Experimental verification of permeability and inertial resistance coefficient model in the goaf

ABSTRACT

Numerical simulation is an important method of studying the flow, temperature, and concentration fields in the goaf. In a simulation, the permeability and inertial resistance coefficient are the key factors. For the verification of goaf permeability model, scholars usually use field data for verification. However, the site conditions of coal mine are complex, and the gas emission and air leakage in the goaf are difficult to control, which will lead to inaccurate verification of permeability model. Therefore, this paper verifies the goaf permeability model under experimental conditions, which can ensure that the experimental conditions are consistent with the numerical simulation conditions and realize the accurate verification of the model. An experimental scenario of a thermodynamic disasters in the goaf can be built, based on gas flow, and heat and mass transfer in porous media. The permeability and inertial resistance coefficient models can then be experimentally verified. Experimental results show that methane concentration increases with increased distance from the working face, hence the methane concentration in the return roadway side is higher than that in the intake roadway side. As distance from the coal seam floor increases, the methane concentration shows a downward trend. After releasing methane from the floor for 120 min, the concentration field inside the goaf stabilizes; therefore, coal spontaneous combustion experiments are started after a 120 minute lapse time period. In a numerical simulation, the goaf is the porous media seepage model, and the boundary conditions of the numerical model are set according to experimental conditions. The numerical simulation results concurred well with the experimental results; verifying the suitability of the authors’ proposed goaf permeability and inertial resistance coefficient model.

KEYWORDS:

• Goaf
• permeability
• inertial resistance coefficient
• porosity
• particle size distribution

Acknowledgments

Financial supports from the National Key Research and Development Project(No. 2018YFC0807903) are sincerely acknowledged.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the National Key Research and Development Project [2018YFC0807903].