Collaborative Research: Droplet breakup in homogenous turbulence: model validation through experiments and direct numerical simulations

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The breakage of liquid droplets in a turbulent fluid flow is an important phenomenon in numerous engineering, scientific, and environmental applications. For example, many chemical and pharmaceutical processing techniques involve droplets breaking as components mix and react. Droplet breakage is also important in environmental applications such as the dynamics of oil spills and their cleanup, and in the leakage of underground storage tanks into water sources. Scientists and engineers have worked to develop computational techniques to predict complex fluid processes such as those listed above. A key component of these computational techniques are models that accurately describe droplet breakage and its dependence on flow parameters such as turbulence intensity and droplet properties such as viscosity, surface tension, diameter, and density. This project will conduct a series of experiments to measure droplet breakage under highly controlled conditions. Data from the experiments will be used to improve droplet breakage models.This project will investigate effects of turbulence intensity and fluid properties on droplet breakage by performing detailed experiments and using these data to improve and validate droplet breakage models. In the experiments, individual droplets will be injected into a flow chamber that has been designed to generate a uniform turbulent field. The turbulent field will be characterized using particle image velocimetry. High-speed movies will be captured of the droplet as it is deformed and then broken by the turbulence. The experiments will be repeated for different droplet diameters and fluids, and large ensembles of droplet breakage movies will be analyzed statistically to yield data on the droplet breakup process, including droplet size and shape. Moreover, because the timing of successive images in the movies will be known, droplet breakage event timings and frequencies can be determined by analyzing each image sequence. Graduate and undergraduate students will work on this project. Local high-school students will be recruited to participate as part of the research team through the Ames (Iowa) High School Enhanced Learning Program.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.