فصلنامه مهندسی معدن
پیاپی 60 (پاییز 1402)

The topic of placement of infill drill holes and providing an optimal pattern for drilling drill hole has long been of interest in the mining process and has become an inseparable part of it. The root of this importance can be found in the financial issues related to the mining process as well as the exploration and extraction sector and issues related to classification. In order to reach an acceptable level of uncertainty, the estimation error method was used in this research to classify the blocks. Also, in order to place supplementary drill holes and weight potential drill holes, CRITIC and TOPSIS methods were used. The CRITIC method was used to assign weight and the TOPSIS method was used to select 5 of the best drill holes. At first, the drill holes were weighted by CRITIC method and with expert opinion, and then they were graded by TOPSIS method. The criteria used for the TOPSIS method include the grade of iron, weight percent grade of remaining iron (geometallurgical component), variance, error of estimation and classification. Finally, after placing the 5 wells in question, the estimation and classification process was carried out again, based on the number of definitively classified blocks, it was increased from 380 to 571, and the estimated average grade of iron also increased and 19% improvement in the classification was obtained. The improvement achieved in the number of blocks with definite classification adds to the certainty and reliability of the model.

The valuation of a mining project is always under uncertainty due to the very complex nature of the deposit. Therefore, in order to evaluate the project more accurately, sources of uncertainty should always be identified and analyzed to increase the net present value. One of the most important sources of uncertainty in a mining project is the price and operating costs that have a significant impact on the net present value during the implementation of that project. According to many researches related to the evaluation of mining projects under conditions of uncertainty, they showed that the use of the real options approach had a significant impact on increasing the net present value of mining projects. In this paper, using the real option approach, according to the case study that was carried out in the Sangan iron ore mine project, an option under the title of low-grade iron ore stockpile (grade less than 35%) and iron ore stockpile with oxide percentage less than FEO<10% defined. The purpose of defining this option is to check the right time to sell low-grade iron ore and iron ore with low oxide percentage, which as a result, according to the technique of real options, can lead to the profitability of the project and increase the net present value.

Due to the significant advancement in the mining and tunneling industry, the depth of underground excavation has been considerably increased. As a consequence of increase in depth, the intact rock strength plays a significant role in rock mass failure. Therefore, the study of intact rock failure has become more crucial. Crack damage stress and crack initiation stress are the two important characteristics of intact rock failure, which have been studied rarely in the shear failure process. This study aims to investigate the crack damage and crack initiation stresses in the shear failure by numerical modeling of direct shear test (DST) using the discrete element method. First, the micro-mechanical properties of the numerical model were calibrated against physical experiments in uniaxial tension, uniaxial compression and triaxial compression tests. Then, the numerical models were validated by comparing against physical direct shear tests under different normal stresses. By undertaking the DST under eight different constant normal stresses, these two stress levels have been studied in brittle, brittle-ductile transition and ductile failure modes. It was revealed that the crack initiation and crack damage stresses occur in 70-91 and 85-95 percent of the peak shear strength, respectively. Also, it was observed that the ratio crack initiation and crack damage stresses to the peak shear strength decrease with an increase in the normal stress. The outcomes would be useful for studying the structures under shear stress like landslides and rock bolts.

Calculation of variograms and spatial continuity is one of the first and most important processes in geostatistical modeling, which is a long and experience-oriented process. Due to the complexities of calculating experimental variograms, interpretation and fitting the appropriate model are always the main challenges in this field. This article presents an intelligent variogram modeling method using deep learning that can increase the speed of variogram modeling and also prevent common errors in manual variogram model fitting. In this method, two convolutional neural networks are used. The first CNN network converts the initial data into a 2D simulated map based on various variogram models. For this purpose, it is necessary to train the first network with initial data and their corresponding simulations. The output of this model is entered into the second convolutional neural network as input, and the variogram parameters (including range, azimuth, ratio, and nugget effect) are predicted. In this article, the proposed algorithm is implemented on synthetic 2D data and the parameters of the CNN models are optimized. The accuracy of the proposed model was 97 %, and then the proposed algorithm was used for variogram modeling of Nouchon area geochemical data, which included the elements Cu, Zn, and Pb. the accuracy of the obtained model compared to manual fitting was 90%.

Selection of tunnel excavation method is one of the most important issues raised in the tunneling projects Because experience has shown that the results of incorrect choice of excavation method can lead to catastrophic situations. Various parameters are effective in choosing the right option for excavation a tunnel. The most important parameters include geological and geotechnical, geometric, executive, economic parameters and parameters related to infrastructure and necessary conditions for tunneling methods. in this research, a model for comprehensive evaluation and selection of the most suitable tunnel excavation method from the methods of drill and blasting, controlled drill and blasting, cut and cover, Austrian drilling method, road header machine and conventional shield excavation (TBM) is presented.In this model, after studying and reviewing the relevant topics, the indicators that are effective in evaluation were considered and since the importance of the indicators in the evaluation is not the same, a questionnaire was prepared to determine their weight and their weight was determined by aggregating the opinions of experts. Scoring for each of the indicators for each of the excavation methods was done by evaluation questionnaires containing questions in numerical quantification. Finally, the simple weighting method (SAW) was used hierarchically to calculate the final score of each method. In this method, according to the geological and geotechnical conditions and the geometric parameters of the existing tunnel, the score of each index is multiplied by the final weight of that index and from the sum of them, the final score of each method is obtained. Finally, the method with the highest score is selected as the appropriate excavation method.