International Journal of Mining & Geo-Engineering
Volume:57 Issue: 1, Winter 2023

The 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 has resulted in the simultaneous deposition of the Shemshak molasses and bauxite in the 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 clay minerals. The remaining immobile elements such as aluminum and residual iron formed the Tash bauxite deposit. The investigation of thin sections designates that the studied ore contains ooidal, plitomorphic, allogeneic pizolite, coloform, and compressive dissolution texture, 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.

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 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 the 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 the hybrid method was higher than each operator. Of note, the success rate of the hybrid method validated by 21 boreholes was about 84%, and it demarcates high favourability zones occupying 0.67 km2 of the studied area.

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 tunneling nearby might significantly influence those existing foundations. In the present study, a 3-dimensional Finite Element (FE) analysis has been carried out to investigate tunneling 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 tunneling. 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 tunneling. The study also extended to see the effect of tunneling on pile groups. Attempts were made to compare the results with some of the previously published literature.

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 the filter cake can be precociously analyzed using the void fraction and density of the 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 were implemented using laboratory-scale bottom 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.

Because of the limitations of manipulating single geophysical data sets to interpret subsurface anomalies for many cases, it is required to combine geophysical data 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 to the synthetic case to investigate its reliability for practical application on real data. Reconstructed models from the noise-contaminated synthetic data are suggestive of the 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 show a high correlation between the magnetite anomaly position horizontally and vertically. The results represent an anomaly with the depth ranging approximately from 25 to 130 m with the horizontal extension of about 120 m from 280 to 400 m relative to the start of the interesting profile.

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 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 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.

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.

Ground settlement need to be predicted well so that necessary precautionary measures could be adopted. Ground deformation behavior 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 behavior.

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.

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).

This work presents an algorithm to construct a 3D magnetic susceptibility property from magnetic geophysical data. Physical model discretization has 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. In potential field geophysics, a finite-element (FE) methodology is usually employed 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 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 best regularization parameter, a weighted generalized cross-validation (WGCV) curve is plotted, that makes a balance between misfit norm and model norm introduced in the cost function. In order 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 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.

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.