Single hot-wire velocity measurements have been conducted along a three-dimensional measurement grid to capture the flow-field induced by a 45°inclined slotted pulsed jet. Based on the periodic behavior of the flow, two different estimation methods have been implemented. The first one, considered as the reference base-line, is the conditional approach which consists in the redistribution of the experimental data into spaceand time-resolved three-dimensional velocity fields. The second one uses a neural network to estimate 3D velocity fields given spatial coordinates and time. This paper compares the two methods for a complete flow-field estimation based on hot-wire measurements. Results suggest that the neural network is tailored to capture the phase-averaged dynamic response of the jet induced by the actuator, and identify the coherent structures in the flow field. Interesting performances are also observed when degrading the learning database, meaning that neural networks can be used to drastically improve the temporal or spatial resolution of a flow field estimation compared to the experimental data resolution.

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Sweeping jets are an emerging type of actuators that have gained interest due to their potential use in flow control applications. The working principle of these devices is based on the bi-stable attachment of a jet to adjacent walls. They are able to produce unsteady blowing within a wide range of operating frequencies. Nevertheless, the state of art shows a lack of space-time characterization of these actuators for high sweeping frequencies. This paper resents a conditional approach that reconstructs the spatial dynamic response of sweeping jets for sweeping frequencies above 500 Hz. The time-dependent velocity is measured with two single-hot-wire sensors: a reference one placed at the edge of the exit nozzle, and a flying one. The method is then tested to characterize the flow at the exit nozzle of an in-house sweeping jet actuator with 1mm space resolution, and 50 µs time resolution. These measurements are performed with a sweeping frequency of 639 Hz. Overall this paper demonstrates that the conditional approach is very useful for understanding the physics of flow control actuators.