Experimental and CFD Simulation Techniques for Coal Dust Explosibility: A Review

Khan, Asfar Mobin; Ray, S. K.; Mohalik, N.K.; Mishra, Debashish; Mandal, Sujata; Pandey, Jai Krishna

doi:10.1007/s42461-022-00631-y

Cited by 7 publications

(3 citation statements)

References 97 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, the dust produced by coal production poses a major threat to coal mine safety, air quality, and the health of mine workers [ 6 , 7 ]. In underground coal mining, the operation of coal cutting machines causes dust to accumulate, which, combined with factors such as static electricity sparks and mechanical friction, can easily trigger coal dust explosion accidents [ 8 , 9 ]. Coal-mine-dust-induced respiratory diseases have become some of the most common and serious occupational diseases among coal miners.…”

Section: Introductionmentioning

confidence: 99%

Molecular Mechanism Study on the Effect of Microstructural Differences of Octylphenol Polyoxyethylene Ether (OPEO) Surfactants on the Wettability of Anthracite

Yan

Kong

et al. 2023

Molecules

View full text Add to dashboard Cite

Inhalable coal dust poses a serious threat to coal mining safety, air quality, and the health of miners. Therefore, the development of efficient dust suppressants is crucial for addressing this issue. This study evaluated the ability of three high-surface-active OPEO-type nonionic surfactants (OP4, OP9, and OP13) to improve the wetting properties of anthracite via extensive experiments and a molecular simulation and determined the micro-mechanism of different wetting properties. The surface tension results show that OP4 has the lowest surface tension (27.182 mN/m). Contact angle tests and wetting kinetics models suggest that OP4 exhibits the strongest wetting improvement ability on raw coal with the smallest contact angle (20.1°) and the fastest wetting rate. In addition, FTIR and XPS experimental results also reveal that OP4-treated coal surfaces introduce the most hydrophilic elements and groups. UV spectroscopy testing shows that OP4 has the highest adsorption capacity on the coal surface, reaching 133.45 mg/g. The surfactant is adsorbed on the surface and pores of anthracite, while the strong adsorption ability of OP4 results in the least amount of N2 adsorption (8.408 cm3/g) but the largest specific surface area (1.673 m2/g). In addition, the filling behavior and aggregation behavior of surfactants on the anthracite coal surface were observed using SEM. The MD simulation results indicate that OPEO reagents with overly long hydrophilic chains would produce spatial effects on the coal surface. Under the influence of the π-π interaction between the hydrophobic benzene ring and the coal surface, OPEO reagents with fewer ethylene oxide quantities are more prone to adsorb onto the coal surface. Therefore, after the adsorption of OP4, both the polarity and the water molecule adhesion ability of the coal surface are greatly enhanced, which helps to suppress dust production. These results provide important references and a foundation for future designs of efficient compound dust suppressant systems.

show abstract

Section: Introductionmentioning

confidence: 99%

Molecular Mechanism Study on the Effect of Microstructural Differences of Octylphenol Polyoxyethylene Ether (OPEO) Surfactants on the Wettability of Anthracite

Yan

Kong

et al. 2023

Molecules

View full text Add to dashboard Cite

show abstract

“…Researchers worldwide found that about 12,489 miners died of 104 coal dust explosion accidents from 1900 to 2020. Asia had the highest number of deaths, followed by Europe, North America, Africa, Australia and South America ( Khan et al., 2022 ). The proportion of gas accident deaths was between 20 % and 30 % from 2010 to 2020 according to the coal mine accidents statistics of China ( You et al., 2021 ).…”

Section: Introductionmentioning

confidence: 99%

A method of regulating the wind field to reduce safety hazards of gas and dust in fully mechanized heading face based on dynamic data

Liu¹,

Gong²,

Chen³

et al. 2022

Heliyon

View full text Add to dashboard Cite

“…Public Health 2023, 20, 624 2 of 18 mine operation can reach 500-850 mg/m 3 , and the respirable dust concentration can reach 300-500 mg /m 3 [2]. According to incomplete statistics, coal dust in more than half of coal mines is explosive [3]. When the suspended coal dust in coal mine reaches a certain mass concentration and there is enough of a heat source and enough oxygen, a coal dust explosion may occur.…”

Section: Introductionmentioning

confidence: 99%

Research on Coal Dust Wettability Identification Based on GA–BP Model

Zheng

Shi

Jiang

et al. 2022

IJERPH

View full text Add to dashboard Cite

Aiming at the problems of the influencing factors of coal mine dust wettability not being clear and the identification process being complicated, this study proposed a coal mine dust wettability identification method based on a back propagation (BP) neural network optimized by a genetic algorithm (GA). Firstly, 13 parameters of the physical and chemical properties of coal dust, which affect the wettability of coal dust, were determined, and on this basis, the initial weight and threshold of the BP neural network were optimized by combining the parallelism and robustness of the genetic algorithm, etc., and an adaptive GA–BP model, which could reasonably identify the wettability of coal dust was constructed. The extreme learning machine (ELM) algorithm is a single hidden layer neural network, and the training speed is faster than traditional neural networks. The particle swarm optimization (PSO) algorithm optimizes the weight and threshold of the ELM, so PSO–ELM could also realize the identification of coal dust wettability. The results showed that by comparing the four different models, the accuracy of coal dust wettability identification was ranked as GA–BP > PSO–ELM > ELM > BP. When the maximum iteration times and population size of the PSO algorithm and the GA algorithm were the same, the running time of the different models was also different, and the time consumption was ranked as ELM < BP < PSO–ELM < GA–BP. The GA–BP model had the highest discrimination accuracy for coal mine dust wettability with an accuracy of 96.6%. This study enriched the theory and method of coal mine dust wettability identification and has important significance for the efficient prevention and control of coal mine dust as well as occupational safety and health development.

show abstract

Experimental and CFD Simulation Techniques for Coal Dust Explosibility: A Review

Cited by 7 publications

References 97 publications

Molecular Mechanism Study on the Effect of Microstructural Differences of Octylphenol Polyoxyethylene Ether (OPEO) Surfactants on the Wettability of Anthracite

Molecular Mechanism Study on the Effect of Microstructural Differences of Octylphenol Polyoxyethylene Ether (OPEO) Surfactants on the Wettability of Anthracite

A method of regulating the wind field to reduce safety hazards of gas and dust in fully mechanized heading face based on dynamic data

Research on Coal Dust Wettability Identification Based on GA–BP Model

Contact Info

Product

Resources

About