فصلنامه مهندسی معدن
پیاپی 5 (زمستان 1387)

In open-pit mining operations, one of the first decisions that must be made in production planning stage, after completing pit limits design, is to determine processing plant cut-off grade. In order to maximize economic payoffs of operations, choosing optimum value of cut-off grade is of considerable importance. Using Lane's model is one of the most common methods for doing this task. This model is based on Operations Research (OR). Its objective function is maximizing difference between cash-flow and opportunity cost, and its functional constraints are mining capacity, processing plant capacity and market demand. Finally, this model is converted to a model with two decision variables namely (cut- off grade) and (time required for processing 1 ton of in- pit materials). Since formulating objective function and constraints of model as mathematical sentences is usually impossible, for solving it graphical or heuristic methods have to be used. Lane has developed a heuristic method for solving his model. In this article a new heuristic method for solving Lane's model has been developed. Then by solving an illustrative example in two methods and comparing their results, has been showed that the result of this method is better than result of Lane's algorithm.

In any mining project, specially when the ore reserve is relatively large and distributed inhomogeneously, drilling new boreholes to reduce the uncertainty associated with the grade estimation as well as reserve classification becomes unavoidable. However, selecting the optimum location of the new borehole, in terms of providing the maximum amount of information possible is a challenge. In this regard, customarily, the geostatistical approaches, based on minimizing the estimation error (variance) of blocks grade is used. However, in this method, the estimation variance of each block is independent of the sample grade values and only takes into account the spatial distribution of sample’s location. This will ignore the local variability of sample values. Another approach to determine the optimum location for the new drilling boreholes could be based on the geostatistical simulation techniques. In simulation methods, the spatial variability due to the sample location, as well as the local variability associated with the data values are taken into consideration. In this paper, the Fractal Conditional Simulation Method (FCSM) is used to simulate the iron grades of anomaly No.3 of Gol-E-Gohar iron ore mine. The simulated data, then, were used to estimate the iron ore reserve and to perform a risk analysis. This method simulates the data sets, while the fractal co-dimension as well as the statistical and geostatistical parameters are kept unchanged. Finally, using uncertainty index and GET (Grade, Error and Thickness) function, the optimum location for new boreholes in the northern part of the ore-body was suggested.

Many underground rock masses are usually subjected to multiaxial states of stress. Moreover, cracks are known as candidate locations for fracture extension. Therefore, it is important to investigate the fracture behavior of cracked rock masses under such multiaxial stress states. However, most of the previous investigations have focused on the ambient conditions and ignored the effects of confining pressure, which in reality exists for in-situ stress conditions. In this paper, to investigate the effects of confining pressure on the mode I and II stress intensity factors (KI and KII), a large number of 3D finite element models have been used for simulating two test specimens, a circular and a semi-circular disc with a center crack. The specimens are subjected to diametral compression load F. For simulating the confining pressure, a uniformly distributed pressure (Pm) is applied to all of the external faces of the specimens. By analyzing the created models for various crack lengths, crack angles and confining pressure values, the effect of Pm on the stress intensity factors is studied. The results show that the presence of confining pressure has a significant influence on the mode I stress intensity factor but it has little effect on the mode II stress intensity factor.

There have been some efforts to investigate shear mode of fracture using rock specimens by different methods in the recent years. Most of the fractures occurring in nature are of the shear, tensile or the combination of both. The determination of Mode II fracture toughness is important for understanding and analyses of the failure process in rock masses. The comprehensive investigations in the methods of determination of Mode II fracture toughness of rocks indicated that punch and shear box tests are reasonable, although there may be still some illusions. Artificial neural networks are capable to establish logical relationship between different variable parameters in order to predict the value of Mode II fracture toughness. In an effort, the test results obtained from punch and shear box tests along with some affective parameters are considered to predict Mode II fracture toughness through neural network models. Thus an optimum network was established and the precision was evaluated. A comparison of the neural network results is made with the linear regression. The details of the investigation are presented in this paper.

One of the problems of tunneling in urban area, in a shallow depth, is encountering load-bearing piles of heavy structures such as bridges, which could endanger the stability of tunnels. In this paper, by a three-dimensional analysis, using Plaxis 3D, a study was carried out to investigate the effects of different parameters relevant to piles such as diameter, length, load on pile and the distance between piles and tunnel on the stability of tunnel. The results obtained show that, the pile length and loading have the most effect on tunnel stability.

SPE developed as an application software tool to select the equipment in mining operations and includes drilling, blasting, loading and haulage and primary crushing. The algorithm of the selecting drilling equipment were designed base on hole diameter. With aspect to the effect of blasting hole diameter on fragmentation and for determining the bucket fill factor, at first, the software could able to design blasting pattern. After that, loading and haulage capacity of equipment determine through classic equations and the effect of bucket fill factor and then primary crusher is selected by dimensions of broken ore. At the end, equipment are selected by minimizing total expenses. This tool can select blasting hole diameter, design blasting pattern, estimate fragmentation, select drilling method and it’s equipment, select the loading and haulage equipment and calculate their quantities and select primary crusher. Also, it estimates total operational expenses of production and compare them for different hole diameters. Finally, SPE selects a hole diameter with the lowest mining operational expenses. SPE found suitable for prefeasibility and feasibility studies in mining projects.

In many cases, analysis of mine ventilation networks by ordinary mathematics is impossible and we have to use numerical methods. Newton – Rephson method is one of them which is being used for solving the mathematical equations. Although this method is used for analysis of water distribution networks, but in mine ventilation networks has not been used. In this paper, using of this method for solving the H equations is discussed.

Zinc oxide nano particles have many applications including food, medicine, tube and electronic industries. Zinc oxide nano powder can be produced using new and different methods. In this study precipitation transformation method was used to produce zinc nano oxide from concentrated oxide of Angoran mine in Zanjan Province of Iran. At first, acidic leaching, neutral leaching, hot and cold purification were carried out and then the final product of to ZnSO4 precipitation method in order to ZnO nano powder was used. Six parameters such temperature, time, mixing rate and NaOH, Na2CO3 and ZnSO4 concentrations in four levels were employed for the experimental design. The optimum condition were found when the Na2CO3 solution and NaOH had the concentration of 1M at the temperature of 80⁰ C and the time and mixing rate were not much effect on production of nano powder. Then NaOH solution was dropped into the precursor. The final production was the Zinc Oxide nano sized. Then ZnO nano powder is variable in size from 70nm to150nm.