The ecological costs of open pit metal mining are quantified, which include lost value of direct eco-services, lost value of indirect eco-services, prevention and restoration costs, and cost of carbon emission from en...The ecological costs of open pit metal mining are quantified, which include lost value of direct eco-services, lost value of indirect eco-services, prevention and restoration costs, and cost of carbon emission from energy consumption. These ecological costs are incorporated in an iterative ultimate pit optimization algorithm. A case study is presented to demonstrate the influence of ecological costs on pit design outcome. The results show that it is possible to internalize ecological costs in mine designs. The pit optimization outcome shifts considerably to the conservative side and the profitability decreases substantially when ecological costs are accounted for.展开更多
The ultimate pit may affect other aspects in the life of a mine such as economical, technical, environmental, and social aspects. What makes it even more complex is that most often there are many pits which are econom...The ultimate pit may affect other aspects in the life of a mine such as economical, technical, environmental, and social aspects. What makes it even more complex is that most often there are many pits which are economically minable. This calls for a heuristic approach to determine which of these pits is the ultimate pit. This study presents a means of selecting an ultimate pit during design operations of the Hebei Limestone mine. During optimization processes of the mine, many pit shells were created using Whittle Software. Normally, Whittle Software optimizes these processes and assigns a revenue factor of 1 for the ultimate pit. Unfortunately, the pit shells created did not satisfy the criteria with a revenue factor of 1 based on the parameters. As a result of this, statistical analysis was implemented to further understand the relationship, variability, and correlation of the pit shells created (data). Correlation Analysis, K-means++ Analysis, Principal Component Analysis, and Generalized Linear models were used in the analysis of the pit shells created. The results portray a salient relationship of the optimization variables. In addition, the proposed method was tested on Whittle Sample projects which satisfy the selection of ultimate pit selection with a revenue factor of 1. The results show that the proposed model produced almost the same results as the Whittle model with a revenue factor of 1 and was also able to determine the ultimate pit in cases which did not satisfy the Whittle selection criteria.展开更多
An integral connection exists among the mine production planning, the mined material destination, and the ultimate pit limit （UPL） in the mining engineering economy. This relation is reinforced by real information a...An integral connection exists among the mine production planning, the mined material destination, and the ultimate pit limit （UPL） in the mining engineering economy. This relation is reinforced by real information and the benefits it engenders in the mining economy. Hence, it is important to create optimizing algorithms to reduce the errors of economic calculations. In this work, a logical mathematical algorithm that considers the important designing parameters and the mining economy is proposed. This algorithm creates an optimizing repetitive process among different designing constituents and directs them into the maximum amount of the mine economical parameters. This process will produce the highest amount of ores and the highest degree of safety. The modeling produces a new relation between the concept of the cutoff grade, mine designing, and mine planning, and it provides the maximum benefit by calculating the destination of the ores. The proposed algorithm is evaluated in a real case study. The results show that the net present value of the mine production is increased by 3% compared to previous methods of production design and UPL.展开更多
基金Project(50974041)supported by the National Natural Science Foundation of ChinaProject(NCET-11-0073)supported by Program for New Century Excellent Talents in University of Ministry of Education of China+1 种基金Project(201102065)supported by the Natural Science Foundation of Liaoning Province,ChinaProject(2012921075)supported by the Ten Million Talent Project of Liaoning Province,China
文摘The ecological costs of open pit metal mining are quantified, which include lost value of direct eco-services, lost value of indirect eco-services, prevention and restoration costs, and cost of carbon emission from energy consumption. These ecological costs are incorporated in an iterative ultimate pit optimization algorithm. A case study is presented to demonstrate the influence of ecological costs on pit design outcome. The results show that it is possible to internalize ecological costs in mine designs. The pit optimization outcome shifts considerably to the conservative side and the profitability decreases substantially when ecological costs are accounted for.
文摘The ultimate pit may affect other aspects in the life of a mine such as economical, technical, environmental, and social aspects. What makes it even more complex is that most often there are many pits which are economically minable. This calls for a heuristic approach to determine which of these pits is the ultimate pit. This study presents a means of selecting an ultimate pit during design operations of the Hebei Limestone mine. During optimization processes of the mine, many pit shells were created using Whittle Software. Normally, Whittle Software optimizes these processes and assigns a revenue factor of 1 for the ultimate pit. Unfortunately, the pit shells created did not satisfy the criteria with a revenue factor of 1 based on the parameters. As a result of this, statistical analysis was implemented to further understand the relationship, variability, and correlation of the pit shells created (data). Correlation Analysis, K-means++ Analysis, Principal Component Analysis, and Generalized Linear models were used in the analysis of the pit shells created. The results portray a salient relationship of the optimization variables. In addition, the proposed method was tested on Whittle Sample projects which satisfy the selection of ultimate pit selection with a revenue factor of 1. The results show that the proposed model produced almost the same results as the Whittle model with a revenue factor of 1 and was also able to determine the ultimate pit in cases which did not satisfy the Whittle selection criteria.
文摘An integral connection exists among the mine production planning, the mined material destination, and the ultimate pit limit （UPL） in the mining engineering economy. This relation is reinforced by real information and the benefits it engenders in the mining economy. Hence, it is important to create optimizing algorithms to reduce the errors of economic calculations. In this work, a logical mathematical algorithm that considers the important designing parameters and the mining economy is proposed. This algorithm creates an optimizing repetitive process among different designing constituents and directs them into the maximum amount of the mine economical parameters. This process will produce the highest amount of ores and the highest degree of safety. The modeling produces a new relation between the concept of the cutoff grade, mine designing, and mine planning, and it provides the maximum benefit by calculating the destination of the ores. The proposed algorithm is evaluated in a real case study. The results show that the net present value of the mine production is increased by 3% compared to previous methods of production design and UPL.
