A Hybrid Computer Vision and Machine Learning Approach for Robust Vortex Core Detection in Fluid Mechanics Applications
Hazem Ashor Amran Abolholl,
Tom-Robin Teschner,
Irene Moulitsas
Abstract:Vortex core detection remains an unsolved problem in the field of experimental and computational fluid dynamics. Available methods such as the Q, delta and swirling-strength criterion are based on a decomposed velocity gradient tensor but detect spurious vortices (false positives and false negatives), making these methods less robust. To overcome this, we propose a new hybrid machine learning approach in which we used a convolutional neural network to detect vortex regions within surface streamline plots and a… Show more
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