Journal of Mining and Environement
Volume:12 Issue: 1, Winter 2021

The ultimate pit limit optimization (UPLO) serves as an important step in the mine planning process. Various approaches of maximum flow algorithms such as pseudo-flow and push-relabel have been used for pit optimization, and have given good results. The Boykov-Kolmogorov (BK) maximum flow algorithm has been used in solving the computer vision problems and has given great practical results but it has never been applied in UPLO. In this work, we formulate and use the BK maximum flow algorithm and the push-relabel maximum flow algorithm in MATLAB Boost Graph Library within the MATLAB software in order to perform UPLO in two case studies. Comparing both case studies for the BK maximum flow algorithm and push-relabel maximum flow algorithm gives the same maximum pit values but the BK maximum flow algorithm reduces the time consumed by 12% in the first case and 16% in the second case. This successful application of the BK maximum flow algorithm shows that it can also be used in UPLO.

Modelling wear of drill bits can increase the efficiency in the drilling operations. Related to the subject, it is aimed to investigate the wear mechanism of drill bits. Wear in drill bits is influenced by many factors related to the drilling and rock properties. The type and intensity of wear are dependent on several complicated factors that are required to be considered in anticipating the rate of wear in the field and laboratory conditions. The laboratory tests have been performed in order to specify the relationships between the bit wear rate and the physico-mechanical properties, drillability, abrasive properties, and brittleness of rocks. Statistical analysis has been used to obtain equations for estimating the bit wear rate based on the rock properties. In this work, an ensemble technique is used to estimate the confidence interval and the prediction intervals for the regression models. This paper summaries the rock properties and bit wear mechanism, and argues the options to determine the bit wear rate. The test models indicate that the rock properties can give an idea of bit wear. They also show a good correlation between the bit wear rates. Also some models are developed to represent the wear quantification, and an approach is suggested in order to estimate the bit wear rate. The results obtained from studying the developed models provide a good agreement with the performance evaluation of an efficient drilling, which provide an indirect evaluation of drill bit wear rate during a drilling process, which can help to reduce the specific energy consumption and lower costs for the exchange of drill bits.

One of the most important tasks in designing the undercut slopes is to determine the maximum stable undercut span to which various parameters such as the shear strength of the soil and the geometrical properties of the slope are related. Based on the arching phenomenon, by undercutting a slope, the weight load of the slope is transferred to the adjacent parts, leading to an increase in the stability of the slope. However, it may also lead to a ploughing failure on the adjacent parts. The application of counterweight on the adjacent parts of an undercut slope is a useful technique to prevent the ploughing failure. In other words, the slopes become stronger as an additional weight is put to the legs; hence, the excavated area can be increased to a wider span before the failure of the slope. This technique could be applied in order to stabilize the temporary slopes. In this work, determination of the maximum width of an undercut span is evaluated under both the static and pseudo-static conditions using numerical analyses. A series of tests are conducted with 120 numerical models using various values for the slope angles, the pseudo-static seismic loads, and the counterweight widths. The numerical results obtained are examined with a statistical method using the response surface methodology. An analysis of variance is carried out in order to investigate the influence of each input variable on the response parameter, and a new equation is derived for computation of the maximum stable undercut span in terms of the input parameters.

In this paper, a power-law relation modeling called the vario-fractal model is introduced in order to understand the discrepancies between the linear and non-linear distribution of the elements and its application for mineral exploration in the calamine Zn-Pb ore-deposit. From a hypothetical viewpoint, since geochemical zonation of the supra- and sub-ore elements is a crucial evaluation criterion for concealed/underlying mineralization potentials, this hypothesis can be tested by delineating the fractal surfaces of elements as the geometric evidence of primary geochemical zonation of elements in the calamine mine. A comparison of the linear regression results with the Poisson distribution coefficients indicate the relative tendency of the elements towards a non-linear distribution. Therefore, a logarithmic equation derived from the variance-distance relationship (power-law) is used here for the delineation of fractal surfaces of elements as the geometric features related to proper self-organized distributions. In this research work, the vario-fractal expression of geochemical zonation has trace-element tendencies to the non-linear distribution. The results obtained show that the calamine’s fractional surfaces are mostly of self-organized types, situated at 2 < FD < 3 as "real fractal surfaces", although 3 of the elements appear in the quasi-fractal populations called "near Brownies” here. Moreover, the calamine’s fractal surfaces can be extended throughout the anomalous regions or may be distributed as limited types of the finalized model, which is a fractal-based pattern of geochemical zonation of the elements for evaluation of the hypogenic mineralization potential and has been prioritized to 6 target-areas containing 10 elements with real fractal surfaces and 3 more at near Brownies and then validated by the mineralogical evidence.

The aim of this work is to obtain recycled aggregate (RA) from construction debris in order to reduce the rapid consumption of aggregate resources and the environmental impact of these resources. In order to fulfill this aim, the density, porosity, Schmidt hardness test, uniaxial compression resistance, carbonation depth, and ultrasonic p-wave velocity experiments were conducted on different construction debris transported by trucks from 9 different points in Turkey. In addition, the debris samples taken were broken down to the size of the aggregate and subjected to the tests of density, porosity, moisture content, freeze-thaw, and impact resistance. As a result of the conducted experiments, the lowest mass loss as a result of freezing-thawing was in GRA with 9.36%, the highest mass loss was in ORA with 22.58%, the highest ORA average aggregate impact strength index was 21.27%, and the lowest TRA aggregate impact strength index was found to be 18.26%. İt was determined that most of the physical properties of RA obtained from the construction wreckage was within the limit values specified in the literature and that the recycled aggregates could be used instead of natural aggregate. With this work and these results, RA obtained could be used in many areas such as concrete aggregate in the construction sector, underground filling in mining, filling material in gunned concrete, and filling materials on highways.

In this work, we employ the fuzzy logic technique to achieve and present, for the first time, a proper analysis of the actual intensity of the increase in the coal miners’ fatality rates in Pakistan from 2010 to 2018, compared with China and India, with an objective to minimize the impact of incidents on the miners’ fatalities. The average and yearwise fatality rates in Pakistan, compared with China and India, are used for the fuzzy logic technique in order to calculate the actual degree of flexibility for the surging fatalities. The findings show that both the average (2010-2018) and yearwise fatality rates in 2011, 2015, and 2018 are 2.44, 1.74, and 1.6, respectively. In the fuzzy logic technique, the variables whose membership function (µ) values are ≥ 1 represent the absolute truth. The membership function values for the years 2011, 2015, and 2018 are alarmingly high for the fatalities of coal miners. Similarly, except for 2014 and 2010, where 0 represents the absolute falseness, the results for the remaining years indicate high fatality rates with a flexibility (or small extent) of its corresponding membership function (µ) values such as 0.623, 0.739, 0.219, 0.173 and 0.115, and 0.714, 0.24, 0.01, 0.324 and 0.317 using the average and yearwise analysis, respectively, compared with China. Likewise, the fuzzy logic membership function (µ) values compared with India in the remaining years are 0.704, 0.795, 0.386, 0.159, 0.352 and 0.306, and 0.675, 0.795, 0.386, 0.186, 0.321 and 0.322, respectively. The proposed fuzzy logic analysis has been founded based on the theory of fuzzy sets to properly identify the miners’ fatalities, and also to suggest the implementation of appropriate recommendations to reduce the fatalities in the coal mines in Pakistan.

In this study, the chemical composition of water and soils contiguous to two abandoned coal mines in southeastern Nigeria, was assessed to evaluate the impact of water flow from the mines ponds on the geoenvironment and potential for acid mine drainage (AMD). Parameters including the pH, anions and cations, and the heavy metals were measured. These were used to evaluate contamination/pollution using hybrid factors including Pollution Load Index, factors, enrichment factors, pollution load index and index of geoaccumulation. The pH range of 3.4 to 5.9 classified the water as weakly to strongly acidic, typical of AMD. The SO42– ion, which indicates pollution by mine waters, showed moderate to high concentrations. Iron, zinc lead and copper were the most abundant heavy metals. Pollution Load Index values were greater than unity which show progressive deterioration in water and sediment quality. The Enrichment Factor values of up to 1 indicated enrichment through lithogenic and anthropogenic sources. The mine dumps serve as pools that can release toxic heavy metals into the water bodies by various processes of remobilization. Based on the lithology, mineralogy, chemical concentrations and environmental factors, the study has shown that there exists a potential for the generation of AMD. The heavy metals enriched mine flow, especially iron, empty into the nearby water bodies which serve as sources of municipal water supply. Consumption of untreated water over a prolonged period from these water sources may be detrimental to health. Remedial measure and continuous monitoring are recommended for good environmental stewardship.

Providing an approach to calculate a suitable panel width for the longwall mining method is considered considering both the technical and economic factors. Based on the investigations carried out, a technical-economic model is proposed to calculate a suitable panel width. The proposed model is a combination of the rock engineering system-based model and the technical relationships to estimate the expected actual face advance rate of the longwall panel and also the economic relationships to determine the operational costs. Applying the technical conditions to the presented model is conducted by the vulnerability index of the advancing operation, which considers the face advance rate as the main important factor that controls the operational costs of the longwall face. The performance evaluation of the presented model is possible by the recordable field data, which is one of its advantages. This process is carried out by a case study, and the results obtained indicate that the developed approach can provide an applicable tool to calculate a suitable panel width.

In this paper, we investigate a probabilistic approach in order to predict how acid mine drainage is generated within coal waste particles in NE Iran. For this, a database is built based on the previous studies that have investigated the pyrite oxidation process within the oldest abandoned pile during the last decade. According to the available data, the remaining pyrite fraction is considered as the output data, while the depth of the waste, concentration of bicarbonate, and oxygen fraction are the input parameters. Then the best probability distribution functions are determined on each one of the input parameters based on a Monte Carlo simulation. Also the best relationships between the input data and the output data are presented regarding the statistical regression analyses. Afterward, the best probability distribution functions of the input parameters are inserted into the linear statistical relationships to find the probability distribution function of the output data. The results obtained reveal that the values of the remaining pyrite fraction are between 0.764% and 1.811% at a probability level of 90%. Moreover, the sensitivity analysis carried out by applying the tornado diagram shows that the pile depth has, by far, the most critical factors affecting the pyrite remaining

Due to the gradual deepening of the Mazinu coal seams from the ground surface, both the open-pit (OP) and underground (UG) mining methods can be applied for extracting them. Thus, it is a necessity to determine the interface of these mining methods optimally. The present paper aims to determine this interface by generating different scenarios using the OP phases and their relative underground stopes, and comparing them with each other. In this regard, an economic block model is created based on the calorific value of the coal portions involved by each block along with the required economic and technical parameters. Then using the Lerchs-Grossman algorithm, the OP phases are created. Proportional to each phase, the production scheduling of underground stopes is executed. Finally, in order to opt the best scenario, the net present value of the whole project (OP & UG) achieved from different scenarios are compared with each other. The results obtained indicate that the optimum interface of the OP and UG mining activities correspond to the ultimate OP limit with a maximum depth of 200 m from the ground surface.

This work incorporates the DEMATEL-MABAC method for quantifying the potential of roof fall in coal mines by means of the coal mine roof rating (CMRR) parameters. For this purpose, considering the roof weighting interval as a quantitative criterion for the stability of the roof, the immediate roof falling potential was quantified and ranked in 15 stopes of Eastern Alborz Coal Mines Company. In this regard, on the basis of the experts’ judgments, the fuzzy DEMATEL method was used for designation weights of the parameters, and the MABAC method was incorporated to quantify and rank the stopes (alternatives). “UCS of roof” and “joint spacing” in the immediate roof were found to be the most important parameters that controlled roof falling in stopes; and “joint persistence” was also found to be a quite significant parameter. Finding confirms that overall strength of rood rock mass plays a main role in the falling potential. Comparison of the coefficients of determination (R2) between the weighting interval and proposed model with that and original CMRR indicated more than 15% increase, which represented that the new proposed model was more accurate to quantify roof quality. The findings of this work show that using this combined method and specializing the CMRR method for a given mine geo-condition to assess the quality of the roof and its potential of collapse possesses a higher performance when compared with the original CMRR method.

The experimental and numerical methods were used to investigate the effects of joint number and joint angle on the failure behaviour of rock pillars under a uniaxial compressive test. The gypsum samples with dimensions of 200 mm × 200 mm × 50 mm were prepared. The compressive strength of the intact sample was 7.2 MPa. The imbeded joint was placed inside the specimen. The joint length was 6 cm in a constant joint length. There were several numbers of cracks including one, two, and three cracks. In the experimental tests, the angles of the diagonal plane with respect to the horizontal axis were 0, 30, 60, and 90 degrees. The axial load was applied to the model with a rate of 0.01 mm/s. In the fracture analysis code, the angles of the diagonal plane with respect to the horizontal axis were 0, 15, 30, 45, 60, 75, and 90 degrees. A constant axial load of 135 MPa was applied to the model. The results obtained showed that the failure process was mostly dependent on the angle and number of the non-persistent joint. The compressive strength of the samples was dependent on the fracture pattern and the failure mechanism of the discontinuities. It was shown that the tensile cracks were developed whithin the model. The strength of the specimens increased by increasing both the joint angle and joint number. The joint angle of 45°  KI had the maximum quantity. The stress intensity factor was decreased by increasing the joint number. The failure pattern and failure strength were analogous in both methods, i.e. the experimental testing and the numerical simulation methods.

This work aims to classify the gas content zones for coking coal deposits using a Number-Size (N-S) fractal modeling considering the explosive and free gas data. The case study is the C1 coking coal seam in the Parvadeh-4 coal deposit in the central Iran. Following this, the N-S log-log plots are created, which indicate three populations regarding both the explosive and gas data exist. Proper zones for both data in the C1 coking coal seam have explosive and free gas contents lower than 9.5 m3/ton and 1.3 m3/ton, respectively. The low-value gas content zone is located in the western part of the studied area, which is in the lowest depth of this coal seam. In addition, a high-value content zone exists in the E, NE, and SW parts of this area with explosive and free gas contents higher than 13.8 m3/ton and 2.2 m3/ton, respectively. These parts of the C1 seam are dangerous due to a high volume of gas content. Moreover, the explosive and free gas contents have a positive correlation with high risk gas volume based on the famous standards.

The drilling and blasting method is the first choice for rock breakage in surface or underground mines due to its high flexibility against variations and low investment costs. However, any method has its own advantages and disadvantages. The flyrock phenomenon is one of the drilling and blasting disadvantages that the mining engineers have always been faced with in the surface mine blasting operations. Flyrock may lead to fatality and destroy mine equipment and structures, and so its risk assessment is very essential. For a flyrock risk assessment, the causing events that lead to flyrock along with their probabilities and severities should be identified. For this aim, a combination of the fuzzy fault tree analysis and multi-criteria decision-making methods are used. Based on the results obtained, the relevant causing events of flyrock in surface mines can be categorized into three major groups: design error, human error, and natural error. Finally, using the obtained probabilities and severities for these three groups, the risk matrix is constructed. Based on the risk matrix, the risk numbers of flyrock occurrence due to the design errors, human errors, and natural influence are 12, 6, and 2, respectively. Hence, in order to minimize the flyrock risk, it is very vital for the engineers to select appropriate values for the design events of blasting pattern such as burden, spacing, delays, and hole diameter.

Over the past two decades, the frequency domain (FD) of the geochemical data has been studied by some researchers. Metal zoning is one of the challenging subjects in the mining exploration, where a new scenario has been proposed for solving this problem in FD. Three mineralization areas including the Dalli (Cu-Au), Zafarghand (Cu-Mo), and Tanurcheh (Au-Cu) mineralization areas are selected for this investigation. After transferring the surface geochemical data to FD, the geochemical signals obtained are filtered using the wavenumber-based filters. The high and moderate frequency signals are removed, and the residual signals are interpreted by the statistical method of principal component analysis (PCA). In order to discriminate the deep metal ore deposits, the principal factors of elemental power spectrum extracted by PCA are depicted in a novel diagram (PC1 vs. PC2). This approach indicates that the geochemical data in the Dalli and Zafarghand deep ore deposits have similar frequency behaviors. The Au, Mo, and Cu elements in these two areas are discriminated from the Au, Mo, and Cu mineralization elements of the Tanurcheh area as a deep non-mineralization zone in this diagram. This new criterion used for distinguishing the buried ore deposits and deep non-mineralization zones is properly confirmed by the exploratory deep drilled boreholes. The geochemical anomaly filtering demonstrates that the strong signatures of deep mineralization are associated with the low frequency geochemical signals at the surface, and the buried mineralization areas with weak surface anomaly can be identified using the geochemical FD data.

In this research work, the potential capability of nano-clay and tonsil, as low-cost and domestic adsorbents, for the elimination of a cationic dye, (CR18) from contaminated water is investigated. The surface properties of the adsorbents are studied by means of the scanning electron microscopy (SEM) and X-ray diffraction techniques. The effects of the initial dye concentration, pH, stirring speed, contact time, and adsorbent dosage are investigated at 25 . The results obtained show that the dye adsorption data from the nano-clay and tonsil experiments fit well to the Langmuir and Freundlich isotherms, respectively. The results of dye adsorption kinetics demonstrate that the adsorption system follows a pseudo-second-order model with a satisfactory correlation value (R=99%).The adsorption thermodynamics is also studied, concluding that the adsorption process is spontaneous and physically controlled. Under the optimum conditions (pH of 7, stirring speed of 200 rpm, CR18 concentration of 30 ppm and contact time of 30 min), the adsorption capacities of the mixed adsorbents show the maximum adsorption efficiency at the tonsil:nano-clay weight ratio of 1:2.

The precipitation of aluminum hydroxide from a supersaturated sodium aluminate solution is known as an essential production step in the Bayer process. In this work, the real precipitation process in the Iran Alumina Plant was modeled by the historical data with the help of Design Expert. According to the results obtained, the recovery is significantly improved with decrease in the super-saturation factor (α) of the solution. However, this modification was found to be the most difficult change due to the operational problems. The results obtained indicated the significant impact of the seed size on the product size. The negligible effects of the other parameters involved on controlling the amount of fine grains (< 44 µm) and coarse grains (> 150 µm) in the product showed the significance of reactivating the classification and agglomeration sections. Ultimately, it was found that the recovery process could be enhanced from 46.32% to 47.86% at a constant α by increasing the seed concentration to 400 g/L, increasing the retention time by adding two precipitation tanks and reducing the temperature of the last precipitation tank by 2 ºC (by reducing the temperature of the inlet suspension), while preserving the quality of the product.

In this work, zinc extraction from an industrial leach solution was investigated by saponified di(2-ethylhexyl)phosphoric acid (D2EHPA). The solution obtained was from a bioleaching process of a low-grade lead-zinc sulfide ore that contained 50 g/L of zinc and 6.3 g/L of iron. The selective and high Zn(II) extraction yield were obtained by modification of D2EHPA in a proposed two-step process. Firstly, a significant amount of iron (87%) was removed as sodium-jarosite via precipitation from the pregnant leaching solution (PLS) prior to zinc extraction, and secondly, the effective parameters involved in zinc extraction including the contact time, saponification degree, type of saponifier, stirring speed, pH, temperature, D2EHPA concentration, and phase ratio (A:O) were investigated. The results obtained showed that 98.4% of zinc could be extracted under the optimum conditions, i.e. 20% D2EHPA, 15% saponification degree, 650 rpm, pH 2, and an A:O ratio of 1:1 at the ambient temperature (25 ± 2 °C) during 90 s; it was 25% higher than using non-saponified D2EHPA under the same conditions. Moreover, while one theoretical step was required for the complete extraction of zinc by saponified D2EHPA, the required number of steps using D2EHPA was about three. Therefore, the advantages of the process would be two-fold: reducing the number of extraction stages and no need for neutralizing the raffinate in every extraction stage.

One of the most essential factors involved in unconventional gas reserves for drilling and production is a suitable quality facies determination. The direct core and geochemical analyses are the most common methods used for studying this quality. Due to the lack of this data and the high cost, the researchers have recently resorted to the indirect methods that use the common data of the reservoir (including petro-physical logs and seismic data). One of the major problems in using these methods is that the complexities of these reproducible repositories cannot be accurately modeled. In this work, the quality of facies in shale gas is zoned using the deep learning technique. The applied method is long short-term memory (LSTM) neural network. In this scheme, the features required for zoning are automatically extracted and used to model the reservoir complexities properly. The results of this work show that zoning is done with an appropriate accuracy (86%) using the LSTM neural network, while it is 78% for a conventional intelligent MLP network. This specifies the superior accuracy of the deep learning method.

Mechanized tunneling in rocks is based on fracture propagation and rock fragmentation under disc cutters. Rock chipping is an efficient kind of fragmentation process, while the grinding process may occur under special conditions. The cutter-head penetration is an appropriate parameter involved in order to distinguish between the chipping and grinding processes in rock cutting. In this work, the grinding and chipping processes are investigated in the Uma-Oya water conveyance tunnel in Sri Lanka. The Uma-Oya project is a water transfer, hydropower, and irrigation system in the SE part of the central highland region of Sri-Lanka. From a geological viewpoint, most parts of the tunnel route in the studied section consist of very strong and abrasive metamorphic rocks that potentially are susceptible to grinding occurrence during the boring process under disc cutters. In this work, firstly, data processing is performed in order to identify the boundary between chipping and grinding. Then the chipping and grinding processes are modeled using the practical numerical and artificial intelligent methods. In the numerical modeling stage, we try to make the modeling as realistic as possible. The results obtained from these modeling methods show that for the penetrations less than 3 mm/rev, the grinding process is dominant, and for the penetrations more than 3 mm/rev, rock chipping occurs. Also, in the numerical modeling, no significant fracture expansion is observed in the rock when the penetration is less than 3 mm/rev. Moreover, it can be seen in the numerical modeling of the chipping process that the propagated fractures come together and the chips are created.