ERC Starting Grant · 2020
Next-generation flow diagnostics for control
Fast-paced advancements of hardware and machine-learning algorithms have triggered successful applications of active flow control, even though mainly limited to laboratory-scale applications. One of the main limits resides in the lesson we are able to learn today from experiments. We can successfully train actuators with probes in a controlled environment to reach a certain goal, e.g. aerodynamic drag minimization or noise reduction; on the other hand, an experimental technique that provides a full description of the flow is not available, thus generalization of the actuation effects to real applications is often prohibitive. The objective of NEXTFLOW is to conceive the next-generation…
From the public funding record at EU CORDIS. Describes the funded project, not the reviews below.