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Article Dans Une Revue Journal of Fluid Mechanics Année : 2017

Unsteady flow dynamics reconstruction from mean flow and point sensors: an experimental study

Résumé

This article presents a reconstruction of the unsteady behaviour of a round jet at a Reynolds number equal to 3300, from the sole knowledge of the time-averaged flow field and one pointwise unsteady measurement. The reconstruction approach is an application of the work of Beneddine et al. (J. Fluid Mech., vol. 798, 2016, pp. 485–504) and relies on the computation of the dominant resolvent modes of the flow, using a parabolised stability equations analysis. To validate the procedure, the unsteady velocity field of the jet has been characterised by time-resolved particle image velocimetry (TR-PIV), yielding an experimental reference. We first show that the dominant resolvent modes are proportional to the experimental Fourier modes, as predicted by Beneddine et al. (J. Fluid Mech., vol. 798, 2016, pp. 485–504). From these results, it is then possible to fully reconstruct the unsteady velocity and pressure fluctuation fields, yielding a flow field that displays good agreement with the experimental reference. Finally, it is found that the robustness of the reconstruction mainly depends on the location of the pointwise unsteady measurement, which should be within energetic regions of the flow, and this robustness as well as the quality of the reconstruction can be greatly improved by considering a few pointwise measurements instead of a single one. The effects of other experimental parameters on the reconstruction, such as the size of the interrogation window used for the TR-PIV processing and the accuracy of the positioning of the sensors, are also investigated in this paper.
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Dates et versions

hal-01799822 , version 1 (25-05-2018)

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Samir Beneddine, Robin Yegavian, Denis Sipp, Benjamin Leclaire. Unsteady flow dynamics reconstruction from mean flow and point sensors: an experimental study. Journal of Fluid Mechanics, 2017, 824, p. 174-201. ⟨10.1017/jfm.2017.333⟩. ⟨hal-01799822⟩
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