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Minerals
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Future Mines: Intelligent and Digital Methods for Mine Safety, Mining...
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Future Mines: Intelligent and Digital Methods for Mine Safety, Mining Optimization, and Mineral Materials Application

A special issue of Minerals (ISSN 2075-163X).

Deadline for manuscript submissions: closed (30 June 2023) | Viewed by 5760

Special Issue Editors

Dr. Yuantian Sun

E-Mail Website
Guest Editor
School of Mines, China University of Mining and Technology, Xuzhou 221116, China
Interests: data analysis by AI and ML; recycling; engineering mineral materials; numerical modeling; simulation
Special Issues, Collections and Topics in MDPI journals
Dr. Guichen Li

E-Mail Website
Guest Editor
School of Mines, China University of Mining and Technology, Xuzhou 221116, China
Interests: mining engineering; intelligent mining
Dr. Reza Taherdangkoo

E-Mail Website
Guest Editor
TU Bergakademie Freiberg, Institute of Geotechnics, 09599 Freiberg, Germany
Interests: contaminant migration in fractured and porous media; coupled THMC processes in rocks; environmental geotechnics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The development of mines trends to be digital and intelligent will be a hot research area in the coming decades. The safety and optimization of mines is closely related to modern techniques and their application. For example, artificial intelligent (AI) methods such as machine learning (ML) and deep learning have been applied in optimization and beneficiation in mines. Additionally, digital methods have been used in the identification and modeling of mineral materials.

Many researchers have performed basic research in recent years and numerous important ideas and outputs have already been established. There is no doubt that collecting and summarizing these advanced techniques and application cases is significant. Combing AI and digital methods for future mines is a frontier that will promote and lead the development of techniques in mines in the next generation.

This Special Issue calls for papers that are related to intelligent and digital methods for mine safety, mining optimization, and mineral materials application. Topics of interest for this Special Issue include:

  • Future mines;
  • AI application in mines;
  • Big data processing;
  • Digital methods for mine safety;
  • Mining optimization;
  • Stability analysis in mining;
  • Simulation in mines;
  • Numerical modeling in engineering;
  • Advanced laboratory tests;
  • Mineral materials test;
  • Mineral materials application.

Nevertheless, the call is broad in its scope and may include many related themes not mentioned above.

Dr. Yuantian Sun
Dr. Guichen Li
Dr. Reza Taherdangkoo
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Minerals is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • future mines
  • mine safety
  • mining optimization
  • mineral materials
  • artificial intelligence
  • machine learning
  • data mining
  • data driven
  • data analysis
  • tests
  • simulation
  • numerical modelling
  • stability analysis

Published Papers (3 papers)

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Research

22 pages, 142691 KiB  
Article
Hybrid Model for Optimisation of Waste Dump Design and Site Selection in Open Pit Mining
by Aleksandar Doderovic, Svetozar-Milan Doderovic, Sasa Stepanovic, Mirjana Bankovic and Dejan Stevanovic
Minerals 2023, 13(11), 1401; https://doi.org/10.3390/min13111401 - 31 Oct 2023
Cited by 1 | Viewed by 1310
Abstract
Waste management is an unavoidable technological operation in the process of raw material extraction. The main characteristic of this technological operation is the handling of large quantities of waste material, which can amount to several hundred million cubic metres. At the same time, [...] Read more.
Waste management is an unavoidable technological operation in the process of raw material extraction. The main characteristic of this technological operation is the handling of large quantities of waste material, which can amount to several hundred million cubic metres. At the same time, this operation must comply with all administrative and environmental standards. Therefore, optimising waste rock management (particularly haulage and dumping) has the potential to significantly improve the overall value of the project. This paper presents a hybrid model for the optimisation of waste dump design and site selection. The model is based on different mathematical methods (Monte Carlo simulation, genetic algorithm, analytic hierarchy process and heuristic methods) adapted to different aspects of the problem. The main objective of the model is to provide a solution (in analytical and graphical form) for the draft waste dump design, on the basis of which the final waste dump design can be defined. The functioning of the model is verified using an example of an existing open pit. In the case study, 2250 members of the initial population (different waste dump variants) were generated, and a total of 110 optimised solutions were obtained using 15 optimisations. The solution with the best value of the objective function is adopted, and the final waste dump design is created. Full article
(This article belongs to the Special Issue Future Mines: Intelligent and Digital Methods for Mine Safety, Mining Optimization, and Mineral Materials Application)
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11 pages, 4215 KiB  
Article
The Roof Safety under Large Mining Height Working Face: A Numerical and Theoretical Study
by Xiaofang Wo, Guichen Li, Jinghua Li, Sen Yang, Zhongcheng Lu, Haoran Hao and Yuantian Sun
Minerals 2022, 12(10), 1217; https://doi.org/10.3390/min12101217 - 27 Sep 2022
Cited by 4 | Viewed by 1338
Abstract
As an important technology of thick coal seam mining, fully mechanized mining with a large mining height has high mining efficiency. In order to study the roof safety control of large mining height working face, the 122106 working face of Caojiatan coal mine [...] Read more.
As an important technology of thick coal seam mining, fully mechanized mining with a large mining height has high mining efficiency. In order to study the roof safety control of large mining height working face, the 122106 working face of Caojiatan coal mine is taken as the engineering background. The numerical simulation method is used to analyze the control ability of roof subsidence when the support strength is 1.2 MPa, 1.4 MPa, 1.6 MPa, 1.8 MPa, 2.0 MPa, and 2.2 MPa. The results show that the support strength of hydraulic support is negatively correlated with roof subsidence. Through theoretical analysis of the mechanical model of the support and surrounding rock under the filling condition, it is shown that the height of the gap between the filling body and roof is the main influencing factor of roof subsidence: the smaller the height of the gap between the filling body and roof, the better the control effect on the roof. Through numerical simulation, the roof subsidence and surface subsidence under different filling rates are analyzed. The results show that when the filling rate increases to 80% the control of roof subsidence achieves better results. Taking production safety and economic benefits into consideration, when the reasonable support strength of the working face is determined to be 2.0 MPa and the filling rate is 80%, the safety control of the working face roof can be ensured. Full article
(This article belongs to the Special Issue Future Mines: Intelligent and Digital Methods for Mine Safety, Mining Optimization, and Mineral Materials Application)
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15 pages, 5385 KiB  
Article
Geostatistical Modeling of Overburden Lithofacies to Optimize Continuous Mining in the Ptolemais Lignite Mines, Greece
by Konstantinos Modis, Daphne Sideri, Christos Roumpos, Hélène Binet, Francis Pavloudakis and Nikolaos Paraskevis
Minerals 2022, 12(9), 1109; https://doi.org/10.3390/min12091109 - 30 Aug 2022
Cited by 3 | Viewed by 1922
Abstract
Lignite production in Greece is implemented mainly by the Public Power Corporation (PPC), with the higher production being in the Lignite Center of Western Macedonia. A continuous surface mining method is used in order to satisfy the high production needs combined with the [...] Read more.
Lignite production in Greece is implemented mainly by the Public Power Corporation (PPC), with the higher production being in the Lignite Center of Western Macedonia. A continuous surface mining method is used in order to satisfy the high production needs combined with the necessity for selective mining; however, the occasional appearance of hard rock formations in the South Field mine overburdens was critical for the adoption of a discontinuous auxiliary method of rock mass removal, at these places, by explosives and large shovels. Furthermore, to minimize the delay of changing the machinery arrangements when a hard rock formation is met, an a priori knowledge of the spatial distribution of these rock masses would be catalytic. In this work, a plurigaussian simulation model of the overburden geological formations is developed in the South Field mine. This model could be used as a guide to schedule and optimize the overburden removal process. Validation of the model was affected in two ways: by direct comparing estimated to real cross-sections as observed on mine slopes or by correlating PPC’s recorded volumetric results to the average simulated hard rock percentages. Full article
(This article belongs to the Special Issue Future Mines: Intelligent and Digital Methods for Mine Safety, Mining Optimization, and Mineral Materials Application)
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