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Mechanism of Coal Spontaneous Combustion in Goaf and Mine Fire...
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Mechanism of Coal Spontaneous Combustion in Goaf and Mine Fire Prevention

A special issue of Fire (ISSN 2571-6255).

Deadline for manuscript submissions: 31 July 2024 | Viewed by 2249

Special Issue Editors

Prof. Dr. Yueping Qin

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Guest Editor
School of Emergency Management and Safety Engineering, China University of Mining & Technology, Beijing, China
Interests: mine fire and gas disaster prevention and control; ventilation and air conditioning engineering; underground space safety; rock dynamic disaster prevention and control
Dr. Hao Xu

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Guest Editor
College of Safety and Environmental Engineering, Shandong University of Science and Technology, Qingdao, China
Interests: mine safety engineering; coal spontaneous combustion; coalbed methane extraction; mine fire prevention and control
Dr. Yipeng Song

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Guest Editor
School of Management Science and Engineering, Shandong Technology and Business University, Yantai, China
Interests: longwall gob; spontaneous ignition; coal self-heating; numerical modeling; fire prevention and prediction
Dr. Wenjie Guo

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Guest Editor
School of Safety Engineering, North China Institute of Science and Technology, Langfang, China
Interests: mine safety; coal spontaneous combustion; mine fire prevention and control
Dr. Jia Liu

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Guest Editor
College of Safety and Emergency Management Engineering, Taiyuan University of Technology, Taiyuan, China
Interests: mine gas and fire disaster prevention and control; gas transport mechanism; underground space safety

Special Issue Information

Dear Colleagues,

Coal fires are a major disaster that threatens the safety of mine production, with the vast majority of fires caused by coal spontaneous combustion, which often occurs in enclosed spaces such as gobs, coal pillars and structural belts. In terms of the occurrence and development laws of coal fires, existing research mainly includes: 1 The self-heating oxidation characteristics of coal; 2. Numerical simulation calculation/similar simulation experiment based on commercial software; 3. Early prediction and monitoring of coal fires; 4. Application of fire prevention and extinguishing technology/materials. However, many important details, such as the combustion characteristics of coal at high temperatures and the fire-extinguishing efficiency of composite materials, to name a few, still need further attention.

This Special Issue aims to to gather recent studies on the disaster mechanism and fire extinguishing technology of coal fires. It aims to combine experiments and on-site observations with numerical simulations to reveal the dynamic evolution process of underground fires. Research areas may include (but are not limited to) the following:

  1. Low-temperature oxidation characteristics of coal;
  2. Disaster mechanism of mine fires/spontaneous combustion;
  3. Theoretical modeling method and numerical simulation;
  4. Fire source location detection (gob, coal pillar, roadway, etc.);
  5. Development of fire extinguishing materials and equipments;
  6. Early warning and control technology for underground coal fires.

We look forward to receiving your contributions.

Prof. Dr. Yueping Qin
Dr. Hao Xu
Dr. Yipeng Song
Dr. Wenjie Guo
Dr. Jia Liu
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. Fire 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

  • coal spontaneous combustion
  • underground space
  • flame combustion
  • numerical modeling
  • fire prevention and control
  • thermodynamics
  • extinguishing materials
  • monitoring method

Published Papers (2 papers)

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Research

27 pages, 6804 KiB  
Article
Prediction of Coal Spontaneous Combustion Hazard Grades Based on Fuzzy Clustered Case-Based Reasoning
by Qiuyan Pei, Zhichao Jia, Jia Liu, Yi Wang, Junhui Wang and Yanqi Zhang
Fire 2024, 7(4), 107; https://0-doi-org.brum.beds.ac.uk/10.3390/fire7040107 - 24 Mar 2024
Viewed by 575
Abstract
Accurate prediction of the coal spontaneous combustion hazard grades is of great significance to ensure the safe production of coal mines. However, traditional coal temperature prediction models have low accuracy and do not predict the coal spontaneous combustion hazard grades. In order to [...] Read more.
Accurate prediction of the coal spontaneous combustion hazard grades is of great significance to ensure the safe production of coal mines. However, traditional coal temperature prediction models have low accuracy and do not predict the coal spontaneous combustion hazard grades. In order to accurately predict coal spontaneous combustion hazard grades, a prediction model of coal spontaneous combustion based on principal component analysis (PCA), case-based reasoning (CBR), fuzzy clustering (FM), and the snake optimization (SO) algorithm was proposed in this manuscript. Firstly, based on the change rule of the concentration of signature gases in the process of coal warming, a new method of classifying the risk of spontaneous combustion of coal was established. Secondly, MeanRadius-SMOTE was adopted to balance the data structure. The weights of the prediction indicators were calculated through PCA to enhance the prediction precision of the CBR model. Then, by employing FM in the case base, the computational cost of CBR was reduced and its computational efficiency was improved. The SO algorithm was used to determine the hyperparameters in the PCA-FM-CBR model. In addition, multiple comparative experiments were conducted to verify the superiority of the model proposed in this manuscript. The results indicated that SO-PCA-FM-CBR possesses good prediction performance and also improves computational efficiency. Finally, the authors of this manuscript adopted the Random Balance Designs—Fourier Amplitude Sensitivity Test (RBD-FAST) to explain the output of the model and analyzed the global importance of input variables. The results demonstrated that CO is the most important variable affecting the coal spontaneous combustion hazard grades. Full article
(This article belongs to the Special Issue Mechanism of Coal Spontaneous Combustion in Goaf and Mine Fire Prevention)
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20 pages, 3723 KiB  
Article
Experimental Study on the Microstructural Characterization of Retardation Capacity of Microbial Inhibitors to Spontaneous Lignite Combustion
by Yanming Wang, Ruijie Liu, Xiaoyu Chen, Xiangyu Zou, Dingrui Li and Shasha Wang
Fire 2023, 6(12), 452; https://0-doi-org.brum.beds.ac.uk/10.3390/fire6120452 - 27 Nov 2023
Viewed by 1300
Abstract
Mine fires are one of the common major disasters in underground mining. In addition to the external fire sources generated by mining equipment and mechanical and electrical equipment during operations, coal is exposed to air during mining, and spontaneous combustion is also the [...] Read more.
Mine fires are one of the common major disasters in underground mining. In addition to the external fire sources generated by mining equipment and mechanical and electrical equipment during operations, coal is exposed to air during mining, and spontaneous combustion is also the main cause of mine fires. In order to reduce the hidden danger of coal mines caused by spontaneous coal combustion during lignite mining, the microbial inhibition of coal spontaneous combustion is proposed in this paper. Via SEM, pore size analysis, and NMR and FT-IR experiments, the mechanism of coal spontaneous combustion is discussed and revealed. The modification of lignite before and after the addition of retardants is analyzed from the perspective of microstructure, and the change in flame retardancy of the lignite treated with two retardants compared with raw coal is explored. The results show that, compared with raw coal, a large number of calcium carbonate particles are attached to the surface of the coal sample after bioinhibition treatment, and the total pore volume and specific surface area of the coal sample after bioinhibition treatment are decreased by 68.49% and 74.01%, respectively, indicating that bioinhibition can effectively plug the primary pores. The results of NMR and Fourier infrared spectroscopy show that the chemical structure of the coal sample is mainly composed of aromatic carbon, followed by fatty carbon and carbonyl carbon. In addition, the contents of active groups (hydroxyl, carboxyl, and methyl/methylene) in lignite after bioretardation are lower than those in raw coal, and methyl/methylene content is decreased by 96.5%. The comparison shows that the flame-retardant performance of biological retardants is better than that of chemical retardants, which provides an effective solution for the efficient prevention and control of spontaneous combustion disasters in coal mines. Full article
(This article belongs to the Special Issue Mechanism of Coal Spontaneous Combustion in Goaf and Mine Fire Prevention)
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