3D reconstruction of the flow and vortical field in a rotating sharp "U” turn channel

Particle image velocimetry experiments have been carried out to obtain visualizations and measurements of the main and secondary flow fields in a square channel with a sharp "U” turn. Both the main and the secondary flow fields have been used to perform a 3D reconstruction of the mean flow and vortical fields in the turn region and in the outlet duct. In order to study the influence of the rotation, tests both in stationary (absence of rotation, Re=20,000) and in rotating (Re=20,000 and Ro=0.3) conditions have been performed. The results show that the Coriolis and centrifugal forces, caused by the rotation, yield strong modifications to the symmetrical flow and vortical fields that are generated, in the static case, only by the abrupt inversion of the flow directio

Turbulence properties in jets with fractal grid turbulence

We carry out high-resolution particle image velocimetry experiments to characterize the flow field of fractal grids located at the exit section of a turbulent round jet. We comment on the mean flow organization and on the turbulence properties of such jets by comparing the results with those obtained with square grids, a regular grid (having the same effective mesh length) and a jet without turbulator. We find that, different from the case of decaying grid turbulence, a correction must be accounted for to properly scale the turbulence intensity profiles with a length scale based on grid parameters. We perform a low-order reconstruction of the velocity field based on the most energetic proper orthogonal decomposition modes and we compare the flow-field structure produced in the lee of fractal grids with a single square object and the jet without turbulator. The typical turbulence intensity profile detailed in Cafiero et al. (Phys. Fluids, vol. 27, 2015, 115103) for jets with fractal grids is produced by the interaction of small eddies shed by the central grid item. In the single square grid case, the turbulence is built upon the interaction between larger structures. Conversely, the interaction of the outward spreading wake with the external shear layer produces pairs of vortical structures, which we relate to the higher entrainment rate featured by jets with fractal turbulators. The secondary grid iterations have a disruptive effect on the turbulence transport, with a corresponding large correlation between the velocity fluctuations at the jet core with those at the jet shear layer

Ensemble 3D PTV for high resolution turbulent statistics

A method to extract turbulent statistics from three-dimensional (3D) PIV measurements via ensemble averaging is presented. The proposed technique is a 3D extension of the ensemble particle tracking velocimetry methods, which consist in summing distributions of velocity vectors calculated on low image density samples and then extract the statistical moments from the velocity vectors within sub-volumes, with the size of the sub-volume depending on the desired number of particles and on the available number of snapshots. The extension to 3D measurements poses the additional difficulty of sparse velocity vectors distributions, thus requiring a large number of snapshots to achieve high resolution measurements with a sufficient degree of accuracy. At the current state, this hinders the achievement of single-voxel measurements, unless millions of samples are available. Consequently, one has to give up spatial resolution and live with still relatively large (if compared to the voxel) sub-volumes. This leads to the further problem of the possible occurrence of a residual mean velocity gradient within the sub-volumes, which significantly contaminates the computation of second order moments. In this work, we propose a method to reduce the residual gradient effect, allowing to reach high resolution even with relatively large interrogation spots, therefore still retrieving a large number of particles on which it is possible to calculate turbulent statistics. The method consists in applying a polynomial fit to the velocity distributions within each sub-volume trying to mimic the residual mean velocity gradient.Stefano Discetti was partially supported by Grant TRA2013-41103-P of the Spanish Ministry of Economy and Competitiveness. This grant includes FEDER funding. Nereida Agüera was supported by the fellowship Beca de colaboración 2015/16 of the Spanish Ministry of Education

The von Kármán street behind a circular cylinder: flow control through synthetic jet placed at the rear stagnation point

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Influence of Machine Learning-based active flow control on the turbulent statistics of the flow over a circular cylinder

The aim of the present paper is to investigate the capabilities of Machine Learning (ML) to reduce the aerodynamic drag of a circular cylinder in cross flow, by actively controlling its wake with a synthetic jet