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12:20
20 mins
Event-based imaging velocimetry for jet flow control
Luca Franceschelli, Enrico Amico, Marco Raiola, Christian Willert, Jacopo Serpieri, Gioacchino Cafiero, Stefano Discetti
Session: Classical and Machine learning methods in flow control II
Session starts: Tuesday 04 November, 11:40
Presentation starts: 12:20
Room: Lecture room B
Luca Franceschelli (Universidad Carlos III de Madrid)
Enrico Amico (Politecnico di Torino)
Marco Raiola (Universidad Carlos III de Madrid)
Christian Willert (DLR Institute of Propulsion Technology)
Jacopo Serpieri (Politecnico di Torino)
Gioacchino Cafiero (Politecnico di Torino)
Stefano Discetti (Universidad Carlos III de Madrid)
Abstract:
This study investigates the use of Event-Based Imaging Velocimetry (EBIV) as a viable sensing technology for optimising open-loop jet-flow control strategies. EBIV is deployed in a jet-control experiment in which the actuation system combines both acoustic and synthetic jet forcing; the resulting velocity fields are used to evaluate the performance of the control action. The goal is to develop and assess EBIV as a fast, reliable sensor in-the-loop to support advanced flow control optimization algorithms such as Bayesian Optimization and Deep Reinforcement Learning.
Keywords: Flow control; Event-Based Imaging Velocimetry; Jet Flow; Synthetic Jets; Optimization