The frictional resistance coefficient of ventilation of a roadway in a coal mine is a very important technical parameter in the design and renovation of mine ventilation. Calculations based on empirical formulae and field tests to calculate the resistance coefficient have limitations. An inversion method to calculate the mine ventilation resistance coefficient by using a few representative data of air flows and node pressures is proposed in this study. The mathematical model of the inversion method is developed based on the principle of least squares. The measured pressure and the calculated pressure deviation along with the measured flow and the calculated flow deviation are considered while defining the objective function, which also includes the node pressure, the air flow, and the ventilation resistance coefficient range constraints. The ventilation resistance coefficient inversion problem was converted to a nonlinear optimisation problem through the development of the model. A genetic algorithm (GA) was adopted to solve the ventilation resistance coefficient inversion problem. The GA was improved to enhance the global and the local search abilities of the algorithm for the ventilation resistance coefficient inversion problem.

The roof-caving step scale goaf behind the working face is sensitive to the region’s spontaneous combustion and gas concentration distribution, including many rock block cracks and holes. A severe deviation from the dynamics of fluids in porous media by representative element volume (REV), leading to the results of Computational Fluid Dynamics (CFD) simulation, has a significant error. A heterogeneous two-dimensional pore network model was established to simulate the goaf flow accurately. The network was first created using the simple cubic lattice in the OpenPNM package, and the spatial distribution of the “O-ring” bulking factor was mapped to the network. The bulking factor and Weibull distribution were combined to produce the size distribution of the pore and throat in the network. The constructed pore network model was performed with single-phase flow simulations. The study determined the pore structure parameters of the pore network through the goaf’s risked falling characteristics and described the flow field’s distribution characteristics in the goaf. The permeability coefficient increases as pore diameter, throat diameter, pore volume and throat volume increase and increases as throat length decreases. The correlation between throat volume and permeability coefficient is the highest, which indicates that the whole throat is the main control factor governing the air transport capacity in the goaf. These results may provide some guidelines for controlling thermodynamic disasters in the goaf.