Prediction of droplets characteristic diameters and polydispersity index induced by a bifluid spraying nozzle by the means of dimensional analysis

Prédiction, par le biais de l'analyse dimensionnelle, des diamètres caractéristiques des gouttelettes et de l'indice de polydispersité lors de la pulvérisation par une buse bifluide

Kevin Lachin (1) , M. Niane (1) , M. Person (2) , J. Mazet (2) , G. Delaplace (3) , C. Turchiuli (1)

1 SayFood - Paris-Saclay Food and Bioproduct Engineering
2 SOREDAB
3 UMET - Unité Matériaux et Transformations - UMR 8207

This work focuses on the study of sprays generated through a bifluid nozzle and the modelling of characteristic spray properties (two characteristic diameters and a polydispersity index) using dimensional analysis. Two types of dimensionless models were identified for each spray target property from the 75 experimental points considered. The first type used a conventional monomial-exponential shape equation, and the second applied shape identification through machine-learning. Although conventional models of the first type were mostly satisfactory when considering the characteristic diameters, they nevertheless showed clear limitations addressed by the machine-learning identified models. The conventional approach also failed to identify a satisfactory equation for the polydispersity index. The machine-learning approach provided an equation identifying this index to the main dimensionless parameters governing atomization. This identification provides a foundation for proposing a two-parameters dimensionless model that predicts spray particle size distribution. The combination of dimensional analysis with machine-learning equation identification thus paves the way to physically rigorous and easy-to-use models capable of predicting characteristic properties and full distributions.

Mots clés: Dimensional analysis; bifluid nozzle; droplet size distribution modeling; atomization; machine learning modeling

Domaines: Sciences de l'ingénieur [physics]

Kevin Lachin, M. Niane, M. Person, J. Mazet, G. Delaplace, et al.. Prediction of droplets characteristic diameters and polydispersity index induced by a bifluid spraying nozzle by the means of dimensional analysis. Chemical Engineering Science, 2023, 265, pp.118187. ⟨10.1016/j.ces.2022.118187⟩. ⟨hal-03846328⟩