Predictive Modelling of the Droplet Size Distribution in Swirl Nozzles under Varying Operating Parameters

Abstract

Droplet size distribution is a critical parameter in liquid atomization because it governs spray coverage, evaporation rate, mixing efficiency, and overall process performance. Predicting droplet-size characteristics remains challenging due to the complex interactions among centrifugal forces, liquid-sheet instability, and operating conditions in swirl nozzles. This study presents a predictive modelling approach for estimating droplet size distribution under varying operating parameters. The significance of the model is directly linked to the combined effects of the selected operating parameters, spray pressure, exit orifice diameter, swirl chamber length-to-diameter ratio, and nozzle spraying height, which were systematically varied to evaluate their influence on droplet size distribution. The model evaluation yielded a p-value of 0.00992 and F-value of 22.85 at 95% confidence level, indicating that variations in these parameters collectively have a statistically significant effect on spray characteristics. The coefficient of determination (R²) of 0.4244 shows that the model explains 42.44% of the variation in droplet size distribution, while the coefficient of variation (CV) of 2.90 (less than 10) confirms good reproducibility. Results indicate that increased operating pressure produces finer droplets, whereas nozzle geometry significantly influences distribution uniformity. The predictive model provides a useful tool for spray system design and optimization, reducing reliance on extensive experimental testing and enhancing spray efficiency in practical applications.