Every snowflake is unique—and so are their wakes
DOI: 10.1063/10.0011408
Every snowflake is unique—and so are their wakes lead image
Studying snowflake behavior is crucial for understanding snow distribution and precipitation on Earth. As a snowflake drops toward the ground, it creates a trailing wake structure. That wake will develop differently depending on the snowflake’s shape and falling velocity, along with other factors such as turbulence in the surrounding air.
In this first comparison of its kind, Tagliavini et al. explored the differences between numerical simulations of fixed snowflakes and time-resolved 3D Particle Tracking Velocimetry experiments at low and moderate to high Reynolds number.
Modeling a moving particle is computationally expensive, so the team’s numerical simulations instead have a fixed snowflake with an airflow around it. On their own, experiments of free-falling particles have limited temporal and spatial resolution compared to the numerical model.
“The computational model helps in the sense that the resolution is much higher, but it lacks some part of the physics because the particle is fixed and not moving,” said author Giorgia Tagliavini. “So, we compensate with information on the falling behavior that we observed in the experiments.”
By matching the Reynolds number in both methods, the researchers found good agreement for the snowflake wake under steady falling conditions, which are generally associated with low Reynolds number. However, under unsteady falling conditions, the strong perturbation in the wake structure, caused by the large oscillations of the falling snow particle during the experiments, differed significantly from the model.
The authors plan to investigate if including extreme particle orientations in the model can better reproduce unsteady falling conditions, and to perform modal analysis to understand how complex snowflake shapes affect the spatial and temporal flow patterns in the wake.
Source: “Wake characteristics of complex-shaped snow particles: Comparison of numerical simulations with fixed snowflakes to time-resolved Particle Tracking Velocimetry experiments with free-falling analogs,” by Giorgia Tagliavini, Majid Hassan Khan, Mark McCorquodale, Chris Westbrook, and Markus Holzner, Physics of Fluids (2022). The article can be accessed at https://doi.org/10.1063/5.0089759 .
