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This study investigates the influence of the surrounding gas on a droplet impacting a smooth dry glass surface at high Weber and Reynolds numbers. It was performed using a flywheel experiment and different gases at ambient pressure. We analyzed the splashing outcome by measuring the size, velocity, and angle of the secondary droplets and by calculating the total volume ejected. We show that gas entrapment is not the mechanism responsible for splashing at high Weber and Reynolds numbers. We demonstrate that splashing is influenced by the density, followed by the viscosity, and last by the mean free path of the surrounding gas. Furthermore, the surrounding gas primarily affects the number of secondary droplets ejected and their ejection angle, whereas the droplet size and horizontal velocity are independent of the surrounding gas properties. We provide the first theoretical expression for the total volume ejected using the theory of Riboux and Gordillo [Phys. Rev. Lett. 113, 024507 (2014)], which attributes the secondary droplet generation to a lift force experienced by spreading lamella. The relationship between the ejected volume and the splashing parameter is described by a power function.

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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.

The focus of this article is to describe the evolution of the spreading diameter and secondary droplets generated by splashing. High-speed visualization was used to study the time evolution of water droplets impacts with dry surfaces at Weber numbers between 3,500 and 10,000. Different prediction models of the maximal spreading diameter have been compared with each other and with the experimental data. A similarity between the spreading rates was observed in the last stage of the impact at high Weber numbers. The time evolution of the secondary droplets and the formation of the crown was observed and analyzed at the different Weber numbers.