Event-based imaging velocimetry for jet flow control

Abstract

This study presents the use of Event-Based Imaging Velocimetry (EBIV) for experimental jet flow control, integrating a Bayesian optimization strategy to enhance mixing in a turbulent round jet. Velocity fields are acquired using a pulsed low-power laser and an event-based vision camera, enabling time-resolved, full-field measurements at kilohertz rates. A cost function based on the spatial average of the turbulent kinetic energy is computed from EBIV measurements and used to optimize the actuation parameters of two synthetic jets located inside the nozzle, in the plane of the EBIV measurement. The proposed approach allows optimizing the control in a non-intrusive manner, with minimal sensor cost and data latency. The impact of the optimal actuation is further assessed using Spectral Proper Orthogonal Decomposition, which reveals the excitation of coherent structures across a broad spectral range, including harmonics not directly excited. These results demonstrate the potential of EBIV as a compact, high-throughput sensor tool for data-driven flow control and the development of active control strategies.