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  • 标题:Methodology for a dump design optimization in large-scale open pit mines
  • 本地全文:下载
  • 作者:Jorge Puell Ortiz ; Sanjay Kumar Shukla ; Reviewing Editor
  • 期刊名称:Cogent Engineering
  • 电子版ISSN:2331-1916
  • 出版年度:2017
  • 卷号:4
  • 期号:1
  • 页码:1387955
  • DOI:10.1080/23311916.2017.1387955
  • 语种:English
  • 出版社:Taylor and Francis Ltd
  • 摘要:Abstract Modern large-scale open pit mines move hundreds of thousands of tonnes of material daily, from the loading sources to the destination zones, whether these are massive mine dumps or, to a lesser extent, to the grinding mills. Mine dumps can be classified as leach or waste dumps, depending upon their economic viability to be processed in-place, a condition that has experienced great progress in the last decades and has reconfigured the open pit haulage network with an increase in the number of dumps. Therefore, new methods for dump design optimization are of the highest priority in mine planning management. This paper presents a methodology to model and optimize the design of a dump by minimizing the total haulage costs. The location and design of these dumps will be given mainly by the geological characteristics of the mineral, tonnage delivered, topographical conditions, infrastructure capital and transportation costs. Spatial and physical design possibilities, in addition, provide a set of parameters of mathematical and economic relationship that creates opportunities for modelling and thus facilitates the measurement and optimization of ultimate dump designs. The proposed methodology consists of: (1) Formulation of a dump model based on a system of equations relying on multiple relevant parameters; (2) Solves by minimizing the total cost using linear programming and determines a “preliminary” dump design; (3) Through a series of iterations, changes the “preliminary” footprint by projecting it to the topography and creates the ultimate dump design. Finally, an application for a waste rock dump illustrates this methodology.
  • 关键词:mine planning ; dump design ; open pit ; optimization
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