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CFD simulation of multi-phase and multi-component diffusion of air-dust-gas in a fully mechanized mining face

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Abstract

To explore the rule of airflow-dust-gas dispersion and interaction in a fully mechanized mining face, the airflow current vector, the dust trajectory, and the gas spatial distribution were numerically simulated by Fluent. The results show that under the influence of airflow, respiratory dust diffuses to the leeward side of each dust-producing point and footway space and forms a high-concentration (peak concentration 2000 mg/m3) dust mass at 2 m on the leeward side of the advancing support. Gas tends to accumulate near the coal cutter drum, the roof, and the return air corner of the mining face, and the peak concentration exceeds the lower limit of explosion. Near the rear drum of the coal cutter and at the advancing support, considering that the gas and coal dust concentrations are both high and dust and gas can reduce each other’s explosion limit, serious gas and coal dust explosions are extremely likely to occur in the presence of a fire source, which may result in serious consequences. Therefore, the two areas can be regarded as key areas of gas and coal dust explosion prevention and control.

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Abbreviations

ρ :

Density of gas (kg m−3)

ρ p :

Density of dust particle (kg m−3)

x :

Coordinates (m)

u :

Continuous phase velocity (m s−1)

t :

Time (s)

p :

Pressure (Pa)

μ :

Viscosity coefficient (Pa s)

F D :

Drag force per unit particle mass

μ t :

Turbulence viscosity coefficient (Pa s)

k :

Turbulence kinetic energy (m2 s−2)

ε :

Turbulent dissipation rate (m2 s−3)

g :

Gravity acceleration (m/s2)

u p :

Particle velocity (m/s)

d p :

Particle diameter (m)

Re:

Relative Reynolds number

Δv i :

Volume of the ith cell

r :

Grid refinement factor

D T,i :

Thermal (Soret) diffusion coefficient

D i,m :

Mass diffusion coefficient for species i in the mixture

ζ :

Random numbers subjected to normal distribution

G k :

Generation of turbulence kinetic energy due to the mean velocity gradients

C 1ε :

Constant in the standard k-e model (1.44)

C 2ε :

Constant in the standard k-e model (1.92)

C μ :

Constant in the standard k-e model (0.09)

CD :

Drag coefficient

σ k :

Constant in the standard k-e model (1.00)

σ ε :

Constant in the standard k-e model (1.30)

T :

Temperature

F x :

Other forces in the X direction, Ν

\( {\overrightarrow{J}}_i \) :

Diffusion flux of species i

Sc t :

Turbulent Schmidt number (0.7)

ω i :

Local mass fraction of each species

y i,j :

Mole fraction of species i and j

M :

Mixture molecular weight

\( \overrightarrow{\nu} \) :

Overall velocity vector (m/s)

R :

Universal gas constant

m :

The order of the discretization method

N :

Total number of cells

R i :

Net rate of production of species by chemical reaction (0)

S i :

Rate of creation by addition from the dispersed phase plus any user-defined sources (0)

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Funding

This work was financially supported by the National Natural Science Foundation of China (Grant no. 51774198, 51904171), the Outstanding Youth Fund Project of Provincial Universities in Shandong Province, China (Grant no. ZR2017JL026), the Qingchuang Science and Technology Project of Universities in Shandong Province, China (Grant no. 2019KJH005), the Taishan Scholars Project Special Funding in Shandong Province, China (Grant no. ts20190935), the National Key Research and Development Program of China (Grant no. 2017YFC0805202), and the Natural Science Foundation of Shandong Provenience, China (Grant no. ZR2019BEE067).

Author information

Authors and Affiliations

  1. College of Energy and Mining Engineering, Shandong University of Science and Technology, Qingdao, 266590, China

    Shuzheng Song

  2. State Key Laboratory of Mining Disaster Prevention and Control Co-founded by Shandong Province and the Ministry of Science and Technology, Shandong University of Science and Technology, Qingdao, 266590, China

    Shuzheng Song, Gang Zhou, Jinjie Duan, Qunzhi Meng, Biao Sun & Yongmei Wang

  3. College of Safety and Environmental Engineering, Shandong University of Science and Technology, Qingdao, 266590, China

    Gang Zhou, Jinjie Duan, Qunzhi Meng, Biao Sun & Yongmei Wang

Authors
  1. Shuzheng Song
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  2. Gang Zhou
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  3. Jinjie Duan
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  4. Qunzhi Meng
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  5. Biao Sun
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  6. Yongmei Wang
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Contributions

All the authors contributed to the study conception and design. Shuzheng Song, Jinjie Duan, Qunzhi Meng prepared the data, experimented, and analyzed. The first draft of this manuscript was written by Shuzheng Song, Yongmei Wang modeled the model, and Professors Gang Zhou and Biao Sun guided the whole process. All the authors commented on previous versions of the manuscript. All the authors read and approved the final manuscript.

Corresponding author

Correspondence to Biao Sun.

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All analyses are based on previously published research. The research does not involve ethical and moral issues, so no moral approval is required.

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We would like to submit the enclosed manuscript entitled “CFD simulation of multi-phase and multi-component diffusion of air-dust-gas in a fully mechanized mining face,” which we wish to be considered for publication in “Environmental science and pollution research.” I would like to declare on behalf of my co-authors that the work described was original research that has not been published previously and not under consideration for publication elsewhere, in whole or in part.

Competing interests

The authors declare that they have no conflict of interest.

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Song, S., Zhou, G., Duan, J. et al. CFD simulation of multi-phase and multi-component diffusion of air-dust-gas in a fully mechanized mining face. Environ Sci Pollut Res 28, 18260–18275 (2021). https://doi.org/10.1007/s11356-020-11850-5

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  • DOI: https://doi.org/10.1007/s11356-020-11850-5

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