Fuel dropsize prediction model on prefilming airblast nozzle at pressurized operating conditions

Due to the scarcity of atomization particle size data under pressurized operating conditions and the absence of physically-based particle size prediction models， a study is conducted on the fuel particle size prediction model for prefilming airblast atomizers under pressurized conditions. Through Design of Experiments （DOE）， a laser particle size analyzer was used to test the atomization particle size data under the cross-influence of multiple parameters such as air pressure， air temperature， air pressure drop， fuel temperature， and fuel-to-air ratio. Based on the surface wave instability theory， a prediction model incorporating non-dimensional parameters such as the Weber number， Reynolds number， and Ohnesorge number was established. Validation with experimental data shows that the prediction model has a maximum error of 14.1% and an average error of 5.2%， with residuals following a normal distribution. Sensitivity analysis demonstrates that the prediction model accurately captures the influence of non-dimensional parameters and experimental conditions on particle size.