Calculation method of roadway ventilation resistance based on fractal characterization of wall roughness

Accurate and rapid measurement of ventilation resistance is crucial for achieving effective real-time airflow control in underground ventilation systems. Conventional measurement methodologies are frequently constrained by operational inefficiency and substantial measurement inaccuracies. To overcome these limitations, this study proposes an innovative approach employing fractal theory to quantify roadway surface roughness and determine ventilation resistance parameters. The surface roughness characterization utilizes two fractal descriptors: fractal dimension (D) and scale parameter (C). Through systematic experimentation and computational fluid dynamics (CFD) simulations of rough-walled pipe flows, a novel ventilation resistance prediction model has been established. The validation process incorporates comprehensive field data acquired from operational roadways in the Kailuan full-scale roadway. The three-dimensional (3D) laser scanning technology was implemented to obtain high-resolution point cloud data of roadway surfaces, enabling precise calculation of fractal roughness parameters. Comparative analysis reveals a maximum deviation of 8.68% between CFD simulation results and the proposed model's predictions. Furthermore, the relative error between the novel computational conventional field measurement techniques was reduced to 2.36%. These findings substantiate the technical validity of the proposed methodology and confirm its capability to effectively quantify the impact of 3D surface roughness characteristics on ventilation resistance dynamics.