r. kakaie

The first production cycle in open-pit mines is the drilling of blast holes, which is a major part of the exploitation costs. Bits are considered as one of the most important parts of drilling in operational processes due to the type of application and high costs. Examining the parameters affecting the bits wear can reduce the effect of wear, prevent wasting time and additional costs of the drilling process. Therefore, in this study, first, by determining the effective parameters based on the results of univariate regression and Principal Component Analysis (PCA), the relationship between these factors and the tricone rotary bits wear has been determined through statistical methods. Then, 100 linear and nonlinear models were examined to predict the rate of the tricone rotary bits wears during drilling, of which only 21 models, including 6 linear models and 15 nonlinear models, were approved. The performance of these models is evaluated based on the root mean square error (RMSE), coefficient of determination (R2), Variance accounted for (VAF), and mean absolute percentage error (MAPE). then the priority of each method is determined based on performance evaluation and prioritization strategies. In this research, three strategies of prioritization, the Rank average method, the Borda method, the Copeland method, and finally the Aggregate of these methods have been used. The ranking results show that the best model for predicting the tricone rotary bits wear is the regression model with independent variables of Weight on Bits (WOB), Uniaxial Compressive Strength (UCS), and Geological Strength Index (GSI). According to the results of sensitivity analysis, the Rij value of the Weight on Bits (WOB) is 0.982, which is more than the other two parameters of the final model. Therefore, this parameter has the greatest effect on the tricone rotary bits wear and it is the most important parameter of the final model.

In terms of longitudinal ventilation design, critical velocity and its estimation are the two most important parameters in a tunnel fire. Critical velocity must be accurately selected to provide safe conditions in a closed environment such as tunnels. This study is focused on fires in curved tunnels using a small-scale model (in a 1/20 scale) experiments and Computational Fluid Dynamics (CFD) simulations. Heat Release Rate (HRR) is considered as one of the key parameters in all numerical studies and physical experiments of the fire. In this study, a numerical study was carried out to evaluate the Heat Release Rate in pool fire Simulation in FDS software and small physical scale experiment. In the first step, grid sensitivity analysis and its impact on HRR estimation were investigated. The critical velocity of the physical model was equal to 0.90m/s and 0.92m/s in the numeric model. After data validation, it was concluded that increasing the HRR increases the critical velocity, so based on the results of the changes, it can be seen that this parameter is very important in estimating the critical velocity. But, this trend only dominates a certain range and the results show that outside of this range, the critical velocity is independent of the amount of HRR. On the other hand, the trend of increasing the critical velocity compared to the heat release rate for the curved tunnel, with a difference of about 10%, is in a higher position than the straight tunnel.

In mining projects, all uncertainties associated with a project must be considered to determine the feasibility study. Grade uncertainty is one of the major components of technical uncertainty that affects the variability of the project. Geostatistical simulation, as a reliable approach, is the most widely used method to quantify risk analysis to overcome the drawbacks of the estimation methods used for an entire ore body. In this work, all the algorithms developed by numerous researchers for optimization of the underground stope layout are reviewed. After that, a computer program called stope layout optimizer 3D is developed based on a previously proposed heuristic algorithm in order to incorporate the influence of grade variability in the final stope layout. Utilizing the sequential gaussian conditional simulation, 50 simulations and a kriging model are constructed for an underground copper vein deposit situated in the southwest of Iran, and the final stope layout is carried out separately. It can be observed that geostatistical simulation can effectively cope with the weakness of the kriging model. The final results obtained show that the frequency of economic value for all realizations varies between 6.7 M$ and 30.7 M$. This range of variation helps designers to make a better and lower risk decision under different conditions.

In uranium mines, the excavated waste has a lower grade than the threshold grade and is dumped on the surface as waste material. Due to erosion and rainfall over time, it is very likely that part of the uranium content is washed out of waste dump and leaked into surface and subsurface water resources and cause severe environmental hazards. The excavated waste during mining, as well as water collected during the drainage process of underground excavations, can be reused in the preparation of concrete fillers. In this study, samples of concrete backfill material were prepared by using waste material excavated from Saghand open pit and underground mines. Based on conducted testing and analyses, it was found that a large proportion of deposed waste and drained water can be used to prepare concrete fillers to fill stopes in Saghand underground mine. This process leads to a major reduction in mining costs, increased safety of mining operations, and significant improvements in reducing environmental pollutions.