Data-driven splashing threshold model for drop impact on dry smooth surfaces

Abstract

We propose a data-driven threshold model to redefine the boundary between deposition and splashing for drop impact on dry smooth surfaces. The starting point is the collection and digitization of multiple experimental sources with varying impact conditions. The model is based on the theory of Riboux and Gordillo [Riboux and Gordillo, “Experiments of drops impacting a smooth solid surface: A model of the critical impact speed for drop splashing,” Phys. Rev. Lett. 113, 024507 (2014)] and is obtained by an uncertainty quantification analysis coupled with machine learning. The uncertainty quantification analysis elucidates the relevance of the impact condition uncertainties when estimating the splashing parameter. The proposed threshold model is trained using a support vector machine algorithm variant that includes uncertainty as a hyperparameter. This threshold model is generalized by complexity reduction and is eightfold cross-validated on the reference data. The results reveal a dependency of the splashing threshold on the impact velocity, the liquid viscosity, the surface tension, and the gas density. Detailed quantification of the prediction performance and a comparison with state-of-the-art models show that the proposed threshold model is the most accurate model to describe the boundaries between deposition and splashing for a wide range of impact conditions. The simplicity and accuracy of this model make it an alternative to existing approaches.

Effect of ambient gas on cavity formation for sphere impacts on liquids

“…The Gordillo-Riboux model has since been expanded by Pierzyna et al using a data-driven threshold model which re-defines the threshold for droplet splashing on a dry smooth surface by collating a large number of experimental sources with different conditions and analysing the data with an uncertainty qualification analysis combined with machine learning [31]. The Gordillo-Riboux model can be considered as the special case where the parameter β for determining splashing is a constant (in the general case, each impact parameter has a different dependence on β).…”

Prediction of the morphological evolution of a splashing drop using an encoder–decoder

“…In recent years, with the increasing availability and accessibility of data, data-driven approaches-and machine learning in particular-have attracted increasing attention among fluid researchers as a faster and cheaper alternative or complement to experimental and numerical studies [32][33][34][35][36][37][38][39]. Regarding drop impacts, several machine-learning-based studies have been carried out [40][41][42][43]. Notably, a number of studies on predicting the maximum spreading factor of a non-splashing drop under various conditions were published in 2022.…”

Physics of droplet impact on flexible materials: A review

“…The examples include rain drops falling on insect wings, splashing of pesticide on plant leaves, coffee stain, food industry and inkjet printing. [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19] Physics of droplet-substrate interaction has been an attractive field of science in various technologies including healthcare, aerospace, electronics, coatings, printings and materials science. Previous studies about droplet impact on rigid substrates demonstrated following physical events: deposit (adhesion), breakup (fragmentation), prompt splash, corona splash, partial bounce and complete bounce as illustrated in Figure 1.…”

“…The examples include rain drops falling on insect wings, splashing of pesticide on plant leaves, coffee stain, food industry and inkjet printing. 1–19 Physics of droplet-substrate interaction has been an attractive field of science in various technologies including healthcare, aerospace, electronics, coatings, printings and materials science. 20…”

“…This happens when the contact line advances on the substrate as a result of the competition between adhesion and cohesion forces at the three-phase contact line. 19,50–53,55,56,70–72,100,108,132,134–160 The adhesion force leads to the advancement the droplet on the substrate while the cohesion force resists the droplet advancement on the substrate.…”