رضا کاکایی

The phenomenon of coal gas outbursts, with its direct influence on preserving the safety of mining through tension alleviation and sustaining operational continuity, as well as the reliance on its quality for various concerns, warrants scrutiny during the planning phase. Consequently, accurately forecasting these sudden gas expulsions is a critical and primary measure in the initial design stage, continuing through the mining and extraction processes. Although the subject has been extensively researched, a complete model is lacking to predict the interrelated impacts of methane gasification and outbursts. Hence, considering its national significance and widespread adoption of this technique globally, it is imperative to investigate the dynamics of sudden gas discharge and drainage. For numerous years, across various research disciplines, experiments utilizing physical models have been conducted to explore and comprehend systems' behaviors and physical properties. A fundamental aspect of these models is the requirement that both the modeled system and the primary model abide by the same physical principles. In the study detailed within this document, following the recognition of critical parameters in the outburst process, a novel apparatus was constructed through dimensional analysis. Utilizing this specially designed laboratory equipment, the outburst emissions were assessed on two coal samples.

Generally, Mine ventilation is based on the analysis of fluids. The main fluid in mine ventilation is air fluid. Based on the science of fluids, air-fluid shows different behaves in different conditions. In the fluid analysis method of the ventilation science, air-fluid can be analyzed from several different perspectives such as dry model, wet model, incompressible model, and compressible model. Researchers have used various models of fluid analysis in mine ventilation and most of them believe that the real conditions for designing mine ventilation are to consider two conditions: humid air and compressible fluid analysis. Accordingly, in this paper, different fluid analysis conditions were considered for designing mine ventilation and the results show that compressible fluid analysis for humid air needs to be solved by two nonlinear equations. Therefore, it requires numerical calculation methods. One of the most common methods in numerical calculations is the Newton-Raphson method. This method is defined based on the derivative. Using this method for solving these nonlinear equations increases the volume of mathematical calculations. Therefore, in this paper, two Delta (Δ) and K methods are presented to facilitate the solution of these two nonlinear equations and reduce the error of mathematical calculations. Delta (Δ) and K methods have been defined based on thermodynamic rules for analyzing compressible humid air in mine ventilation design. Also, the amount of evaporation rate of water should be known in these methods. The results show that these two methods have a simpler and better performance.

Extraction and exploitation is one of the important parts in the field of mines and mining industries. Blast hole drilling is the first stage of the production cycle in open pit mines. Which account for a large part of the exploitation costs. In operational processes, bits are one of the most sensitive and important parts of drilling, due to the type of application and high costs. Wear of these tools are an important parameter for estimating the efficiency of drilling equipment in mining projects. Wear of drilling bits is a function of various factors, some of which are related to machinery, operational parameters and management parameters, and some are dependent on the conditions and rock properties and rock mass and the surrounding environment. Examining the parameters affecting the tricone rotary bits wear can prevent wasting time and additional costs of the drilling process. Therefore, in this study, the evaluation of the factors affecting the tricone rotary bits wear in Sarcheshmeh copper mine has been investigated. For this purpose, the tricone rotary bits wear has been calculated through weight loss and by determining the effective parameters, the relationship between these factors and the tricone rotary bits wear has been determined through statistical methods. Then, using sensitivity analysis, the effect of input parameters on the target is determined. The results of these analyzes show that all the parameters of the study except the Chemical Index of Alteration (CIA), porosity and Equivalent Quartz Content on the desired output (the tricone rotary bits wear).

The Remaining Useful Life (RUL) valuation of mining machinery is a principal to ensure the production/output and customer satisfaction in the mining zone. In many cases, it may be of attention to know the expected value of the remaining life of the item before it fails from an arbitrary time that known RUL. The system's failure is also evaluated with the reliability index, which describes up-times. An individual unit's reliability during field use is essential in many mining equipment applications. This index, especially in industrial systems, and being affected by the internal condition also affects operating environmental conditions. For example, the loader performance in cold weather will be different from that of warm, which will affect the machine's reliability and thus the RUL. In reliability engineering, operating environmental conditions are considered "Risk factors or Covariates". Therefore, in this paper, an approach is proposed first to analyze the system's reliability considering covariates' effect and then estimate the RUL for different scenarios. The proportional hazard model was used in reliability analysis to be realistic and take the operational influencing factors in calculation. Methods are presented for calculating the reliability function and computing the RUL as a function of the current conditions to guarantee the desired output. The remaining useful life estimation of a Komatsu PC-1250 from the Sungun copper mine was evaluated as a case study of this approach. Systems operating environmental factors such as shift, dump-truck kind, rock kind, … (known as covariates) are assumed to influence covariate in this context. As a result, the Weibull proportional hazard model was fitted to describe the failure behavior, and the RUL of four selected scenarios was evaluated. Presented results can be used, e.g., for developing operational performance, planning of maintenance activities, spare parts provision, and the profitability of the owner of an asset.

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.

The contamination of ores with wastes or materials of lower than the cut-off grade is referred to as dilution. Dilution is an undesirable phenomenon that, on one hand, reduces the product grade and, consequently, reduces the sales prices and, on the other hand, adds an extra cost to waste production. Therefore, studying and evaluating the dilution risk is important in mining, and especially in underground mining. In this work, using a powerful decision-making method, i.e. Multi-Attributive Approximation Area Comparison (MABAC), the dilution risk and ranking it in underground mines are assessed. For this purpose, the most important parameters affecting the dilution in 10 mines of the Venarch manganese mines are first identified and then weighed using the Fuzzy Delphi Analytical Hierarchy Analysis (FDAHP) method. Then using the MABAC method, the dilution risk score for each mine is estimated, and subsequently, various mines are ranked as the dilution risk. Then with the implementation of the Cavity Monitoring System (CMS) and measurement of the actual dilution values, the mines are ranked in dilution. The correct matching of the results of these two rankings indicates that the MABAC method is highly effective in the ranking of the risk. At the end, the risk ranking of the mines is done using the TOPSIS method, and the lack of full compliance with the results of this method with the actual values indicates that the MABAC method is preferable to the TOPSIS method.

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.

Prediction of the production rate of the cutting dimensional stone process is crucial, especially when chain saw machines are used. The cutting dimensional rock process is generally a complex issue with numerous effective factors including variable and unreliable conditions of the rocks and cutting machines. The Group Method of Data Handling (GMDH) type of neural network and Radial Basis Function (RBF) neural network, as two kinds of the soft computing method, are powerful tools for identifying and assessing the unpredicted and uncertain conditions. Hence, this work aims to develop prediction models for estimating the production rate of chain saw machines using the RBF neural network and GMDH type of neural network, and then to compare the results obtained from the developed models based on the performance indices including value account for, root mean square error, and coefficient of determination. For this purpose, the parameters of 98 laboratory tests on 7 carbonate rocks are accurately investigated, and the production rate of each test is measured. Some operational characteristics of the machines, i.e. arm angle, chain speed, and machine speed, and also the three important physical and mechanical characteristics including uniaxial compressive strength, Los Angeles abrasion test, and Schmidt hammer (Sch) are considered as the input data, and another operational characteristic of the machines, i.e. production rate, is considered as the output dataset. The results obtained prove that the developed GMDH model is able to provide highly promising results in order to predict the production rate of chain saw machines based on the performance indices.

The over-break and slough of walls and roof of stopes in underground mines leads to unplanned dilution and dropping in the grade. The complex mechanism of unplanned dilution resulting from the effect of different parameters and interaction between them makes it impossible to provide an unplanned dilution model with sufficient accuracy through non-system methods. In this paper, a high-precision model in which interactions between parameters are considered is presented using the rock engineering systems approach. For this purpose, after selecting 8 parameters, as the most important parameters for unplanned dilution, the steps of this method include the formation of interaction matrix, matrix coding and formation of the ranking table, the index of unplanned dilution of 24 stopes from the Venarch Manganese mines has been calculated. Subsequently, using the cavity monitoring system, the actual values of unplanned dilution of each stope were measured and from there the unplanned dilution prediction model was obtained based on the unplanned dilution index. The model, which is a power relationship, has a coefficient of 0.89, root mean square error of 0.034, mean absolute error of 0.089 and a percentage of variance of 87. In the end, using this model, unplanned dilution of 9 new stopes (other than the 24 workshops) was predicted and compared with the actual values measured. The coefficient of this prediction is equal to 0.95, which indicates the high efficiency of the model and system approach in predicting the unplanned dilution of underground mining stopes.

In underground stopes, unplanned dilution occurs due to the overbreak and slough of walls and roof and consequently contamination of ore with wastes. This phenomenon not only leads to a reduction in the grade and, consequently costing to deficit grade, but also leads to the cost for mining the waste. Hence, the measurement of the amount of overbreak and slough of roof and walls of stopes in order to determine the unplanned dilution and, consequently, the study of the economic effects of it, is very important in underground mining. In this paper, using the cavity monitoring system (CMS), the effects of unplanned dilution on reduction of grade and increase in the cost of mining and reduction in the profit investigated. For this purpose, by defining the linear equivalent of overbreak and slough (ELOS) for the dilution, the system was implemented on 24 stopes of Venarch Manganese Mines and led to the discovery of the relations between the overbreak and dilution parameters and the economic parameters, including prediction relationship of the loss of profit. Results of data analysis indicate that the break-even of over break is in the 2.18 (m) that results 67.38% dilution.

Special measures must be taken to maximize the recovery of uranium deposits, reduce the absorption rate of radiation for personnel working, reduce environmental pollution and reduce mining costs in underground uranium mining. One of these measures is to fill the extracted spaces, in particular, in the tunnel cut and fill mining method. In this research, it has been tried to select the most suitable concrete filler mixing plan with the above-mentioned attitudes. To carry out this research, in a laboratory scale, concrete mixing designs were implemented for hydraulic concrete with four types of rock materials from waste of uranium mines, river sand, washed sand and barite sand. Samples of these mixing designs for testing of resistance One-axial pressure was taken. Also, in addition to calculating the cost of making any mixing plan, hydraulic concrete was constructed in different thicknesses adjacent to the uranium ore was poured to measure the amount of radiation. Radiation experiments and measurements were carried out for concrete mixing designs in different thicknesses. The results indicate a sharp decrease in the radiation and absorption dose of radiation by increasing the thickness of the filler concrete. It has also been proven that mining waste and drainage water from uranium mines that are contaminated with radioactive substances can be mixed with hydraulic concrete fillers to fill uranium underground mines in order to reduce environmental pollution and Filling costs.

In order to achieve maximum recovery and minimum absorption level of radiation in underground uranium mines specific measures must be taken. One way to achieve this goal is to employ the backfilling method using hydraulic concrete fills, in particular in the tunnel cut and fill method. The backfill is a material which is used to fill the excavated underground stopes to provide support and safety for the mining operations. In this research various mixes of hydraulic concrete fillers were prepared at the laboratory scale. The underground mine waste rock, open pit waste rock, natural river sand, and barite sand were used as backfilling main ingredients and representative samples of each mix design were prepared for the laboratory tests. Moreover, large scale samples of concrete hydraulic fills were cast at varying thicknesses in in the vicinity of uranium ore to enable examining the radiation level. The test results demonstrate that the use of hydraulic concrete fills can provide safety and stability to mining activities.

In this paper, Given the high importance of joint persistence characteristics on the mechanical behavior of the rock mass, geometric-stochastic joint network model, based on Veneziano method, has been developed by considering the statistical characteristics of joint size. Using surveyed data in the access tunnel of Rudbar Lorestan dam & hydropower plant and estimation of the best probability distribution function on geometric characteristics of existing joint sets in the study area, three-dimensional (3-D) geometric model of joint network has been presented. Nowadays, modeling is increasingly put forward as a method of determination of rock mass strength characteristics. An accurate description of the rock mass structure does provide a better starting point for modeling of rock mass. Besides, there will always be some random variation in the geometric properties of joints by virtue of rock mass heterogeneous nature. Therefore, it is necessary to describe the ordered properties stochastically and to use in rock mass modeling. 3-D stochastic joint network modeling technique represents the most optimal choice for simulating the probability nature of joint geometric properties. Methodology and Approaches: Using field measurements and statistical analysis, stochastic parameters of discontinuities are detemined. In this paper, collected data is obtained using a linear surveying. Data processing including matching different probability distribution function on geometric properties of surveyed joint sets has been performed using Dips and EasyFit software packages. In order to calculate volumetric joint density, joints, which have been visible to the naked eye in the field, have been counted within an area of 1 m2 using a square frame (1×1 m) with grid lines at 10 cm intervals. Using the areal joint density and existing equations, the volumetric joint density has been calculated for each joint set, separately. Thus, to prepare the geometric-stochastic model, the required inputs,mentioned above, have been used. The generated joints by the developed model, are coincided on the ordered probability distribution function of joint persistence. Results and In this paper, a 3-D geometrical- stochastic discontinuities network model for the access tunnel of Rudbar Lorestan dam has been presented. In order to model implementation, a computer code written in C++, named DFN-FRAC3D, has been developed to represent the joint network in different directions and to generate digital outputs. The results of this paper can be a useful input for numerical stability analysis and hydraulic behavior studies of rock mass.

Open pit mining is one of the most important methods of surface mining in which extraction of mineral deposit is carried out in benches. Ultimate limits of an open pit which define its size and shape at the end of the mine’s life must be designed before to start the operation. Manual and computer methods can be used to determine optimum ultimate pit limits. Manual methods of designing pit limits are based on stripping ratios and involve determining break even pit limits. The objective of computer methods is to determine the optimum ultimate pit outline for which the net profit is maximized. A number of algorithms such as floating or moving cone method, the Korobov algorithm and the corrected form of this method and the Lerchs and Grossmann algorithm based on graph theory have been developed to find out the optimum final pit limits. Each of these methods has special advantages and disadvantages. The designers of the corrected form of Korobov algorithm claim that this method is able to yield the true optimum pit in all the cases. The aim of this paper is to examine this method for being as a true optimum pit algorithm. This method is compared with the Lerchs-Grossmann algorithm which is the only method that can be proved, rigorously, always to yield the true optimum pit. The results show that the corrected form of Korobov algorithm is not always able to find out a true optimum pit outline.

Mineral Resources which can be regarded as a best potential opportunity to sustainable development of the country. Consequently appropriate investment in exploitation of these reserves can achieve high value added to the most industries. Therefore, it is necessary to recognize the priority of minerals for future investments. In this paper, the Analytical Hierarchy Process, in which a complex problem is modeled in a hierarchical structure showing the relationships of the goal, objectives (criteria) and alternatives, is used to recognize high priority 33 minerals for future investment with regards to the 6 criteria and 29 sub-criteria. For this purpose, on the bases of interview with mineral sector experts weights of criteria are calculated and then the piority of each mineral is determined for investments. The results show that copper, Iron, Phosphate, lead and zinc, coal, gold have high priority for future investments.

The commonly used failure criterion based on stress intensity factors is compared with new developed stress based failure criterion to predict crack growth trajectory and the advantages and disadvantages of both criteria are discussed using some examples. To obtain displacement vector and strain and stress tensors، the element free Galerkin method (EFGM) is used. The visibility criterion is applied to model cracks and the M-integral method is employed to calculate the stress intensity factors. Two examples are considered to evaluate the mentioned failure criteria. The stress intensity factors obtained from EFGM show good agreement with the results of finite element and analytical solutions. The failure criterion based on stress intensity factors only can predict the initial crack trajectory however the stress based failure criterion can predict the complete crack growth path and its predictions coincide very well with numerical and experimental results.

Mines as an important sector of economy has a basic role in the supply chain of most economical sectors. The analysis of quality and quantity of labor force in mines is one of the necessary activities for efficient management. This paper describes the relationship between qualitative properties with labor wage and productivity indexes of Iran mines labor force. For this purpose, qualitative and quantitative properties of labor forces have been evaluated in the period of 1994-2003 based on the experience, education, research and development, training and skills. The quantitative properties of labor force include labor wage and labor productivity. In the next step, relationships between qualitative and quantitative have been evaluated with Eviews software based on information of 8 provinces of Iran. Results show the effects of knowledge level and labor force wage on the labor force productivity. In addition, the skill level has no effect on the mine labor force wages.

Mineral sector as the essential part of the economy has important role for supplying industrie's raw materials. Investment promotion in this sector can earn high value added to the most industries. Consequently, it is necessary to recognize high priority minerals for future investment. In this paper, TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method, one of the major techniques of multiple attribute decision making process, utilized for ranking the 33 minerals for future investment. For this purpose, based on the interviews with mining experties, 29 criteria are defined. Then their quantities and weights are calculated. After that, based on the weights obtaining from the interviews as well as applying equal weights, the rank of each mineral is determined. The results show that copper, coal, iron, gold, chromites, lead and zinc have high priority respectively for future investments in Iran.