A deep learning model trained on PIV data from one street-canyon geometry can generate 500 plausible turbulent flow snapshots for a different canyon geometry, matching mean statistics and dominant structures.
Study of interscale interactions for turbulence over the obstacle arrays from a machine learning perspective
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Predicting Turbulence Structure In Street-Canyon Flows using Deep Generative Modeling
A deep learning model trained on PIV data from one street-canyon geometry can generate 500 plausible turbulent flow snapshots for a different canyon geometry, matching mean statistics and dominant structures.