Geometrization of Kryvbas iron ore deposits

Author:

Peremetchyk A,Pysmennyi S,Chukharev S,Shvaher N,Fedorenko S,Moraru R

Abstract

Abstract Mining and geometrical prediction of iron ore deposit quality indices to solve problems of long-term and current planning intended to provide the most efficient performance of mining enterprises in terms of ore blending quality and increase rationalization of deposit development is an important aspect of geometrization. Investigations carried out to develop a mining-geometrical method for predicting indices of iron ore deposit quality are topical nowadays. The present study aims to enhance the methodology for geometrization of iron ore deposit quality indices for developing a mining-geometrical method of their prediction to provide rational mining. The research methodology consists in mining and geometrical modeling of quality indices and properties of the deposit, thus enabling determination of a certain relationship between components of a mineral, and, thereby, identification of the nature of these components’ location in the mineral. The latter is essential in design, construction and operation of a mineral deposit. The obtained results allow predicting quality indices of the deposit, assessing mineral reserves and consequently planning and optimizing performance of mining enterprises. The developed methods enable increased efficiency of mining iron ore deposits of Kryvbas.

Publisher

IOP Publishing

Subject

General Medicine

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Monitoring and estimation of mining and geometric indicators of the deposit;IOP Conference Series: Earth and Environmental Science;2024-05-01

2. 4th International Conference on Sustainable Futures: Environmental, Technological, Social and Economic Matters;IOP Conference Series: Earth and Environmental Science;2023-10-01

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3