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.
Assessment of inner–outer interactions in the urban boundary layer using a predictive model
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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.