فصلنامه مهندسی معدن
پیاپی 56 (پاییز 1401)

Mining and mineral industries supply raw materials to many industries and play an important role in economic self-sufficiency, productive employment, increasing economic growth and per capita income. However, despite the mineral benefits that Iran enjoys, the mining industry has little place not only in the country's exports, but also in national production. In this regard, the main purpose of this article is to review and evaluate the performance of 16 mining companies operating in the Tehran Stock Exchange to evaluate their performance, the most efficient companies to be introduced as role models for other mining companies. In this study, using nonparametric method and data of Kadal Publishers Information System in 1398, the efficiency of mining companies operating in the stock market has been evaluated with two assumptions, constant return to scale and variable return to scale. The results of this study showed that the scale efficiency is 80% and the average management efficiency is 74%. This means that the subdivisions of mining companies, assuming the stability of other conditions, in terms of scale and management, have empty space, in other words, the factors used such as manpower, mining equipment, transportation and heavy and light equipment in a They do not use optimally. Other results of the study showed that the average efficiency of the listed mining companies in the country is 62%. Due to the model of Damavand, Gol Gohar mining and industrial companies, Chadormelo mining and industrial companies and the development of mines in Iran, mining companies are recommended. Inefficiently to imitate them in order to increase efficiency.

Mining industry has an essential role in the economic and industrial development of a country by providing minerals. However, the mining industry faces considerable challenges in the field of environmental health and safety of its staff. The mining industry is a high-risk activity and a large number of miners are injured/killed each year. The problems related to miners' safety due to the exceptional condition in underground mines are more complicated. To reduce hazards and risks in the case of underground mines, identifying the most important factors that affect hazards is significant. Thus, controlling the accidents is possible as well as safety will increase by distinguishing the effective factors in the underground mining risks. In this study, 21 factors that have significant roles in underground mines accidents are identified. The factors classified into three categories, i.e., direct factors, work environment factors and systematic factors. These factors were evaluated using the fuzzy cognitive mapping (FCM) method and the casual-effect relationships between them specified. Notably, theory of Z-numbers used to overcome the uncertainty corresponding to causal relationship between the factors. Finally, the relationships between concepts were analyzed utilizing a hybrid learning algorithm and the final weight of each factor was obtained during 30 iterations. The obtained weights were prioritized and the results showed that the "falling" and "insensibility to hazards" factors with weights of 0.999 and 0.641, respectively, have the highest and lowest impact on the occurrence of underground mines accidents. It should be noticed that the factor of the fall, simultaneously with other factors, affects the occurrence of accidents in underground mines.

In this study, the assessment and reserve estimation of the IV (Madanjo) deposit as one of the eastern anomalies of Sangan iron mines, has been done using geostatistical methods. The used data in this study include topographic data and 49 boreholes information with a total drilling of 8549 meters. Reserve modeling was performed by SURPAC software and statistical analysis was done using SPSS. The dimensions of the blocks according to the distances of exploration works, in the direction of X and Y are equal to 25 meters and along the axis of Z is equal 10 meters according to the bench height in the western and central anomalies. Also, sub-blocks were added along the mineral boundaries in the model and 2100 blocks were built.The reserve estimation of IV deposit has been presented based on different values of cut off grades using kriging and inverse distance square methods. The estimated tonnage based on 20% cut off grade with the kriging method is equal to 12985979 tons and in the inverse square method is 12907748 tons.

Froth recognizing as the output of the flotation process can be efficient in better control of this process. Since the physical structure of the froth indicates the operational conditions of the flotation cell, the quality of the separation can be estimated according to its characteristics. Technological advances have led to monitoring and control operations using online systems. Image analysis method is one of the growing methods in this field. In addition to control the structural changes of the concentrate, using a device that can measure the quality of the froth online and report it regularly can keep the amount of chemicals consumed in the cell at optimal levels, and provide stability in the separation efficiency of the flotation unit. In this paper, changes in the froth structure of cleaner cell of Sungun copper processing plant were investigated. The area, circumference, elongation and diameter of the bubbles and their distribution, which are structural features of the froth, were calculated online to control flotation cell changes and used to classify the froth. Froth images were clustered in three classes of dry, wet and stiff froth using K-means algorithm and two characteristics of bubble fret area and diameter. The results showed that in dry froth, bubbles of froth surface are in a wider range of dimensions. This type of froth is in optimal condition in terms of load, mobility, stability and structure, also the grade of this type of froth is in the range of 25 to 29. Though, unlike dry froth, wet and hard froths are not in optimal condition in terms of bubble load, mobility, stability and structure due to the use of more or less excessive chemical additives. Also, the grades of wet and hard froths are in the range of 22 to 27 and 20 to 24, respectively.

In mechanized mining and tunneling operations, the interface of existing rock layers poses a variety of challenges including cutter failure, machine vibration, and low advance rate without prior notification. As a result, proper understanding of the cutting process and the tool-rock interaction is critical for machine design in these circumstances. In this study, a lab-scale investigation on the interaction between rock and tool to determine the cutting forces at transition zone was carried out in mechanized excavation laboratory of Tarbiat Modares University using a small-scale linear cutting machine equipped with a disc cutter of 54 mm in diameter. Three types of samples were used in the study: sandstone with a strength of 37 MPa and two types of synthetic gypsum with strength of 21 and 24 MPa, in a mixed condition. Experiments with linear cutting machine were carried out at cutting depths of 1, 2, and 3 mm. Laboratory studies revealed that as the cutter approaches the interface between two soft and hard specimens in mixed specimens, the normal and rolling forces vary dramatically, and the difference in the ratio of forces in the transition zone diminishes as the cutting depth increases. It was also revealed that the ratio of boundary cutting forces to rock cutting forces in unmixed mode reduces as cutting depth increases. Taking into consideration the highly variation of cutting forces pattern at the interface, the importance of selecting appropriate cutters for tunneling machines and mechanical excavators increases in the field conditions. Also, it was revealed that the difference in cutting forces results in shock load at the transition zone where the cutter passing the interface of two rock layers. This shows the importance of proper design of cutter in respect of toughness and hardness and its impact in reducing cutter failure in mixed face conditions.

The most critical problem of using edge detection filters is determining the horizontal boundaries of gravity and magnetic anomalies with different depths and integrating the effect of adjacent anomalies, which are diffused in geophysical maps. In recent years, edge enhancement filters having different performances have been provided to solve this problem. Edge detection filters are usually a combination of horizontal and vertical gradients with different orders to determine the boundaries and edges of gravity and magnetic anomalies data with different quality and accuracy. In this study, the efficiency of filters to determine the edge of potential field anomalies, including total horizontal derivative (THD), analytical signal (AS), tilt angle (TA), theta map (TM), the hyperbolic tangent of tilt angle (HTA), normalized total horizontal derivative (TDX), sun shading (SS), generalized derivative operator (GDO), and the improved logistics function (IL) are tested on potential field data. The efficacy of edge detection filters was evaluated using two synthetic gravity and magnetic models with and without Gaussian noise. The results reveal that the improved logistic filter outperforms existing edge detection filters in terms of accuracy and quality in determining the edges and boundaries of synthetic anomalies. This filter also prevents drawing erroneous or spurious boundaries, which complicates interpretation. Subsequently, applying an improved logistic filter on the real data of the Tuzgolu (Salt Lake) region of Turkey shows that this filter can detect the boundaries and edges of anomalies, even deep anomalies within the study area. In general, the data acquired using edge determination filters and a much improved logistic filter can be employed in qualitative interpretation for 3D modeling of subsurface structures and detecting faults and fractures.

This research aims to investigate magnetic anomalies and Interpretation and modeling of 2D and 3D magnetic data of Iron mineralization at Darreh-Ziarat deposit in the Kurdistan province, West of Iran. For this purpose, more than 2000 survey stations were recorded. The magnetic survey has been done at profiles with a distance of 10 m and station distance of 10 m. After correcting raw data, RTP and upward continuation filters were applied to interpret magnetic data. In the next step, the anomaly depth was estimated by Euler and Euler-Analytical signal methods. The approach proposed by Li and Oldenburg was used to generate a 3D model of magnetic susceptibility property using MAG3D software. For this purpose, the study area was divided into 3D cells and one value of susceptibility was allocated to each cell. According to this model and other maps of magnetic interpretation, the mineralization trend was determined. Finally, Drilled boreholes were utilized to validate the 3D magnetic inversion model.