[Paper] Estimating Flow Velocity and Vehicle Angle-of-Attack from Non-invasive Piezoelectric Structural Measurements Using Deep Learning

Summary

This paper presents a novel, non-invasive deep learning method to estimate critical aerodynamic state variables like vehicle velocity and angle of attack (AoA). It utilizes a dense array of piezoelectric sensors mounted on the interior skin of an aeroshell to capture vibration measurements, replacing traditional intrusive flow instrumentation such as pitot tubes. This approach promises more accurate estimations crucial for aerodynamic load prediction, flight control, and model validation.

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