Abstract: This paper has used numeric and heuristic approaches to investigate the effect of jointed rock mass properties on the Minimum Required Caving Span (MRCS) in the block caving method. To do so, the effects of five parameters of jointed rock mass, namely joint set number, joint spacing, joint inclination angle, joint surface friction angle, and undercut depth on MRCS, were investigated using discrete element code. For this purpose, many numerical models were generated with various rock mass parameters. Moreover, Gene Expression Programming and Artificial Neural Networks were employed to create a heuristic model for MRCS. The model parameters were subjected to sensitivity analysis. All model input parameters showed sensitivity to the model. There are several effective parameters on MRCS, but joint dip and joint set numbers are the most important and the smallest.
Abstract: The Mineral Prospectivity Map (MPM) is a powerful tool for identifying target areas for the exploration of undiscovered mineral deposits. In this study, a knowledge-driven Index overlay technique was utilized to create the MPM on a regional scale. The complex distribution patterns of geological features associated with mineral deposits were mapped and correlations between these features and mineral deposits were revealed by integrating geological, geophysical, hydrothermal alteration, and fault density data layers. It was found that 23% of the study area was highly prospective, with 77% of the known porphyry copper occurrences located within this area. The normalized density was equal to 3.35, indicating a significant relationship between the known porphyry copper occurrences and their occupied area. The MPM also identified potential tracts outside the known mineralized areas that can be used for exploration and quantitative assessment of undiscovered resources. It is suggested that the MPM is a valuable tool for mineral exploration and could have significant implications for the mining industry.
Abstract: Malawi’s geology has not been mapped in detail and there is no detailed geological and structural assessment in relation to gold mineralization. Mangochi-Makanjira area in southern Malawi is endowed with abundant gold mineral resources but there is a scarcity of precise knowledge on the structures that control primary mineralization. This study used aeromagnetic data to provide a structural framework of the Makanjira area and delineated potential areas for further gold exploration. Many analytic approaches were applied to the aeromagnetic data, including reduction to the pole, Euler deconvolution, Tilt, and Vertical Derivatives filtering. Euler deconvolution was used to determine the depth of magnetic sources. Geophysical data interpretations identify the dominant linear trends present in the area to be faults, dykes and deep level basement shear zones as structures responsible for fluid flow and gold mineralization in the area. Gold in this area is structurally controlled by N-S structures that were derived during the Pan African orogeny and it is during in this event that the area got mineralized. These fractures and faults served as channel ways for hydrothermal solutions, resulting in the emplacement of gold mineralization within the fractures. Mineralization occurs from the surface and goes deep and ranges in depth from 0.5 km to 2.4 km. Exploration for gold should focus on these structures.
Abstract: The effective use of residual laterite soils is usually hindered because of their mineralogy and the high amount of fine contents present in them. This paper studied the potential improvement in the geotechnical and mineralogical properties of a fly ash-treated residual laterite collected from Southwest Nigeria. Some physical and geotechnical properties such as plasticity, compaction, unconfined compressive strength (UCS), and California Bearing ratio (CBR) of untreated and treated laterites were determined using ASTM standard methods. Stabilization was achieved by mixing the laterite with varying proportions (0, 3, 6, 9, 12, and 15% by mass of dry laterite) of fly ash. Mineralogical analysis of untreated and treated laterite was done using an X-ray diffractometer (XRD). The results showed a slight initial increase at low proportions of fly ash (at 3%) in the plasticity properties and a decrease (of up to 65%) afterward. The UCS and CBR of the treated laterite increased over 100% (UCS 110% and CBR 183% maximum) at 6% fly ash content. XRD analysis showed the formation of new minerals, predominantly portlandite, within the stabilized soils. This study confirmed using fly ash for the stabilization of residual laterite soils to be potentially used for road construction is viable.
Abstract: Magnetic data play a significant role in the interpretation of various geologic structures using depth estimation methods and edge detection filters. In this study, we applied methods based on directional derivatives such as tilt-depth (TD), signum transform (ST), source distance (SD) and classical Euler deconvolution (ED) to estimate the depth of the magnetic sources. Moreover, to enhance the edges of magnetic field anomalies, we utilize the total horizontal derivative (THD), analytical signal (AS), tilt angle (TA), theta map (TM), hyperbolic tilt angle (HTA), the tilt angle of horizontal derivative (TAHG), and logistic function of total horizontal gradient (LTHD). These algorithms are tested on a synthetic magnetic model with noise and free noise to understand their performance. Since the edge detection filters are sensitive to noise, we carry out an upward continuation (UC) filter before the reduction of data to magnetic the pole to reduce the noise effect. After comparing the efficiency of the approaches in estimating the depth and horizontal lateral boundaries, these methods were applied to the data surveyed from the Aji-Chai salt dome in East Azerbaijan Province, Iran. The results obtained by the depth determination methods were compared with the drilling report of Iran’s geological survey and three-dimensional classical Euler deconvolution method.
Abstract: Magnetic and gravity anomalies have spatially overlapping fingerprints from many buried sources that differ in shape, depth, density contrast, magnetization intensity, and direction. Geophysicists have developed a suite of image enhancement filter algorithms that accurately represent the geometry and detail of subsurface features. Edge enhancement filters are high-pass filters that emphasize potential field anomalies, horizontal lateral edges, and the horizontal location of buried sources, i.e., specific combinations of directional derivatives of gravity and magnetic fields. Lateral edge enhancement filters (e.g., THG, AS, TA, TM, LTHG, IL, and ILTHG) were investigated using Gaussian noise on synthetic magnetic and gravity field data. The results show that LTHG and IL perform better than the other procedures. The ILTHG filter defined with the logistic function does not have the required accuracy and capability to determine the lateral boundaries. In addition, the filters were examined using real gravity field data from the Western Carpathians area in Slovakia. The primary and secondary faults in the western and southern Tribeč Mountains and the secondary faults and geological formations in the Pohronský Inovec Mountains are recognizable in the LTHG and IL images. The results of the LTHG and IL maps will allow us to improve the qualitative interpretation of gravity anomalies in studying the structural and tectonic geology of the Slovak Tribeč and Pohronský Inovec Mountains.
Abstract: The different methods for the delineation of favorable areas for mineral exploration utilize exploration criteria in regard to targeted mineral deposits. The criteria are elicited according to conceptual model parameters of the targeted mineral deposits. The selection of indicator criteria, the evaluation of their comparative importance, and their integration are critical in mineral prospectivity modeling. In data-driven methods, indicator features are weighted using functions whereby the importance of certain indicator criteria may be ignored. In this paper, a data-driven method is described for recognizing and converting exploration criteria into quantitative coefficients representing favorability for the presence of the targeted mineral deposits. In this approach, all of the indicator features of the targeted mineral deposits are recognized and incorporated into the modeling procedure. The method is demonstrated for outlining favorable areas for Mississippi valley-type fluorite deposits in an area, north of Iran. The method is developed by studying and modeling the geological characteristics of known mineral occurrences. The degree of prediction ability of each exploration criterion is quantified as a recognition coefficient, which can be used as a weight attributed to the criterion in mineral exploration targeting to outline favorable areas.
Abstract: This research case study presents a fuzzy ordered weighted averaging (FOWA) method for mineral prospectivity/potential mapping (MPM) at Chahargonbad district in SE Iran, a system whereby new areas of high prospectivity for porphyry Cu mineralization are identified. The ultimate goal of this research is to find the complex and hidden relationships between the evidence layers and known ore occurrences using a comprehensive consideration of a multi-disciplinary geospatial data set. Hence, thirteen evidences are accurately derived from available databases, including geological, geochemical, geophysical, and remote sensing, and integrated through a FOWA multi-criteria decision-making approach to delineate favorable Cu-bearing zones. FOWA methodology uses a wide range of decision strategies to synthesize input geospatial evidences utilizing multiple values for an alpha parameter as the cornerstone of the algorithm that controls the experts' attitude toward the MPM risk. It is reflected through the generation of seven mineral potential maps to search the most suitable one(s). Considering a prediction-area plot for data-driven weight assignment of each evidence map, the hybrid FOWA outputs are searched for the most appropriate map in targeting notable Cu occurrences. The desired synthesized evidence map could indicate an ore prediction rate of 77%, where known Cu deposits were distributed at favorable zones occupying 23% of the whole district area.
Abstract: Based on magnetic susceptibility and density contrast models, the final purpose of analyzing potential field data is to estimate the parameters of the sought source, such as depth, structural index, horizontal location, and physical characteristics. Meanwhile, when conducting geophysical explorations, it is critical to ascertain the exact depth of the underground source as accurately as possible. In this study, the potential field is interpreted using the depth from extreme points “DEXP” automatic transformation technique, founded on the accurate processing of the local wavenumber at various scales and the extreme points of the DEXP field to extract the depth, horizontal position and structural index of the source. This highly stable method demonstrates low sensitivity to noise-contaminated data since it employs an upward continuation filter and a potential field derivative operator. In addition, the findings are more dependable than those of alternative techniques. Furthermore, the procedure is entirely automatic and does not require any basic information from the data collection area. In other words, DEXP can be considered a fast imaging method. Since multiscale methods are less reliant on the magnetic induction field, nowadays, they are utilized more frequently in magnetic field computations. At the beginning of this research, synthetic scenarios are simulated, and then the depth extension of the postulated models was demonstrated by implementing the DEXP technique to the synthetic gravity and magnetic data. Subsequently, this method has been implemented on data from the Ghareh-Aghaj potash exploratory area in Zanjan Province, North of Iran. By summarizing this method's results, it can be seen that the potash mass exhibits a minimal transverse expansion and has extended more in the depth dimension. Compared to the findings obtained via exploratory boreholes, these findings demonstrate a level of agreement that can be considered satisfactory.
Abstract: One of the operating costs of exploiting underground mines is related to ventilation operations. The development of the underground network during the mine life and new excavations will cause a redesign of the ventilation plan over and over again. Excavating the waste pass in the Anguran underground lead and zinc mine and developing new access for the transfer of cement filling requirements from the surface will make it necessary to review the ventilation network plan. The present research aims to analyze the efficiency of the mine ventilation network through simulation with considering the effects of waste pass based on the consequences of natural ventilation. For this purpose, based on the estimation of the needs of the underground development plan, the required airflow intensity of this mine was 57.5 m3/sec and the air pressure drop was estimated to be 116.79 millimeters of the water column. The underground mine network was imported into the software by using Ventsim software, and the simulation and specifications of each branch have also been entered. Then, different positions of the main fan were examined according to the location of mine opening and airways the advantage of mine natural ventilation in different seasons, and finally, the most suitable design for ventilation was presented. Modeling natural ventilation was investigated in two parts before waste/ore pass excavation and after excavation in Ventsim software at temperature, pressure, and different humidity. According to the simulation, it was found that the minimum natural ventilation flow to the mining network is 14 m3/sec in winter, its use saves 16.02 Kwh of energy.
Abstract: The massive deposit of medium-grained, white-coloured sandstone of about 20 m thick, located immediately above the coal seam in Quarry No. 2, resulted in lesser yield due to lower powder factor (m3/kg) and over-sized boulder formations specifically from the stemming zones at Chotia Opencast Coal Mine of M/s Prakash Industries Limited, which was operating at a depth of about 30 to 40 m with an average bench height of 5.5 m. The criticality of the problem led to the rectification of the blast design parameters through the incorporation of pilot holes and pocket charges; decked charges; air-decking; evolution of static energy distributions and fragment data analysis for establishing optimized design patterns with available machinery. Several test blasts added with on-site testing of explosive quality, rebound hardness tests of overlying strata, and rearrangements of firing patterns through surface delay connections were considered for adopting the best-suitable blast pattern for the mine. Generalized and perceptible inferences were made so as to apply the results in other mines with similar kinds of problems.
Abstract: Blasting operation is one of the technologies used for breaking rock mass and reducing the rock mass into smaller sizes to improve transportation and further particle separation. The improvement of blast fragmentation supports the maximization of mining operation and productivity. Soft computing and regression model has been developed in this study to optimize small-scale dolomite blast operations in Akoko Edo, Nigeria. WipFrag software was used to analyze the results of 35 blasting rounds. As independent variables, one uncontrollable parameter and five blast controllable parameters were chosen to predict blast particle sizes using four mathematically motivated soft computing model approaches. The prediction accuracy of the developed models was tested using various model performance indices. The study revealed that rock strength influence blast fragmentation results and based on the rock strength properties, the fragmentation block size increase with an increase in rock strength. The result of the model performance indices used for the evaluation of the proposed models showed that the modified Artificial Neural Network (ANN) called Hunter point (HP-ANN) has the highest predictive accuracy. A new model evaluator was also developed in this study called the decision factor. Its application indicates the HP-ANN model to be the best model suitable for the prediction of blast fragment size distribution. Therefore, the developed models can be used to predict blast result mean size (X50) and 80% percentage passing size (X80) for mining engineering blasting practices.
Abstract: Reconstruction of geological images using partial measurement is one of the most important topics in geosciences. In many methods, this is done using training images and very complex models which increase the computational complexity. In the first part of the article, a simple method based on spatial domain filters such as median and mean filter has been presented to reconstruct geological images. One of the most significant characteristics of this method is that it does not need the training image; moreover, its computational complexity is less than the other advanced methods. Via this method, it is easy to reconstruct binary, continuous, and three-dimensional images. The results show that the reconstruction accuracy of the proposed method is also acceptable. In the second part of the article, to introduce quantum computing to geosciences and encourage researchers to work on this issue, a quantum median filter is proposed to reconstruct geological images. According to the results, this method has much less computational complexity than classical methods such as DS. Also, its results are acceptable in terms of reconstruction rate. Due to the high speed of quantum algorithms and the widespread use of quantum computers in the near future, researchers in this field must become more familiar with quantum computing.
Abstract: This work presents an algorithm to construct a 3D magnetic susceptibility property from magnetic geophysical data. Physical model discretization has a substantial impact on accurate inverse modeling of the sought sources in potential field geophysics, where structural meshing suffers from edge preserving of complex-shaped geological sources. A finite-element (FE) methodology is usually employed in potential field geophysics to discretize the desired physical model domain through an unstructured mesh. The forward operator is calculated through a Gauss-Legendre quadrature technique rather than an analytic equation. To stabilize the mathematical procedure of inverse modeling and cope with the intrinsic non-uniqueness arising from magnetometry data modeling, regularization is often implemented by utilizing a norm-based Tikhonov cost function. A so-called fast technique, “Lanczos Bidiagonalization (LB) algorithm”, can be utilized to solve the central system of equations derived from optimizing the function, where it decreases the execution time of the inverse problem by replacing the forward matrix with a lower dimension one. In addition, to obtain the best regularization parameter, a weighted generalized cross-validation (WGCV) curve is plotted, which makes a balance between the misfit norm and model norm introduced in the cost function. To tackle the normal propensity of physical structures to focus at the shallow depth, an expression of depth weighting is used. This procedure is applied to a synthetic scenario presenting a complex-shaped geometry along with a real set of magnetic data in the central part of Iran. So the capability of the proposed algorithm for inversion indicates the accuracy of the inversion algorithm. Additionally, the modeling results pertaining to a field case study are in good agreement with the drilling data.
Abstract: Dealing with numerous reviews and wide inquiries, it has been concluded that much more information and interpretive parameters are accessible related to the subsurface structures while using a particular frequency range in the spectral induced polarization (SIP) measurements. Therefore, the interpretation uncertainty would diminish which causes studies with more valid and authentic outcomes. This could be achieved by using a comprehensive and general model which is appropriate for representing electrical features variation in terms of frequency, known as the Cole-Cole model. By using the SIP method and applying a defined broad of frequencies, it would be conceivable to describe items such as medium properties, spectral behavior of the studied area, and intensity of every single parameter. The widespread utilization of the SIP method requires accurate and fast modeling and inversion algorithms. An integral part of every geo-electrical data inversion is accurate and efficient forward modeling resulting in numerical simulation of responses for a given physical property model. In other words, like every other geophysical method, a reliable spectral-induced polarization inversion is highly dependent on the accuracy of the forward problem. Forward modeling is accomplished over a 2D earth structure to generate complex resistivity data by current flow simulation into the earth's surface and solution of the Poisson equation containing complex values. In this contribution, a finite difference algorithm is applied to solve the complex partial differential equations (PDEs) restricted by a mixed boundary condition. A spatial Fourier transform of the PDEs with respect to a defined range of wavenumbers is carried out along the strike direction to elucidate 3D source characteristics. Eventually, it is needed to conduct an inverse Fourier transform to obtain potential solutions in the spatial domain. To verify the accuracy of the proposed numerical algorithm, some synthetic models are simulated and the forward responses including resistance and phase values with respect to a specific frequency spectrum are calculated. Furthermore, a comparison between our numerical results and those of Geotomo geo-electrical software is provided.
Abstract: From an economic, technological, and environmental perspective, sulfur removal from coal resources has received increased attention in recent years. The present work investigates the ability of chemical (Meyers and Molten caustic leaching (MCL)) and biological methods for the desulfurization of Tabas coal. Accordingly, in the Meyer process, at 1 M ferric sulfate concentration, during 90 minutes at 90 ° C, 61.78 % of ash and 82% of pyrite, and 51.35% of total sulfur were removed from Tabas coal, respectively. The MCL method was also investigated. Hence, based on the MCL experimental condition of caustic soda /coal ratio of 2, leaching time of 60 minutes, and constant temperature of 180 ° C, 71.82 % of ash, 88% of pyrite sulfur, and 57.85% of total sulfur content were removed from Tabas coal, respectively. Furthermore, biodesulfurization of Tabas coal was conducted using a mixed culture of acidophilic iron- and sulfur-oxidizing mesophilic bacteria. The effect of time, bacterial medium, solid/liquid (S/L) %, and the absence of bacteria were investigated, and based on the results, time was the most significant parameter. Accordingly, 68.98% of ash, 92% of pyrite sulfur, and 72.43% of total sulfur were removed from Tabas coal with 20% v/v bacterial inoculum during 20 days, respectively.
Abstract: Characterization of large reservoir models with a great number of uncertain parameters is frequently carried out by ensemble-based assimilation methods, due to their computational efficiency, ease of implementation, versatility and nonnecessity of adjoint code. In this study, multiple ensemble-based assimilation techniques are utilized to characterize the well-known PUNQ-S3 model. Accordingly, actual measurements are employed to determine porosity, horizontal and vertical permeabilities and their associated uncertainties. In consequence, uncertain parameters of the model will be gradually adapted toward the true values during assimilation of actual measurements, including bottomhole pressure and production rates of the reservoir. Monotonic reduction of root-mean-squared error and capturing the key points of the maps (such as direction of anisotropy and porosity/permeability contrasts) verify successful estimation of the geostatistical properties of the PUNQ-S3 model during history matching. At the end of the assimilation process, RMSE values for Deterministic Ensemble Kalman Filter, Ensemble Kalman Filter, Ensemble Kalman Filter with Bootstrap Regularization, Ensemble Transform Kalman Filter Symmetric Solution, Ensemble Transform Kalman Filter Random Rotation, and Singular Evolutive Interpolated Kalman filter are 1.120, 1.153, 1.132, 1.132, 1.129, and 1.113, respectively. In addition to RMSE, the quality of history match as well as prediction of the future performance are looked into in order to assess the performance of the assimilation process. Obviously, the results of the ensemble-based assimilation methods closely match the true results both in the history match section and in the future prediction section. Besides, the uncertainty of future predictions is quantified by the use of multiple history-matched realizations. This is due to the fact that Kalman-based filters use Bayesian framework in the assimilation step. Accordingly, updated ensemble members are samples of the posterior distribution through which the uncertainty of the future performance is assessed.
Abstract: Birjand region is a portion of South Khorasan province situated in the structural-magmatic zone of eastern Iran. As a part of the continental shelf, it forms from subduction during the Cenozoic and subsequent continental collisions. This region is favorable for copper and gold mineralization for various geological reasons. The ultimate goal of this study is to create a Cu geochemical potential map to delimit prone regions for further mining activities. A total of 2468 geochemical samples were gathered to run a 20-element analysis. Taking data preprocessing approaches such as correction of outlier data and data normalization into consideration, a fractal graph through a concentration-number (C-N) model was produced to isolate different geochemical populations of Cu, Pb, Zn, Ag, Ba, and Ni for Cu targeting. Then, a Prediction-area (P-A) graph was plotted for each geochemical variable to determine the weight of each evidence map. The results show that Barium map indicates a prediction rate of 72% and specifies 28% of the studied areas as mineralization prone areas. The zinc geochemical map presents an ore prediction rate of 65% and 35% of the area as the potential zone. In addition, Copper with an ore prediction of 56% covered 44% of the Birjand region. Finally, a hybrid evidence map was overlaid. Accordingly, the geochemical potential areas were located further at south and south-east of Birjand, which were closely related. Moreover, there are highly favorable areas in the middle part. It is noteworthy that the copper potential map has higher efficiency over each individual geochemical evidence, with an ore prediction rate of 75% and occupying 25% of the area as favorable zones.
Abstract: Geoelectrical methods are considered common subsurface geophysical imaging tools providing significant insight into the electrical properties of targets. Considering the three-dimensional nature of subsurface structures, geoelectrical survey data and their 3D inverted models can yield reliable and accurate results. Using an unstructured tetrahedral meshing in this research, three-dimensional forward and inverse models of electrical resistivity and chargeability data were performed for geological structures with travertine layers. Application of the unstructured mesh for the discretization of the subsurface geological units increases the speed and accuracy of the modeling procedure as well as the flexibility in designing and implementing meshing on tough topographies and the complex-shaped geometry of the target mass. Using an open-source and full-item Python software named ResIPy, the forward and inverse models were calculated and interpreted precisely. According to the geological background of the studied area, to investigate the applicability and efficiency of the 3D geoelectrical modeling method in imaging the subsurface travertine deposits, three synthetic scenarios were modeled according to the geological setting of the studied area. The results of the 3D inversion of the synthetic models indicated the accuracy and validity of this procedure in the exploration of underground travertine deposits. As a real case study, the electrical resistivity and chargeability survey datasets in the Atashkohe travertine mine were inverted in 3D aimed at inferring the schematic geological sections along the three surveyed profiles. The survey was conducted with an electrode spacing of 10 and 15 meters and a combination of dipole-dipole and pole-dipole arrays. Considering the two-dimensional nature of these data and the relatively large distance between the two main profiles, the three-dimensional inversion results may increase the error rate, therefore, the 2D batch inversion was preferably utilized to obtain the more realistic and sensible geological model. According to the geological studies and instrumental analysis of the rock samples, three types of geological structures were identified throughout the study area. Upon the subsurface electrical characteristics inferred along each profile, three geological layers were designed to illustrate the underground structures. The comparison of the inferred geological models and the drilling results along one of the survey profiles demonstrated acceptable compatibility and concordance indicating the efficiency of the research utilized approach.
Abstract: This paper presents a novel rock engineering system (RES) based method for estimating blast-induced vibration attenuation risk index and predicting peak particle velocity (PPV). The RES approach involves three key steps, which are the identification of influencing parameters, the construction of an interaction matrix and the rating of parameters based on their influence on ground vibration. The selected parameters are the scale distance (SD), the ratio of the scale distance to stemming divided by the burden (SD/TB), the distance of the monitoring station (D), the scale distance divided by the burden (SD/B), the ratio of the scale distance to powder factor (SD/PF) and the ratio of scale distance to spacing divided by the burden (SD/SB). The results indicated that all the six parameters considered have statistically significant influences on the constructed interaction matrix system, with the SD having the highest weighty factor (21.43%) while SD/TB is the lowest (14.29%). The maximum rating of the parameters is 5, 5, 4, 5, 5, 4 for SD, D, SD/B, SD/PF, SD/SB and SD/TB, respectively. The attenuation risk index ranges from 14.29 to 63.43, and the slope of the actual measured PPV against the calculated attenuation risk index is negative. The developed RES-based model demonstrated better performance and a reliable method for ground vibrations prediction with a higher degree of accuracy, considering its higher determination coefficient (R2 = 0.96) and smaller error (RMSE = 1.08, MAD = 0.79, MAPE = 9.95) compared to multiple regression, Langefors & Kihlstrom and Hudaverdi models.
Abstract: In the open-pit mining method, it is necessary to design the ultimate pit limit before mining to determine issues such as the amount of minable reserve, the amount of waste removal, the location of surface facilities, and production scheduling. If the obtained profit of the extraction of the pit limit becomes maximum, it is called the optimum pit limit. Various algorithms have been presented based on heuristic and mathematical logic for determining the optimum pit limit. Several algorithms such as the floating cone algorithm and its corrected forms, the Korobov algorithm and its corrected form, dynamic programming 2D, Lerchs and Grossmann algorithm based on graph theory have been presented to find out the optimum pit limit. Each of these algorithms has particular advantages and disadvantages. The designers of the corrected form of the Korobov algorithm claim that this algorithm can yield the true optimum pit in all cases. Investigation shows that this algorithm is incapable of yielding the true optimum conditions in all models and in some models the method produces an optimum with a negative value. In this paper, this algorithm has been evaluated, and also a modification model is presented to overcome its disadvantage. This new algorithm was named Korobov algorithm III. In this paper, this new algorithm was considered in different models of two and three-dimensional space. A case study for designing of optimum pit limit in three-dimensional space was done for a gold mine in the sewed country. The outcomes of Table 9 show that this new method designs a pit limit with a 69428.59 value that has better results than previous Korobov algorithms.
Abstract: A series of plate load tests were performed on a model T-shaped skirted footing by varying the normalized skirt depth and relative density of sand from 0.25 to 1.5 and 30 % to 60 %, respectively. The findings revealed that, regardless of the roughness condition, the observed peak in the pressure settlement ratio corresponding to relative densities of 30%, 40%, 50%, and 60% gradually vanished as the normalized skirt depth was increased from 0.25 to 1.5. The results further revealed that at a given pressure, a lesser settlement ratio was observed for a skirted footing than the footing without a skirt. The most significant benefit of providing a skirt to the footing was obtained when the base and skirt were partially rough and the relative density of sand was kept at 30%. In all the cases, the observed bearing capacity ratio for the present skirted footing was higher than the H-shaped skirted footing reported in the literature. Finally, an empirical equation was proposed to predict the bearing capacity ratio and settlement reduction factor for a given skirt depth and sand relative density.
Abstract: For the possibility of using valuable lands with plateaus terrain, the High-filled cut-and-cover tunnels (HFCCTs) are considered a practical and successful solution. The HFCCT is first constructed and then backfilled in layers in the trench, which is different from traditional tunnel construction methods. Because the high amount of backfill soil above the HFCCT produces ultrahigh earth pressure, it is necessary to use load reduction methods to reduce the earth pressure on the HFCCT, which will reduce the tunnel designing structure loads and increase safety. This study describes two load reduction methods using a combination of tire-derived aggregate (TDA) and geogrid. Abaqus CAE 2019 software, based on the finite element method, was employed to analyze and examine the lateral earth pressure (LEP) reduction progress and mechanism. Several influential factors, including the geogrid presence effect, the TDA form, the TDA thickness, and the distance between the top of the HFCCT and the bottom of the TDA were studied. The analysis results focused on changes in average LEP, relative vertical displacement of the HFCCT backfill soil prisms, and the effect of geogrid presence on the top of the TDA. This study found that the factors are influential and have significant effects on the average LEP reduction on the HFCCT through the load reduction mechanisms, which include relative vertical displacements of the HFCCT backfill soil prisms and soil arching, where the average LEP on the top of the HFCCT model reduced from 303 kPa to 125 kPa (58.745% reduction in the average LEP).
Abstract: Tash bauxite mine is located approximately 6 km northeast of Tash village and 40 km northwest of Shahroud city in Semnan Province with coordinates of 36° 32′ N to 36° 37′ N and 54° 41′ E to 54° 48′ E. The actions of the orogenic phase of the former Cimmerian as well as the chemical and physical factors have caused the erosion of the basalts in the Shemshak sedimentary basin, which have resulted in the simultaneous deposition of the Shemshak molasses and bauxite in Tash area. According to some geological evidence and the location of Elias rule, bauxites in the vicinity of Shemshak Formation shales, it is concluded that the clay minerals have played an important role in forming the bauxite deposits in this area. The results showed that the basalts were formed from the alkaline magma and then altered to the clay minerals. The rmaining immobile elements such as aluminum and residual iron formed Tash bauxite deposit. The investigation of thin sections designates that the studied ore contains ooidal, plitomorphic, allogeneic pizolite, coloform, and compressive dissolution tissues, which indicates the autochthonous origin. Pyrite, chalcopyrite, goethite, and hematite were also recognized. The mineralogical study, performed by the X-Ray diffraction method, led to the identification of minerals of anatase, boehmite, diaspore, chamosite, kaolinite, quartz, and hematite. Analysis of ore samples by the X-Ray fluorescence method and calculation of aggregation coefficient of trace elements and geochemical indicators along with geological evidence revealed the source rock could be from the mafic type.
Abstract: In integrating geospatial datasets for mineral potential mapping (MPM), the uncertainty model of MPM can be inferred from the Dempster – Shafer rules of combination. In addition to generating the uncertainty model, evidential belief functions (EBFs) present the belief, plausibility and disbelief of MPM, whereby four models can be simultaneously utilized to facilitate the interpretation of mineral favourability output. To investigate the functionality and applicability of the EBFs, we selected the Naysian porphyry copper district located on the Urmia – Dokhtar magmatic belt in the northeast of the Isfahan city, central Iran. Multidisciplinary datasets- that are geochemical and geophysical data, ASTER satellite images, Quickbird and ground survey- were designed in a geospatial database to run MPM. Implementing the Dempster law through intersection (And) and union (OR) operators led to different MPM performances. To amplify the accuracy of the generated favourability maps, a combinatory EBFs technique was applied in three ways: (1) just OR operator, (2) just And operator, and (3) combination of And and OR operators. The plausibility map (as mineral favourability map) was compared to Cu productivity values derived from drilled boreholes, where the MPM accuracy of hybrid method was higher than each individual operator. Of note the success rate of hybrid method validated by 21 boreholes was about 84%, and it demarcates high favourability zones occupying 0.67 km2 of the studied area.
Abstract: Tunnel construction in cities faces many geotechnical challenges, and the effect on pile foundation is possibly one of the most complex ones. Most tall buildings in big cities mostly have pile foundations, and any tunnelling nearby might significantly influence those existing foundations. In the present study, a 3-dimensional Finite Element (FE) analysis has been carried out to investigate tunnelling effects on pile foundations. The investigation is done for a single pile with multiple stages of tunnel excavation where the pile foundations are assumed to reach below the base of the excavation of tunnelling. A tentative rate of excavation was also included in this investigation and found that a faster rate of excavation results in better performance of foundations affected by tunnelling. The study also extended to see the effect of tunnelling on pile groups. Attempts were made to compare the results with some of the previously published literature.
Abstract: Filters are widely used for dewatering in the mining industry. In general, different parameters affect vacuum filtration, such as solid percentage, vacuum level, particle size distribution, filter cloth, and chemical additives. These parameters can influence filtration properties such as cake moisture, throughput, and filter cloth lifetime. Moisture and throughput usually are used to determine the quality of filtration. In this study, new variables were used to express the filtration and characteristics of filter cake at a microscopic scale. The quality of filter cake can be precociously analyzed using void fraction and density of filter cake. The present study aimed to propose some new variables to properly analyze the filtration process, improve the filtration rate, and decrease the cake moisture of Gol-E Gohar iron ore concentrate. In this regard, a series of filtration experiments was implemented using laboratory-scale bottom and top feed vacuum filters. The results showed that an increase in the solid percentage decreased the void fraction from 0.45 to 0.40 and increased cake density from 0.30 to 0.33 gr.cm-3, respectively. Increasing the particle size increased the void fraction from 0.415 to 0.43. Furthermore, the type of structural or capillary moisture of the filter cake could be determined using a void fraction.
Abstract: Because of the limitations of manipulating single geophysical data sets to interpret subsurface anomalies for many cases, it is required to combine geophysical data in order to decrease the ambiguity and non-uniqueness of the interpretation. Integration interpretation of two different geophysical data sets is one of the most common ways to integrate geophysical data and in this paper we want to utilize the combination of gravity and magnetic data for the Golgohar mine in Iran. This mining case is located in the Sanandaj-Sirjan zone in the province of Kerman. Gravity and magnetic data are interpreted using a MATLAB code written based on the damped weighted minimum length solution for which the model weighting is the product of the multiplying of compactness and depth weighting constraints. At first the inversion algorithm is applied on the synthetic case to investigate its reliability for practical application on the real data. Reconstructed models from the noise contaminated synthetic data are suggestive of productivity of the inversion algorithm. Ultimately, the algorithm is applied for the interpretation of the real data and the inversion results of both data sets shows a high correlation about the magnetite anomaly position horizontally and vertically. The results represent an anomaly with the depth ranges approximately from 25 to 130 m with horizontal extension of about 120 m from 280 to 400 m relative to the start of the interested profile.
Abstract: Blastability is one of the most important and effective parameters in open pit mining, which is closely related to rock mass, environmental conditions and explosion systems. To investigate the blastability, many classification systems have been proposed so far, each of which has expressed some of the parameters affecting the blasting according to environmental conditions and based on empirical judgments. Therefore, the factors affecting the blastability can be identified and determined according to theories and environmental conditions. Due to the necessity and presentation of a classification system to investigate the blastability of the Sangan iron ore mines project, by studying and examining each of these factors, in this paper, this classification system was presented and introduced. For this purpose, according to the response received from a questionnaire sent to experts around the world and using the fuzzy Delphi Hierarchical Analysis (FDAHP) method, the weighting of each of the factors affecting the proposed classification system was performed and finally, a new classification system was introduced to optimize blastability classification.
Abstract: The large-scale open-pit mine production planning problem is an NP-hard issue. That is, it cannot be solved in a reasonable computational time. To solve this problem, various methods, including metaheuristic methods, have been proposed to reduce the computation time. One of these methods is the genetic algorithm (GA) which can provide near-optimal solutions to the problem in a shorter time. This paper aims to evaluate the efficiency of the GA technique based on the pit values and computational times compared with other methods of designing the ultimate pit limit (UPL). In other words, in addition to GA evaluation in UPL design, other proposed methods for UPL design are also compared. Determining the UPL of an open-pit mine is the first step in production planning. UPL solver selects blocks whose total economic value is maximum while meeting the slope constraints. In this regard, various methods have been proposed, which can be classified into three general categories: Operational Research (OR), heuristic, and metaheuristic. The GA, categorized as a metaheuristic method, Linear Programming (LP) model as an OR method, and Floating Cone (FC) algorithm as a heuristic method, have been employed to determine the UPL of open-pit mines. Since the LP method provides the exact answer, consider the basics. Then the results of GA were validated based on the results of LP and compared with the results of FC. This paper used the Marvin mine block model with characteristics of 53271 blocks and eight levels as a case study. Comparing the UPL value's three ways revealed that the LP model received the highest value by comparing the value obtained from GA and the FC algorithm's lowest value. However, the GA provided the results in a shorter time than LP, which is more critical in large-scale production planning problems. By performing the sensitivity analysis in the GA on the two parameters, crossover and mutation probability, the GA's UPL value was modified to 20940. Its UPL value is only 8% less than LP's UPL value.
Abstract: Ground settlement need to be predicted well so that necessary precautionary measures could be adopted. Ground deformation behaviour due to tunnel construction in inhomogeneous soil has been studied in the past few decades by many researchers. When tunnel-induced ground, settlement is predicted by considering average soil properties, it is likely to miss the true settlement characteristics and failure mechanism due to the inherent heterogeneity of the ground. In this paper, spatial variability of the ground is considered in the numerical analysis to simulate the ground settlement. A numerical model is developed using the Finite-Difference based numerical code FLAC3D to simulate tunnel construction with earth pressure balance (EPB) TBMs for a case study. Both 2D and 3D random fields are simulated in the numerical model. Results are systematically compared with some of the empirical and analytical methods for predicting ground settlement. Spatial distribution is found to have a significant effect on surface settlements and overall ground behaviour.
Abstract: In current study, sampling from the Baghak anomaly in Sangan mines has been carried out based on radioactivity and radiation measurement methods. The goal of this study is to survey the presence or absence of such a relation (between rare earth and radioactive elements) in a skarn mine which is a different case study in central Iran. Mineralogical studies (based on optical and electronic microscopic observations), univariate and multivariate statistical investigations and geochemical analyses are applied. Results show that the Baghak anomaly is due to a significant amount of U, Ce, La and a high concentration of REEs. It seems that mineralization of Th and REEs occurred simultaneously with the formation of iron skarn, while uranium mineralization in hydrothermal form occurred in a secondary phase after the skarn iron mineralization. Finally, it could be acknowledged that in addition to presence of such a relation in the mineralization (central Iran mineralizations), there is an acceptable correlation between these elements in Baghak iron-skarn mineralization.
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