Research on dust control and ventilation parameter optimization in roadhead mining based on response surface methodology

At fully mechanized heading faces, dust accumulation in roadways poses persistent safety and occupational health risks, particularly under long-forcing, short-exhaust hybrid ventilation conditions, with the return-air-side corners being critical dust accumulation zones. This study aimed to optimize the ventilation system and reduce dust mass concentrations by combining numerical simulations with response surface methodology (RSM). A simplified geometric model was developed in SpaceClaim, and numerical simulations were performed using ANSYS Fluent. Single-factor analysis and a Box--Behnken experimental design were employed to investigate the effects of the exhaust duct inlet angle, exhaust-to-forcing airflow ratio, exhaust duct inlet diameter, and forcing duct outlet diameter. The results showed that the exhaust duct inlet angle and diameter were the dominant factors affecting dust distribution. Through multi-objective optimization, the dust mass concentrations at the lower and upper return-air-side corners were reduced by 58% and 34%, respectively. Validation using a 1:4 scaled-model experimental platform showed that the experimental measurements agreed well with the numerical predictions, with relative errors below 5%. This study developed an integrated research framework combining numerical simulation, response surface optimization, and scaled-model experimental validation to address dust accumulation in the return-air-side corner regions under a long-forcing, short-exhaust hybrid ventilation system. The proposed framework enables the coupled analysis of multiple ventilation parameters and the dual-objective optimization of dust mass concentrations at the upper and lower return-air-side corners, providing a reference for dust control and ventilation parameter optimization under similar operating conditions.