نشریه مهندسی منابع معدنی
سال پنجم شماره 2 (تابستان 1399)

Execution of exploration activities is costly and time-consuming, which reveals the necessity of mineral prospectivity mapping (MPM) for identifying highly mineral potential zones. In this regard, the present study introduces a new hybrid method called SWARA-MOORA, through which different evidence layers can be integrated to map Cu highly potential zones in the Abhar area. Thus, based on expert judgments, six evidence layers as targeting criteria was considered. For fulfilling the integration process, the spatial values of predictor maps were initially transformed into a new space ranging [0,1] and then were categorized by C-A fractal-based model to determine thresholds of favorable populations. To generate the overlay prospectivity map pertaining to the mineral deposit of type sought, SWARA method was used to determine the weights of criteria and sub-criteria and MOORA was concerned with order preference of decision alternatives. In order to evaluate the efficiency of SWARA-MOORA overlay prospectivity map, the Predication-Area (P–A) plot along with normalized density (Nd) was used. This predictive map foresees 19% of the study area as prospective areas through which 81% of the known Cu occurrences are ascertained. The relevant Nd is 4.26 that affirms that SWARA-MOORA overlay prospectivity map can be applied efficiently as a target map for subsequent detailed explorations.

Due to the role of recovery in calculating the economic value of ore blocks and the impact of the block's economic value on the design calculations of the final pit and production planning, determination of the amount of metal recovery from the ore material sent to the processing plant is very important. The aim of this study is to investigate the capability of estimating the recovery rate of ore in qualitative manner with three methods based on data classification from data mining techniques and quantitatively using multivariate regression and artificial neural networks. Hence, the Miduk copper mine was studied using 58 analyzed samples of the feed of the plant, including Cu, CuO and CuS grades, and the recovery rate of Cu in the final product of the plant. The process of predicting the total recovery of the reserve was made qualitatively by decision tree method, classification based on Bayes rule and k-nearest neighbor (kNN) classification algorithm. For quantitative estimation of recovery, multivariate regression and artificial neural network models were established between the mentioned grade parameters and recovery rates (For 47 samples of 58 samples) and with the 11 additional analyzed samples, the obtained models were validated. The coefficient of (R2), Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) in the regression model were 0.77, 0.027722 and 0.029722, respectively, and in the artificial neural network model, 0.82, 0.015753 and 0.024040, respectively. Therefore, the artificial neural networks model acts as a more accurate tool for predicting recovery versus the multivariable regression model. The results of sensitivity analysis of artificial neural network model showed that Cu grade is the most important factor and grade of CuO and CuS, respectively, as well as other factors influencing the changes in recovery rate.

Mechanized excavation of the large cross section tunnels in rock condition has some hazards. Machine purchasing costs, fault zones, water inflows, squeezing, face instability, and etc. are some of the hazards which may cause excavation stop for a long time. In addition to mechanized excavation advantages, machine inflexibility in the complex geological conditions, high investment costs, technical, geometrical and political risks are the major disadvantages. Due to the high investment costs in this method, assessment and ranking the mentioned hazards are of a great importance. In this study, the tunneling risks of Alborz Western Tunnel (AWT) has been investigated using the fuzzy multi criteria decision making methods. The AWT in Tehran Shomal Highway is one of the major country project that considered to be excavated by an EPB shield machine. By analyzing geological condition and survey of some specialist's point of view, in this study, 17 possible hazards have been identified, and assessed by fuzzy TOPSIS and ELECTRE methods. Results shown that insufficient experience in mechanized tunneling of the large diameter tunnel and gas emission in the tunnel and investment and purchasing the machine are the most important risks in the project.

In the case of explosions and fires, the rocks undergo cycles of heating and cooling, that is, they are exposed to considerable heat first and then cooled after extinguishing the fire. The purpose of this paper is to study how the temperature in a heating-cooling cycle can affect the physical and mechanical properties of travertine. In Iran, travertine stone is widely used for building facades, so travertine was chosen as the material of study. In this study, three types of travertine (Travertine B, Travertine D and Travertine R) were studied. The effective porosity and permeability at 25 °C for Travertine B is greater than Travertine D and Travertine D is greater than Travertine R. Also, the longitudinal wave velocity, tensile strength and uniaxial compressive strength at 25 °C for Travertine B are lower than Travertine D and Travertine D is lower than Travertine R. During the heating phase in a heating-cooling cycle, experiments were performed on specimens that were initially exposed to temperatures of 150, 300, 500 and 800 °C and then cooled gradually to ambient temperature. A series of experiments were performed on specimens that were not exposed to a heating-cooling cycle. This paper investigates the effect of the heating-cooling process on its physical properties including effective porosity, longitudinal wave velocity and permeability, and its mechanical properties including tensile strength and uniaxial compressive strength. The results showed that as the temperature increases, the effective porosity and permeability increased and the longitudinal wave velocity, tensile strength and uniaxial compressive strength decreased. The highest increase in effective porosity and permeability due to increasing temperature was related to travertine B and the lowest increase was related to travertine R. The highest decrease in longitudinal wave velocity, tensile strength, and uniaxial compressive strength due to increasing temperature was related to travertine B and the lowest decrease was related to travertine R.

The purpose of this research is to design and explain the health, safety, environment and energy education model in the mineral industry. The statistical population of the study was all health, safety and environmental education specialists.  Sampling was performed purposefully. Data were collected by a researcher-made questionnaire (48 items). Verbal and content validity of the tool was confirmed by experts and its reliability was confirmed by Cronbach's alpha. The data are analyzed using exploratory factor analysis and structural equation modeling using the least squares method or PLS method. The findings showed that educational process has four components of educational needs assessment, design of educational program, implementation of educational process, assessment of educational process which affect the productivity of health, safety, environment and energy education in mineral industry. Average Variance Extracted each were 0.565, 0.593, 0.602, 0.773, respectively. Also, these components were able to explain 543% of variance of the productivity education. The model fitted well. Also, the size of the extracted effect showed that the implementation of training (39.169) had the most effect on educational productivity. Also t values in all directions of the model were more than 1.96 and all the research hypotheses were confirmed. According to the results, the designed model is suitable for fitting and can be used in health, environmental and energy education in the mineral industry.

In the conventional mass balance methods, sampling are carried out to determine the metal content, solid percentage and particle size distribution in the paths (branches) and ultimately the corresponding errors are dispersed. In these methods, there is no information about the amount of feed and the grade (or the metal content) at any moment of time for each mineral processing unit (plant equipment). Thus, in this paper, the quantitative and qualitative values of input feed to each of the operating units in the processing paths were probabilistically investigated using stochastic process theory, and consequently the load distribution in these units was estimated. For this purpose, the processing plant was firstly modeled as a directional and balanced graph. In this graph, each node represents an operating unit and each edge displays a path between two units. The weight of each edge also indicates the passing material weight from the node to another node, which is assigned as a random variable at a specified interval. After modeling the process, the obtained graphical model containing random parameters was analyzed using Markov chain theory. Applying the philosophy outlined in this paper, not only the load distribution, but also the presence probability of each particle or mineral in each of the operational units of the processing plant can be predicted. It is also possible to estimate the tonnage in each unit when the plant is shut down and even the necessary steps are provided to discharge them. In this research, Chadormalu iron ore processing line was modeled using method presented and the results were analyzed and thereafter were reported using probabilistic parameters.

In Lines 5 and 6 of Gol Gohar Mineral and Industrial Complex the special surface of concentrate (Blain) is increased by the high pressure grinding rolls equipment (HPGR). At present, due to changes in the input feed of the plant, the magnetite concentrate moisture has increased. Increasing the moisture content of the material will reduce the HPGR operational gap, thereby reducing the feed rate and the effective pressure on the particles. As a result, Blain Concentrate will not be desirable. After checking of the process, it was determined that the parameters of vacuum pump pressure, filtration time, solid particle size and solid pulp percentage were effective on the filtering process. For this purpose, filtration experiments were carried out at different levels of each of the above parameters. In this research, four types of surfactants SDS, PEG, CTAB and SLES were used to study their effect on moisture reduction and filtration process. The results showed that the optimal conditions of the process parameters to achieve the minimum moisture content is 60 Kpa operating pressure, optimum dewatering time was 120 seconds, particle size 105 microns, proportional to the separation of Hydrocyclones and 60% solids content of pulp proportional to transfer equipment. Surfactant experiments showed that by adding 100 g/t anionic surfactant SDS to the pulp, the filter cake moisture content was reduced by 2%. The SDS increased filtration efficiency by decreasing the time of forming the filter cake and increasing the filtrate volume, especially at the time of forming the cake. The use of SDS improves filtration performance by increasing the ratio of throughput to moisture. At a concentration of 100 g/ton SDS and SLES, the lowest moisture of filter cake and the highest throughput was achieved. The ratio of throughput to moisture content for SDS was highest compared to other surfactants. SLES was selected with the same results as SDS at a concentration of 75 g/t, and because of its cost-effectiveness and availability, it was chosen as the final filter aid.

The effect of shell liners on mill performance has been the subject of various studies, but little known about the effect of dry SAG mills end liners on throughput and grinding efficiency. In particular, in the case of dry Aerofall mill types where it has been claimed that the end liners play a key role in the crushing and grinding actions. This paper experimentally characterizes the role of end liners in dry SAG mills with the objective of obtaining a thorough understanding of the effects of end liners design on the load trajectory and SAG mill performance. It was thought the characterization study will lead to design new end liners which eliminate or reduce the shortcomings of the current liners and improve the comminution efficiency mainly by prolonging liner life. The test works conducted in a scale down mill with a diameter of 1m indicated that conventionally used "deflector" type liners did not provide efficient environment for grinding. Direct observations obtained from the model mill during tests by various visualization techniques, along with simulations using the KMPCDEM software were the main sources of understanding flow behavior of charge inside the mill. In this research, to improve the grinding efficiency, a new design using low profile end liners incorporating radial ribs of proper height was investigated. The special design of model mill made it possible to increase the radial ribs height in steps of 6mm up to 18.5mm. The transparent end of the mill enabled accurate trajectory determination by image analysis. The results indicated that the new lower height profile deflectors and 15.5mm-height (14.5cm in industrial scale) radial ribs improved the mill performance while avoiding excessive pressure drop across the mill and wear on the liner. The image analysis showed that the use of new liners increased the distribution of coarse particles across the mill cross section from 28% to 35%. A new liner design was proposed by decreasing the number of liners in each slice from 5 to 4 pieces. The thickness of the inner head liners reduced from 45cm to 30cm and the outer deflector liners replaced by14.5 cm radial ribs. The distance between the feed and discharge liners increased from the original 115cm to 176cm which increased the effective length of the mill by 53%. The new design reduced the weight and volume of end liners by 9% and 23%, respectively. On account of installation of the new liners in Aerofall SAG mills the throughput increased from 441 to 465 t/h, the product size decreased from 519 to 480 μm and the amount of recycled material from the SAG mill product decreased from 10 to 6%. The most significant improvement was observed in the liner life; an increase of 50 to 200 % in liner life depending on the location of end liners was achieved. The relining time also reduced by 37.5% with the new liners.