM (1981) standard stimulations. Statistical approaches were executed to find the most influential geomechanical characteristics on slake durability indices and to find an appropriate slake durability cycle for interpreting rock behaviors. According to the simple regression analysis, the first and fourth cycles of slake durability can provide adequately good information for initial engineering/design works. Also, the correlation coefficients demonstrated nearly constant change after the fourth cycle. Geomechanical parameters, like Schmidt hammer and dry density, showed the highest correlation with the fourth slake durability cycle (R =0.98). On the other hand, uniaxial compressive strength revealed a poor correlation (R = 0.49) with this cycle. Apart from estimating the 4th durability cycle from geomechanical properties, it is possible to calculate the second to fourth cycles of slake durability using the results of the first durability cycle (R = 0.99–0.94). Consequently, a multivariate equation was developed based on water absorption, Schmidt hammer, effective porosity, and modulus of elasticity with R<sup>2</sup>=0.89 using the best subset regression method.University of TehranInternational Journal of Mining and Geo-Engineering2345-693055120210601Determining the relationship between shear wave velocity and physicomechanical properties of rocks65728124510.22059/ijmge.2019.275851.594782ENMohammadRezaeiDepartment of Mining Engineering, Faculty of Engineering, University of Kurdistan, Sanandaj, Iran0000-0002-0619-2846PouyaKoureh DavoodiDepartment of Mining Engineering, Faculty of Engineering, University of Kurdistan, Sanandaj, IranJournal Article20190211Thorough knowledge of physicomechanical properties of rocks is crucial during the primary and secondary stages of designing a rock engineering project. Laboratory examination of these properties requires high-quality rock specimens. However, preparing such high accuracy samples is a difficult, expensive, and time-consuming task, especially in weak and fractured rocks. Hence, indirect approaches seem an attractive research area for determining these properties. The main object of this study is to develop some empirical relations to determine different physical and mechanical properties of sedimentary and metamorphic rocks based on the shear wave velocity index. To do that, several schist, phyllite, and sandstone core samples were collected from the drilled boreholes in the Marivan Azad dam in western Iran. Then, the shear wave velocity and some physical and mechanical properties of rocks were measured in dry and saturated conditions. Subsequently, statistical analyses were conducted to develop shear wave velocity-based equations to determine different rock properties, including uniaxial compressive strength, modulus of elasticity, porosity, Poisson’s ratio, slake durability index, density, and water absorption. An equation with the maximum correlation coefficient was proposed as the optimum equation to determine each of the above rock properties. Finally, the results of the proposed empirical equations were compared with those of laboratory measurements. This comparison proved the proposed equations to have high accuracy for determining the physicomechanical properties of rocks and can be used in practical projects with similar geological conditions to save time and money.University of TehranInternational Journal of Mining and Geo-Engineering2345-693055120210601A simple but efficient non-linear method for 2D inversion of magnetic field data based on Ridge-Regression algorithm73798124610.22059/ijmge.2021.254258.594724ENAliMoradzadehSchool of Mining, College of Engineering, University of Tehran, Tehran, Iran0000-0001-9077-8278AliNejatiFaculty of Mining, Petroleum and Geophysics, Shahrood University of Technology, Shahrood, Iran0000-0002-1399-4556FuadMeysamiFaculty of Mining, Petroleum and Geophysics, Shahrood University of Technology, Shahrood, IranSaeedMojaradFaculty of Mining, Petroleum and Geophysics, Shahrood University of Technology, Shahrood, Iran0000-0001-8176-1933Journal Article20180310In geophysical exploration, inversion is carried out on the observed data to generate a geophysical model, approximating the subsurface geological structure. In the interpretation of magnetic data, the subsurface model parameters are found by a proper inversion scheme. Hence, it will be possible to obtain the entire parameters of any features (e.g. Dike) including depth, width, and location. In this paper, theoretical and field studies were carried out to interpret the total components of magnetic anomalies of dikes at the finite depth. Moreover, a least-squares approach was used for depth determination using anomalous magnetic data. Potential field data inversion can be achieved through many optimization techniques. This study, however, it is attempted to develop an efficient two-dimensional (2D) inversion algorithm based on the Ridge Regression routine. The developed method was programmed using Matlab software and applied to three sets of synthetic magnetic data containing different percent of random noise to find out how good the results are. It was found that the proposed 2D inversion method can produce an accurate subsurface model that precisely explains the synthetic data in each case of data inversion. Finally, the method was applied to the real total magnetic field (TMF) data of Moghan Sedimentary basin. In that case, the estimated sedimentary basement depths were found to be in good agreement with that of the seismic data acquired before.University of TehranInternational Journal of Mining and Geo-Engineering2345-693055120210601Identification of hidden mineralized and non-mineralized zones using spectral analysis of geochemical data81898126610.22059/ijmge.2020.273203.594776ENHosseinMahdiyanfarDepartment of Mining Engineering, University of Gonabad, Gonabad, Iran0000-0002-1977-0967MohammadFarzamianCentro de Geofísica, Universidade de Lisboa, Campo Grande Ed. C8, 1749-016 Lisbon, Portugal0000-0001-9549-7344Journal Article20190106Detection of dispersed and blind mineral deposits is an important aim in the mineral exploration. Detailed exploratory operations such as drilled boreholes which are performed for exploration of mineral deposits in the depth caused high cost and risk. In this research, a new scenario based on spectral analysis of geochemical data has been utilized for prediction of mineralized zones in the depth without any additional cost. The variations of mineralized elements from the surface to the depth are predicted and delineated by using this approach based on surface geochemical data. This proposed approach is the state-of the-art application of two-dimensional Fourier transformation (2DFT) for geochemical image processing. This approach which is named frequency coefficient method (FCM) has been defined based on the behavior of elements in the frequency domain. In this study, the FCM shows two Pb and Zn mineralized zones at the surface and moderate depth and a non-mineralized zone at the profound depth in Chichakloo Pb–Zn mineralization. Finally, the results of FCM have been validated and confirmed by the results of drilled boreholes and geophysical surveys.University of TehranInternational Journal of Mining and Geo-Engineering2345-693055120210601The Modeling and Optimization of Titanium Dioxide Extraction, Case study: The Slag Sample of Blast Furnace91968168210.22059/ijmge.2021.263730.594753ENMohsenFattahpourSchool of Mining, College of Engineering, University of Tehran, Tehran 1439957131, Iran0000-0001-6723-2066MohammadNoaparastSchool of Mining, College of Engineering, University of Tehran, Tehran 1439957131, Iran0000-0002-8688-4593ZiaedineShafaeiSchool of Mining, College of Engineering, University of Tehran, Tehran 1439957131, IranGolnazJozanikohanAssistant Professor, Ph.D in Mining Engineering (Mineral Exploration), School of Mining Engineering, College of Engineering, University of Tehran, Tehran, Iran0000-0002-5920-0424MehdiGharabaghiSchool of Mining, College of Engineering, University of Tehran, Tehran 1439957131, IranJournal Article20180812In this research work, the application of the Response Surface Methodology (RSM) and the Central Composite Design (CCD) techniques for modeling and optimization of some of the operating variables on the titanium dioxide extraction were studied. This study was performed, using sodium hydroxide roasting and sulfuric acid leaching. Four main parameters, i.e., leaching temperature, time, liquid to solid ratio, and the concentration of acid, were changed during the experiments. The two parameters of the stirring rate (250 rpm), and the feed size (d80= 106 micrometers) were considered to be constant. Based on the findings, several empirical equations were modeled for the titanium dioxide extraction with the above mentioned parameters. The empirical equations were then individually optimized by employing the quadratic programming to maximize the extraction within the experimental range. In conclusion, the optimum conditions were accordingly obtained at 85°C, 235 minutes, liquid to solid ratio of 15, and the acid concentration of 2.4 M, in which the maximum TiO2 extraction of 81.32% was achieved.