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.
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.
