Optimization of an axial-flow mine ventilation fan based on effects of design parameters

Underground mining safety relies heavily on ventilation, which is energy and maintenance intensive. An opti-mization method for an axial-flow Chinook ventilation fan, analyzing parameters like angle of attack, tip clearance, rotation speed, hub-to-tip ratio, and rotor blade count using Design of Experiments (DOE) and regression is proposed. The numerical solutions are confirmed with experimental data. Considering a Mach number of 0.4, compressible flow conditions are analyzed using a two-equation turbulence model. During stall, fan efficiency drops to 47 %. High fatigue probability is observed at the blade-root intersection in stall condi-tions. The optimization pinpoints several operational configurations that meet the required performance while preserving the fan's structure. A particular off-design optimal point indicates that reducing the blade count and decreasing the tip-clearance lead to an average performance improvement of 9 %, with significant benefits in noise, cost, weight, and energy consumption. The numerical forecasts demonstrate precision with an average discrepancy of less than 5 %.