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Applied Sciences
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Mining Safety: Challenges and Prevention, 2nd Edition
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Mining Safety: Challenges and Prevention, 2nd Edition

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Earth Sciences".

Deadline for manuscript submissions: closed (20 August 2024) | Viewed by 2424

Special Issue Editor

Dr. Hao Shao

E-Mail Website
Guest Editor
School of Safety Engineering, China University of Mining & Technology, Xuzhou 22111, China
Interests: mine safety; big data analytics; gas explosion; emergency rescue; mine ventilation; fire prevention; spontaneous combustion of coal
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The mining industry is limited by its work environment. The ventilation of this work environment is poor, and there are many problems that influence the safety and health of miners, such as fire hazard, gas, dust explosion, poor ventilation, etc. Nowadays, the aim of research on mining safety is to use new theories and methods to investigate the mechanisms of mining safety problems, the rule of development, and new technologies.

The Special Issue topics include the analysis of trends around mine safety, the management of mine safety, mine fire, mine ventilation, mine dust, and mine gas, and the big data analysis of mine safety.

Dr. Hao Shao
Guest Editor

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Keywords

  • mine safety
  • big data analysis
  • gas prevention
  • gas explosion
  • emergency rescue
  • dust control
  • mine ventilation
  • intelligent ventilation
  • fire prevention
  • spontaneous combustion of coal

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Published Papers (3 papers)

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Research

14 pages, 4005 KiB  
Article
Determination of the Advanced Mining Influence Range in Coal Mines Based on the Statistical Analysis of Mining-Induced Seismicity
by Kunyou Zhou, Zhen Deng, Jiliang Kan, Linming Dou, Jiazhuo Li, Minke Duan and Peng Kong
Appl. Sci. 2024, 14(17), 7737; https://doi.org/10.3390/app14177737 - 2 Sep 2024
Viewed by 335
Abstract
Determining the advanced mining influence range of an underground working face is crucial for preventing dynamic disasters, such as coal bursts and gas outbursts. In this study, the occurrence of advanced seismicity before the working face as well as its correlation with the [...] Read more.
Determining the advanced mining influence range of an underground working face is crucial for preventing dynamic disasters, such as coal bursts and gas outbursts. In this study, the occurrence of advanced seismicity before the working face as well as its correlation with the acoustic emission (AE) activity of coal and rocks under axial loading was analyzed. Based on the results, a novel statistical method to determine the advanced mining influence range based on advanced seismicity data was proposed and then validated with a case study. The results show that advanced seismicity is caused by the combined effects of static and dynamic stresses at the working face. This seismicity can be used to assess the mining influence degree of the working face on the advanced coal and rock mass, and determine the advanced mining influence range. Using the novel statistical method, the normalized curves for the total number and total energy of the advanced mining-induced seismicity can be plotted. Then, the advanced mining influence range can be determined using thresholds. The thresholds can be established based on the AE activities observed in coal and rock samples under axial static loading. In the case study in this research, the thresholds for the total seismic number and total seismic energy are 0.076 and 0.052, respectively. The corresponding advanced mining influence ranges are 275 m and 245 m, respectively. Field monitoring confirms an advanced mining influence range of 255 m, which validates the results obtained using the novel statistical method. Full article
(This article belongs to the Special Issue Mining Safety: Challenges and Prevention, 2nd Edition)
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14 pages, 5497 KiB  
Article
Management Solutions and Stabilization of a Pre-Existing Concealed Goaf Underneath an Open-Pit Slope
by Qing Na, Qiusong Chen, Yunbo Tao, Xiangyu Zhang and Yi Tan
Appl. Sci. 2024, 14(15), 6849; https://doi.org/10.3390/app14156849 - 5 Aug 2024
Viewed by 949
Abstract
Pre-existing concealed goafs underneath open-pit slopes (PCO-goafs) pose a serious threat to the stability of open-pit slopes (OP-slopes), which is a common problem worldwide. In this paper, the variable weight-target approaching method, equilibrium beam theory, Pratt’s arch theory, and numerical simulation are used [...] Read more.
Pre-existing concealed goafs underneath open-pit slopes (PCO-goafs) pose a serious threat to the stability of open-pit slopes (OP-slopes), which is a common problem worldwide. In this paper, the variable weight-target approaching method, equilibrium beam theory, Pratt’s arch theory, and numerical simulation are used to analyze the management solutions and stability of five PCO-goaf groups in the Nannihu molybdenum mine located in Luoyang City, Henan Province, China. The five PCO-goaf groups, numbered 1#, 2#, 3#, 4#, and 5#, are divided into four hazard classes, ranging from extremely poor to good stability. The stability of 1#, 2#, and 4# is poor and must be managed by filling, and the design strength of backfill is 1.2 MPa; caving is used to treat 3# and 5#, and the safe thickness of the overlying roof is calculated to be 10.5–41 m. After treatment, the safety coefficient of the slope is greater than 1.2, indicating that the slope is stable. This study provides insight and guidance for the safe operation of open-pit mines threatened by the existence of PCO-goafs. Full article
(This article belongs to the Special Issue Mining Safety: Challenges and Prevention, 2nd Edition)
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20 pages, 7894 KiB  
Article
Hazardous High-Energy Seismic Event Discrimination Method Based on Region Division and Identification of Main Impact Factors: A Case Study
by Yaoqi Liu, Anye Cao, Qiang Wang, Geng Li, Xu Yang and Changbin Wang
Appl. Sci. 2024, 14(14), 6154; https://doi.org/10.3390/app14146154 - 15 Jul 2024
Viewed by 674
Abstract
An investigation of risk factors has been identified as a crucial aspect of the routine management of rockburst. However, the identification methods for principal impact factors and the examination of the relationship between seismic energy and other source parameters have not been extensively [...] Read more.
An investigation of risk factors has been identified as a crucial aspect of the routine management of rockburst. However, the identification methods for principal impact factors and the examination of the relationship between seismic energy and other source parameters have not been extensively explored to conduct dynamic risk management. This study aims to quantify impact risk factors and discriminate hazardous high-energy seismic events. The analytic hierarchy process (AHP) and entropy weight method (EWM) are utilized to ascertain the primary control factors based on geotechnical data and nearly two months of seismic data from a longwall panel. Furthermore, the distribution law and correlation relationship among seismic source parameters are systematically analyzed. Results show that the effect of coal depth, coal seam thickness, coal dip, and mining speed covers the entire mining process, while the fault is only prominent in localized areas. There are varying degrees of log-positive correlations between seismic energy and other source parameters, and this positive correlation is more pronounced for hazardous high-energy seismic events. Utilizing the linear logarithmic relationship between seismic energy and other source parameters, along with the impact weights of dynamic risks, the comprehensive energy index for evaluating high-energy seismic events is proposed. The comprehensive energy index identification method proves to be more accurate by comparing with the high-energy seismic events based on energy criteria. The limitations and improvements of this method are also synthesized to obtaining a wide range of applications. Full article
(This article belongs to the Special Issue Mining Safety: Challenges and Prevention, 2nd Edition)
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