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露天矿内排长远规划模型及其求解方法 被引量:5

Long-term planning model of internal dumping in surface coal mining and its solution method
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摘要 不同于以往短期排土规划模型,构建长远排土规划模型能够降低露天矿剥离物总运输费用,避免内排土场高度频繁调整。根据露天矿采排场发展时空关系,提出了排土场动态调整约束条件,并以剥离物总运输费用最小为目标,建立了露天矿内排长远规划模型。此外,定义了模型基础数据,提出了模型的求解方法,给出了排弃阶段坡底位置、坡面切割实体后的质心和体积、排弃高度等的计算方法。以某露天煤矿为例,构建了三维地质模型,计算结果表明:与传统方法设计结果相比,该模型计算结果能够降低剥离物总运输费用17.8亿元,各阶段排弃标高波动较小,有利于排土及后续复垦作业。 Unlike the existing short term dumping plan model,the long term model can reduce the overburden trans portation cost and avoid adjusting the height of internal dump frequently. The constraint conditions of dump's dy namic adjustment were put forward in this study based on the space time relations between working slope and inter nal dump,and the long term planning model of internal dumping was established for the minimization of the total transportation cost. In addition,the basic data of the model were defined,the solving method of the model was pro posed,and the calculation methods of dump stage slope position,centroid and volume of entity sliced by dump stage slope and dump stage height were presented. Taken a surface coal mine as an example,the three dimensional geolog ical model was built. Compared with the results with traditional method,the total overburden transportation cost can be reduced by 17.8 million Yuan,the dump heights of each stage change slightly,which is beneficial to dump and reclamation.
作者 肖双双 黄甫 李克民 马力 洪勇 XIAO Shuangshuang;HUANG Fu;LI Kemin;MA Li;HONG Yong(School of Energy Engineering, Xi' an University of Science and Technology, Xi' an 710054, China;North Blasting Engineering Co Ltd, Beijing 100089, China;School of Mines, China University of Mining and Technology ,Xuzhou 221116, China;School of Materials and Mineral Resources ,Xi ' an University of Architecture and Technology ,Xi ' an 710055,China)
出处 《煤炭学报》 EI CAS CSCD 北大核心 2018年第4期951-958,共8页 Journal of China Coal Society
基金 国家自然科学基金青年科学基金资助项目(51604264) 西安科技大学博士(后)启动基金资助项目(2017QDJ008)
关键词 露天矿 内排 长远规划 目标优化 surface mining internal dumping long-term planning objective optimization
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