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Accurately predicting entrainment in free shear flows like jets, wakes, and shallow water shear layers is crucial for industrial, environmental, and geophysical applications, yet most studies focus on wakes and jets using Eulerian statistics from 2D experiments, limiting insight into this inherently 3D, multiscale phenomenon. To bridge this gap, we will conduct cutting-edge measurements capturing 3D Lagrangian statistics, generating novel datasets that will deepen our understanding of turbulent entrainment and mixing between distinct turbulent streams. This research has direct industrial relevance, particularly in wind farms, where wake interactions with ambient turbulence impact efficiency, often leading to reliance on empirical models for wake spreading. A more precise characterization of entrainment in shear-layers will help to develop models to characterize pollutant dispersion in rivers, and the mixing phenomena across two flow streams.
Susan Gaskin
Imperial College London
Engineering
Education
McGill University
Globalink Research Award
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