نشریه مهندسی منابع معدنی
سال پنجم شماره 3 (پاییز 1399)

As the best linear estimator, Kriging is now a well-established method in all types of  2D and 3D modeling, including geochemical mapping, rock types modeling, geophysical mapping, and resource estimation. In general, a multi-stage approach can be used for evaluating kriging parameters. The first step in the assessment of mineral resources using linear geostatistics is to remove outlier data and to find the best de-cluster size. After this stage, variogram models in the area under study must be provided by a spherical model. In this context, investigating kriging performance has always been of interest to numerous researchers. Evaluating kriging implementation for different applications has been a growing field of study in the last few decades. Although many authors have discussed various kriging parameters, it seems necessary to conduct more detailed reviews on range searching, high and low nugget effect, as well as 2D and 3D estimations. In this paper, an optimal search range was determined using quantitative kriging neighborhood analysis (QKNA), and the utility of this search range was explored by assessing kriging efficiency. To this end, the borehole dataset of the Gol-E-Gohar No.1 mine was used. In total, 2579 samples (of length 3 m) make up the database for this study.  In this research, the dataset was divided into two zones based on their associated geological domains. Based on the aforementioned parameters, 180 estimation strategies were generated for each rock type. The results indicate that the optimal search ranges of zone 1 are 688, 226, and 152, and the optimal search ranges of zone 2 are 482, 233, and 303.

Heavy metals are dangerous for our environment due to their toxic and stable behavior in nature. These metals can change the chemical properties of sediments because they move from their sources, i.e., deposition sites, to stream of water. In this regard, mining activities are one of the major sources of heavy metal pollution in environments around the mines. In this study, to evaluate the risk of heavy metals (Cr, Ni, Cr, Zn, Pb&Mn) pollution, a dataset of stream sediment elemental concentration of the 1:100,000 scale Khoy quadrangle map was bult. Due to the fact that the sediment data represent upstream materials of sampling locations, the sample catchment basin method was applied to portray the pollutions. Then uni-element background concentration caused by lithology was calculated by the weighted average method and was applied as a reference value for calculation of sediment quality indices such as Contamination factor, Geoaccumulation index and ecological risk factor. In order to Participation in the Integrated quality indices, the elements with multivariate statistical methods such as Pearson correlation matrix, factor analysis, and hierarchical clustering were investigated. In this research, the study of contaminated basins showed that the sources of contamination were mainly due to the geological features of the area, but in some cases, mineral and human activities were very effective in spreading the contamination. Next, to prioritize the contaminated areas amount sediment discharge was calculated for each basin and according to sediment contamination level, Volumetric production potential and sediment discharge of each basin, those contaminated areas were ranked TOPSIS method.

Coupling effects of stress, temperature, pore pressure and damage on hydraulic parameters of hydrocarbon and geothermal reservoirs and their production wells show that the realistic design of the production process from these reservoirs requires a comprehensive stress-strain behavioral model. In this study, through presenting a novel definition of total damage due to the effects of high temperature fluid in porous medium, a coupled stress-strain thermo-hydro-mechanical-damage behavioral model of rock in three-axial loading condition is performed based on the effective medium theory, the concept of Biot effective stress, power probability density function and convection and conduction heat transfer. Results show that: A) Increasing Biot effective stress coefficients, rock permeability, pore pressure and temperature leads to the augmentation of the coupled thermo-hydro-mechanical damage while the increase in confining pressure reduces damage thus improves rock bearing capacity. B) As temperature increases, total thermo-hydro-mechanical damage rate decreases and its peak occurs at larger strains, C) Modified Lade failure criterion provides a more realistic prediction from coupled thermo-hydro-mechanical-damage behavior compared with Mohr-Coulomb and Dragger-Prager failure criteria. Generally, it is concluded that taking into account the concept of Biots effective stress and convection heat transfer along with power distribution function will lead to more accurate predictions of the coupled thermo-hydro-mechanical-damage model.

Drilling a certain number of blast holes per hour plays an important role in reaching the required annual mine production. Since, the proper use of the availability time of machine to drill the maximum number of blast holes is crucial. The drilling rate of blast holes is affected by various factors such as rock properties and system parameters. Thus, recognizing the effectiveness of these factors on the penetration rate of bit (PR), not only machine production can be increased but also drilling and blasting costs can be reduced in the mine. In this study to predict the PR in the selected mine, firstly, parameters of 91 holes related to 28 blasting block and in 9 various extracting benches were collected. Secondly, the sensitivity rate related to each of the independent parameters on the PR was studied using Cosine Amplitude Method (CAM). Finally, three models including non-linear multivariate regression (NLMR), artificial neural network (ANN), and fuzzy logic were produced to predict the PR. These models were validated using 12 series of data tests. It was shown that with a coefficient of determination of 0.68 and mean absolute percentage error (MAPE) of 12.15, the ANN model could predict the PR with a slightly higher precision compared to NLMR.

In each project, there is always a possibility of occurrence of hazards and risks. Accidents cause many damages such as financial and psychological problems, that may have a negative effect on the workers life. To prevent or reduce the occurrence of incidents, it is necessary to identify and manage the relevant affecting factors. Blasting is one of the events that has frequently led to accidents. In this paper, 13 factors affecting the occurrence of blasting related accidents in the mining and construction projects, have been selected according to the opinion of experts and ranked to identify the most important one. For this purpose, Monte Carlo simulation method and analytical hierarchy process method were implemented. The factors were ranked based on the opinion of 15 experts in this field. Finally, based on the obtained results, inappropriate blasting time, unprofessional personnel were selected as the most important factors. Also, blasting pattern specifications, type of explosive and rock mass characteristics have the least effect in this regard. Validity of the paper outcomes was checked with comparing the real recorded events.

Regarding variety of mineral resources, reserves tonnage, economic potentials, and geographical conditions of West Azerbaijan province, there are substantial opportunities in the province. By analyzing and selecting proper strategies and their implementation, the mining sector could operate as the leading sector of the regional economy. Assessing the strengths, weaknesses, opportunities, and threats of the mining sector in this region by employing the SWOT method were the main objectives of this research. To achieve the goals, these factors were evaluated by the contribution of elites of the sector in the beginning. By applying external and internal factor evaluation matrix, external and internal evaluation matrix and SWOT method, the most significant factors were evaluated. Subsequently, the strategy direction for the mining sector was determined, and the attractive strategies were developed. The different options were evaluated by implementing the QSPM matrix, and the superior strategies were selected. The results indicated that the strategy of joint ventures with foreign leading companies of dimension stone was recommended as the most attractive strategy due to new technologies transformation and variety in dimension stone products.

A novel bio-composite produced from coal fly ash accompanied by rhamnolipid biosurfactants was produced and used as an efficient adsorbent for the removal of cadmium from aqueous solution. Effects of initial solution pH (3-11) and absorbent to cadmium ratio (40-200) on cadmium removal, as process response, were studied and optimized using a central composite type response surface methodology. Results showed that both factors significantly affect the removal efficiency. Optimum adsorption conditions, resulting in over 99% cadmium removal, were achieved at pH 10 and absorbent to cadmium ratio of 40. Time-wise studies revealed that a maximum removal can be achieved following a classic first order model with a rate of 548.57 min-1. The cadmium adsorption on activated fly ash was also found to follow the Langmuir isotherm model with monolayer adsorption mechanism. Moreover, the bio-composite yielded a maximum adsorptive capacity of 67.11 mg/g. The selectivity study in bimetal aqueous systems using copper, lead and zinc metals also confirmed the high adsorption capacity of bio-composite. This study demonstrated that rhamnolipid-fly ash bio-composite could be considered as a promising efficient, low-cost resource material for the treatment of heavy metal polluted wastewaters.

The spent lithium-ion batteries contain valuable metals (lithium, cobalt, manganese and nickel) and organic compounds that recycle of these batteries, means recovery and production of valuable metals from huge secondary sources as well as environmental requirements. In this paper, hydrometallurgy technique was used in two steps (pretreatment, leaching of valuable metals) to dissolve the metals from spent lithium-ion batteries. In the pretreatment step, neutralized, fragmentation and separation of the various compound of spent lithium-ion batteries were investigated. Then, the dissolution of valuable metals from spent lithium-ion batteries using acetic acid (organic acid) and sulfuric acid (mineral acid) was investigated as the dissolution agent and hydrogen acid as the reducing agent. Other studied parameters are used to optimize the experimental conditions include acid concentration, hydrogen peroxide concentration, solid to liquid ratio, time and temperature. Leaching efficiency of lithium, cobalt, manganese and nickel metals under optimum test conditions in the presence of 2 M sulfuric acid, 60 °C, 80 min, 4% v/v hydrogen peroxide, and solid to liquid ratio of 30 g/L, respectively, %98.40, %99, %97.53 and %96.78 were obtained.