فصلنامه مهندسی معدن
پیاپی 51 (تابستان 1400)

Understanding the non-elastic behavior of demolished rock in the rock structures, especially after maximum resistance, is required for the stability analysis of the rocky structure. Mechanical failure theory is a method for analyzing the behavior of rocks, especially after maximum resistance. Methods based on fracture mechanics consider the behavior of the rock well, such as reducing load capacity after maximum resistance and elastic rigidity. In this research, a microstructural failure model for open and closed friction microcrack is considered, taking into account the coupling between frictional slip and damage. Therefore, the basic concepts of mechanical mechanics failure are presented first. To calculate the effect tensor, the Ponte-Castaneda and Willis (1995) homogenization pattern has been used. Then, the formulation of this model was coded in FLAC software environment and the micromechanics damage behavior model developed in the FLAC software environment was called as a new behavioral model. In order to use the developed model and validate it on a laboratory scale, a axial compressive strength test on limestone was used as the basis, and its results with acceptable numerical model were acceptable.

The extensive use of underground spaces is an index of development in countries. Choosing the right supporting system to achieve a safe and stable space is an important issue in tunnel construction. One of the methods used to classify rock masses is the Q-system. The Q-system depends on rock quality designation, joint strength, joint roughness, joint alteration, groundwater, and stress reduction factor, which are not always available. Sometimes it is not possible to access all the parameters of the Q-system due to time and cost. This paper aims to obtain the value of the rock quality index in the Q system using the most important parameters affecting it. Therefore, using the Pearson analysis method and SPSS software, the Q-system's most effective parameters are identified. In this regard, three models were selected to determine Q. The first and second models have three input parameters and one output parameter, and the third model has four input parameters and one output parameter. Using multivariate regression, a relationship to predict the Q-value using the most effective parameters is proposed. For this purpose, 140 experimental data were used, and 34 test data checked the results' accuracy. Determining the Q-value using three or four parameters instead of the six most effective parameters is the novelty of this paper. Comparing the results of the proposed relationship and the actual values obtained from the field measurements show that these results are in good agreement with each other. The results show that the second model with a correlation coefficient of 0.81 for the initial data and 0.8 for the test data and the root mean square error of 2.68 for the initial data and 2.55 for the test data has the best performance.

Implementation the appropriate approaches to reducing the risk of uncertainties in Mine production planning process, maximizes net present value of extraction plan with high degree of confidence. In Maximum upstream potential/Minimum downside risk approach, the key economic factors in final plan, should be realized with any grade distribution of reserve. With reduction the risk of project evaluation factors as downstream, the upstream potential such as reserve tonnage must be realized at the same time. For implementation of this approach with some changes, in this study, 10 different grade distribution model of the copper vein reserve were simulated with a Gaussian simulation tool in Datamine software. At next step, after implementation of technical and economic parameters, the construction of nested pits for each simulated model as extraction plans and optimization performed with the Lerch-Grossman algorithm in Whittle software. Each plan were integrated into other designs obtained from simulated models. Then, the key parameter of each plan were calculated and some plans were eliminated. The calculation of upside potential and downside risks in remaining plans performed based on supplying of 95 thousand tons feed with an 80% probability of realization and the ability to return investment of 31 billion Rial that spent on the development of the second phase of the processing plant. Finally the high priority plan was selected. The mineable reserve in selected plan was estimated about 71000 tons with average grade of 0.25% copper, which is much lower compared to the 375000 tons that estimated in the previous studies.

Prediction of gas emission before mining is difficult since it depends on a number of geology, geographical, and operation factor. The gas content is among the most important parameters for the assessment of gas emission through the coal layer both during and after the mining operation. The most important objective followed by studying the gas content is to evaluate the volume of gas that will emit upon extracting the coal from different depths, as it comprises a fundamental basis for the calculation of the required air volume for ventilating the coal mine. The large amounts of gas released during mining present concerns about sufficient airflow for ventilation to ensure worker safety. Hence, the functions of mine ventilation system are vital for an underground mining system. In the present study, the central data from a total of 64 exploratory boreholes was utilized. Once finished with identifying the most important coal layers in terms of gas emission, the variogram modeling as performed to define the distribution of the gas content across the coal layer. Subsequently, simulations were performed to stochastically assess the gas content. So, an approach is provided for the prediction of gas emission based on a random simulation method, Monte-Carlo Simulation (MCS). For this purpose, six factors are selected for predicting methane emissions including main layer gas content, main layer thickness, advanced rate, production rate, adjacent layer gas content, adjacent layer thickness and main layer distance from adjacent layers. The result shows that the prediction model has enough prediction accuracy for application of actual engineering in the coal mine. The predicted value is also essentially consistent with the actual value and the prediction method based on the uncertainty theory is reliable.

Kriging weights are calculated regarding the sample distances from the estimation point without attention to the sample values. This problem of kriging shows the necessity of developing new methods that consider both distance and sample values for assigning appropriate weights to the samples. In this study, a combination of the Gumbel and Clayton Archimedean copulas is proposed to describe spatial structure of two data sets. One of these sets includes some simulated physico mechanical properties of an andesite quarry and the other one contains borehole data of a porphyry copper deposit. The combined copula was able to describe various kinds of spatial structures with asymmetric upper and lower tails at different lags. The jackknife cross-validation test showed better performance of copula over ordinary kriging such that the mean values of variables were better estimated through the copula method. Correlation coefficients between the estimated and real values were higher for copula than kriging. The copula results had lower mean squared errors and this method better reproduced the data distribution. The kriging performance was severely affected by the variables’ distributions such that for highly skewed variables it showed the worst results. Moreover, accuracy and precision of the kriging results are inversely correlated with the amount of nugget effect. In contrary to kriging, marginal distribution and the nugget effect have far less impact on the copula’s performance. Therefore, this study strongly suggests copula approach for geostatistical estimation due to its flexibility in describing various spatial structures and outperforming ordinary kriging that consequently results in better economic evaluation.

Following the reduction of fresh water resources and the growing need of society for these resources, the reduction of fresh water consumption in industries, especially the copper industry, is considered. In addition to water recycling, the use of seawater and treated water can be considered as alternatives. Since the highest water consumption of copper and molybdenum sulfide minerals processing is in the flotation unit, the purpose of this study is to investigate the changes of water quality on the efficiency of rougher flotation unit. The results showed that in similar operating conditions, the use of seawater reduces the recovery of copper sulfide minerals from 89.2% to 68.8%. However, the recovery of flotation when using treated water was 80.89% which is close to recovery when using well water (89.20%). Molybdenum recovery in both cases was approx. 100%, compared to 59 percent for seawater. Therefore, the use of treated water can be a good alternative to well water (current conditions).

Nowadays, one of the intractable challenges facing the minerals industry is the processing of complex ores. Processing of high sulphur content ore type is a major challenge in iron ore beneficiation. Thus, modification of mineral processing circuits to process iron ore with high sulphur content is essential. In this research, employing a regrinding section in iron ore concentrator aiming to reduce the particle size and improve the quality of concentrate in Golegohar concentrator line no. 4 was investigated. In this order, two different configurations were studied including regrind mill after high intensity (rougher, cobber) and low intensity (recleaner) magnetic separators. To assess the results of the circuit configurations, iron and sulphur grade, yield and blaine of concentrate were considered. Furthermore, the effect of particle size fractions with the d80 of 38, 45, 63 and 80 μm in the configurations was evaluated to find optimum particle size. Results indicated that the desired particle size in the reduction of sulphur content is +63-80 μm. Furthermore, utilising regrind mill after cobber resulted in a higher iron grade, yield and blaine while lower sulphur grade was attained with the regrinding after recleaner.