Exploitation
Meisam Saleki; Reza Khaloo Kakaie; Mohammad Ataei; Ali Nouri Qarahasanlou
Abstract
One of the most critical designs in open-pit mining is the ultimate pit limit (UPL). The UPL is frequently computed initially through profit-maximizing algorithms like the Lerchs-Grossman (LG). Then, in order to optimize net present value (NPV), production planning is executed for the blocks that ...
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One of the most critical designs in open-pit mining is the ultimate pit limit (UPL). The UPL is frequently computed initially through profit-maximizing algorithms like the Lerchs-Grossman (LG). Then, in order to optimize net present value (NPV), production planning is executed for the blocks that fall within the designated pit limit. This paper presents a mathematical model of the UPL with NPV maximization, enabling simultaneous determination of the UPL and long-term production planning. Model behavior is nonlinear. Thus, in order to achieve model linearization, the model has been partitioned into two linear sub-problems. The procedure facilitates the model solution and the strategy by decreasing the number of decision variables. Naturally, the model is NP-Hard. As a result, in order to address the issue, the Dynamic Pit Tracker (DPT) heuristic algorithm was devised, accepting economic block models as input. A comparison is made between the economic values and positional weights of blocks throughout the steps in order to identify the most appropriate block. The outcomes of the mathematical model, LG, and Latorre-Golosinski (LAGO) algorithms were assessed in relation to the DPT on a two-dimensional block model. Comparative analysis revealed that the UPLs generated by these algorithms are consistent in this instance. Utilizing the new algorithm to determine UPL for a 3D block model revealed that the final pit profit matched LG UPL by 97.95%.
Exploitation
M. Mohseni; M. Ataei; R. Khaloo Kakaie
Abstract
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. ...
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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.
Exploitation
F. Sotoudeh; M. Ataei; R. Kakaie; Y. Pourrahimian
Abstract
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 ...
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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.
Rock Mechanics
J. Mohammadi; M. Ataei; R. Kakaie; R. Mikaeil; S. Shaffiee Haghshenas
Abstract
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. ...
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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.
Rock Mechanics
A.R. Dormishi; M. Ataei; R. Khaloo Kakaie; R. Mikaeil; S. Shaffiee Haghshenas
Abstract
One of the most significant and effective criteria in the process of cutting dimensional rocks using the gang saw is the maximum energy consumption rate of the machine, and its accurate prediction and estimation can help designers and owners of this industry to achieve an optimal and economic process. ...
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One of the most significant and effective criteria in the process of cutting dimensional rocks using the gang saw is the maximum energy consumption rate of the machine, and its accurate prediction and estimation can help designers and owners of this industry to achieve an optimal and economic process. In the present research work, it is attempted to study and provide models for predicting the maximum energy consumption of the gang saw during the process of soft dimensional rocks with the help of an intelligent optimization model such as random non-linear techniques, i.e. the Hybrid ANFIS-DE and Hybrid ANFIS-PSO algorithms based upon 4 physical and mechanical parameters including uniaxial compressive strength, Mohs hardness, Schimazek’s F-abrasiveness factors, Young modulus, and an operational characteristic of the machine, i.e. production rate. During this research work, 120 samples are tested on 12 carbonate rocks. The maximum energy consumption of the cutting machine during this work is measured and used as a modeling output for evaluating the performance of cutting machine. Also meta-heuristic algorithms including DE and PSO algorithms are used for training the Adaptive Neural Fuzzy Inference System (ANFIS). In addition, the PSO algorithm has a higher ability in terms of model output and performance indices and has a superiority over the differential evolution algorithm. Furthermore, comparison between the measured datasets with the ANFIS-DE and ANFIS-PSO models indicate the accuracy and ability of the ANFIS-PSO model in predicting the performance of gang saw considering the machine’s properties and the cut rock.
Exploitation
M. Mohseni; M. Ataei; R. Khaloo Kakaie
Abstract
Production planning in mineral exploitation should be undertaken to maximize exploited ore at a minimum unplanned dilution. Unplanned dilution reduction is among the ways to enhance the quality of products, and hence, reduce the associated costs, resulting in a higher profit. In this way, firstly, all ...
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Production planning in mineral exploitation should be undertaken to maximize exploited ore at a minimum unplanned dilution. Unplanned dilution reduction is among the ways to enhance the quality of products, and hence, reduce the associated costs, resulting in a higher profit. In this way, firstly, all the parameters contributing to unplanned dilution in underground stopes and specifically the cut-and-fill stoping method are identified. Secondly, the parameters are weighed using the fuzzy-Delphi analytical hierarchy process. Thirdly, the most effective parameters are selected among the pool of effective parameters. Finally, in order to present a novel classification system for an unplanned dilution assessment, a new index called stope unplanned dilution index (SUDI) is introduced. SUDI represents the extent to which a cut-and-fill stope is susceptible to unplanned dilution. That is, having the value of this index, one may classify the cut-and-fill stopes into five groups according to robustness versus unplanned dilution: very strong, strong, moderate, weak, and very weak. SUDI is applied to10 stopes in different parts of Venarch Manganese Mines (Qom, Iran). In this way, a semi-automatic cavity monitoring system is implemented in the stopes. The regression analysis method shows that there is a relationship between SUDI and the actual unplanned dilution in equivalent linear overbreak/slough with a correlation coefficient (R2 = 0.8957).
R. Norouzi Masir; R. Khalokakaie; M. Ataei; S. Mohammadi
Abstract
Mining can become more sustainable by developing and integrating economic, environmental, and social components. Among the mining industries, coal mining requires paying a serious attention to the aspects of sustainable development. Therefore, in this work, we investigate the impacting factors involved ...
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Mining can become more sustainable by developing and integrating economic, environmental, and social components. Among the mining industries, coal mining requires paying a serious attention to the aspects of sustainable development. Therefore, in this work, we investigate the impacting factors involved in the sustainable development of underground coal mining from the structural viewpoint. For this purpose, the decision-making trial and evaluation laboratory (DEMATEL) technique, which is a graph-based method, is utilized. To do so, at first, twenty effective factors are determined for three components. Then the hierarchical structure and the systematic approach are used to determine the total exerted influence or total received influence of the components. The results obtained show that the environmental and social components are the most important, and the economic components are the least important among them.
Exploitation
S. Mohammadi; M. Ataei; R. Khaloo Kakaie; A. Mirzaghorbanali
Abstract
Immediate roof caving in longwall mining is a complex dynamic process, and it is the core of numerous issues and challenges in this method. Hence, a reliable prediction of the strata behavior and its caving potential is imperative in the planning stage of a longwall project. The span of the main caving ...
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Immediate roof caving in longwall mining is a complex dynamic process, and it is the core of numerous issues and challenges in this method. Hence, a reliable prediction of the strata behavior and its caving potential is imperative in the planning stage of a longwall project. The span of the main caving is the quantitative criterion that represents cavability. In this paper, two approaches are proposed in order to predict the span of the main caving in longwall projects. Cavability index (CI) is introduced based on the hybrid multi-criteria decision-making technique, combining the fuzzy analytical network processes (ANP) and the fuzzy decision-making trial and evaluation laboratory (DEAMTEL). Subsequently, the relationship between the new index and the caving span is determined. In addition, statistical relationships are developed, incorporating the multivariate regression method. The real data for nine panels is used to develop the new models. Accordingly, two models based on CI including the Gaussian and cubic models as well as the linear and non-linear regression models are proposed. The performance of the proposed models is evaluated in various actual cases. The results obtained indicate that the CI-Gaussian model possesses a higher performance in the prediction of the main caving span in actual cases when compared to the other models. These results confirm that it is not possible to consider all the effective parameters in an empirical relationship due to a higher error in the prediction.
Exploitation
M. M. Tahernejad; M. Ataei; R. Khalokakaie
Abstract
In the context of open-pit mine planning, uncertainties including commodity price would significantly affect the technical and financial aspects of mining projects. A mine planning that takes place regardless of the uncertainty in price just develops an optimized plan at the starting time of the mining ...
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In the context of open-pit mine planning, uncertainties including commodity price would significantly affect the technical and financial aspects of mining projects. A mine planning that takes place regardless of the uncertainty in price just develops an optimized plan at the starting time of the mining operation. Given the price change over the life of mine, which is quite certain, optimality of the proposed plan will be eliminated. This paper presents a risk-averse decision-making tool to help mine planners in mining activities under price uncertainty. The objective is to propose mine planning in a way that a target Net Present Value (NPV) is guaranteed. In order to reach this goal, Information Gap Decision Theory (IGDT) is developed to hedge the mining project against the risk imposed by the information gap between the forecasted and actual price. The proposed approach is of low sensitivity to the price change over the life of mine, and can use the estimated prices with uncertainty. A case study at an existing iron mine demonstrates the performance of the proposed approach. The results obtained showed that the proposed method could provide a robust solution to mine planning under price uncertainty. Moreover, it was concluded that the method could present more reliable mine plans under condition of price uncertainty.
A. Nouri Qarahasanlou; M. Ataei; R. Khaolukakaie; B. Ghodrati; M. Mokhberdoran
Abstract
The life cycle cost of a system is influenced by its maintainability. Maintainability is a design parameter, whose operational conditions can affect it significantly. Hence, the effects of these operational conditions should be quantified early in the design phase. The proportional repair model (PRM), ...
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The life cycle cost of a system is influenced by its maintainability. Maintainability is a design parameter, whose operational conditions can affect it significantly. Hence, the effects of these operational conditions should be quantified early in the design phase. The proportional repair model (PRM), which is developed based on the proportional hazard model (PHM), can be used to analyze maintainability considering the effects of the operational conditions. In PRM, the effects of the operational conditions are considered to be time-independent. However, this assumption may not be valid for some cases. The aim of this paper is to present an approach for prediction of the maintainability performance of the mining facilities considering the time-dependent influencing factors. The stratified Cox regression method (SCRM) is used to determine maintainability in the presence of time-dependent covariates for fleet vehicles operating in Sungun Copper Mine, Iran.
M. Ataei; E. Tajvidi Asr; R. Khalokakaie; K. Ghanbari; M. R. Tavakoli Mohammadi
Abstract
Environmental impact assessment (EIA) has led to the dominance of planners on the natural environment of the regions, providing the possibility of continuously monitoring and controlling the status quo by management staff. In this regard, a new semi-quantitative model is presented for the EIA of the ...
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Environmental impact assessment (EIA) has led to the dominance of planners on the natural environment of the regions, providing the possibility of continuously monitoring and controlling the status quo by management staff. In this regard, a new semi-quantitative model is presented for the EIA of the Eastern Alborz Coal Mining complex using the matrix method, and determining the corresponding impacting factors and environmental components. For this purpose, the expert opinions are used to gather the preliminary data and score the parameters involved. The effect of each impacting factor involved on each environmental component is determined by quantifying the qualitative comments. According to the results obtained, the components air quality, human health and safety, and ecology and soil of the area undergo the most environmental damages from the mining activities. Then the EIA results obtained are used to assess the sustainability of the complex using the Phillips mathematical model. The results obtained indicate that the sustainability of this complex is weak, and, therefore, the preventive environmental measures with a preference must be recommended to reduce the environmental damages to its components.
M. Noroozi; R. Kakaie; Seyed M. E Jalali
Abstract
Fault zones and fault-related fracture systems control the mechanical behaviors and fluid-flow properties of the Earth’s crust. Furthermore, nowadays, modeling is being increasingly used in order to understand the behavior of rock masses, and to determine their characteristics. In this work, fault ...
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Fault zones and fault-related fracture systems control the mechanical behaviors and fluid-flow properties of the Earth’s crust. Furthermore, nowadays, modeling is being increasingly used in order to understand the behavior of rock masses, and to determine their characteristics. In this work, fault zones and fracture patterns are reviewed, and also comprehensive studies are carried out on the fracture geometry and density variations. A model to describe damage zones around the strike-slip faults is developed, in which the range of damage zone styles commonly found around strike-slip fault zones are shown. A computer code, named DFN-FRAC3D, is developed for the two- and three-dimensional stochastic modeling of rock fracture systems in fault zones. In this code, the pre-existing and fault-related fractures are modeled by their respective probability distributions, and the joint density may be varied by the distance from the fault core. This work describes the theoretical basis and the implementation of the code, and provides a case study in the rock fracture modeling to demonstrate the application of the prepared code.
S. Mohammadi; M. Ataei; R. Khalokakaei; E. Pourzamani
Abstract
Optimization of the exploitation operation is one of the most important issues facing the mining engineers. Since several technical and economic parameters depend on the cut-off grade, optimization of this parameter is of particular importance. The aim of this optimization is to maximize the net present ...
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Optimization of the exploitation operation is one of the most important issues facing the mining engineers. Since several technical and economic parameters depend on the cut-off grade, optimization of this parameter is of particular importance. The aim of this optimization is to maximize the net present value (NPV). Since the objective function of this problem is non-linear, three methods can be used to solve it: analytical, numerical, and meta-heuristic. In this study, the Golden Section Search (GSS) method and the Imperialist Competitive Algorithm (ICA) are used to optimize the cut-off grade in mine No. 1 of the Golgohar iron mine. Then the results obtained are compared. Consecuently, the optimum cut-off grades using both methods are calculated between 40.5% to 47.5%. The NPVs obtained using the GSS method and ICA were 18487 and 18142 billion Rials, respectively. Thus the value for GSS was higher. The annual number of iterations in the GSS method was equal to 18, and that for ICA was less than 18. Also computing and programming the process of golden section search method were easier than those for ICA. Therefore, the GSS method studied in this work is of a higher priority.