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An experiment was performed using stereo particle image velocimetry (SPIV) in the Laboratoire de Mécanique des Fluides de Lille boundary layer facility to determine all the derivative moments needed to estimate the average dissipation rate of the turbulence kinetic energy $\epsilon = 2 \nu \langle {\mathsf{s}}_{ij}{\mathsf{s}}_{ij} \rangle$ , where ${\mathsf{s}}_{ij}$ is the fluctuating strain rate and $\langle ~\rangle$ denotes ensemble averages. Also measured were all the moments of the full average deformation rate tensor, as well as all of the first, second and third fluctuating velocity moments except those involving pressure. The Reynolds number was $Re_\theta = 7634$ or $Re_\tau = 2598$ . The present paper gives the measured average dissipation, $\epsilon$ and the derivative moments comprising it. The results are compared with the earlier measurements of Balint, Wallace & Vukolavcevic (J. Fluid Mech., vol. 228, 1991, pp. 53–86) and Honkan & Andreopoulos (J. Fluid Mech., vol. 350, 1997, pp. 29–96) at lower Reynolds numbers and to new results from a plane channel flow DNS at comparable Reynolds number. Of special interest is the prediction by George & Castillo (Appl. Mech. Rev., vol. 50, 1997, pp. 689–729) and Wosnik, Castillo & George (J. Fluid Mech., vol. 421, 2000, pp. 115–145) that $\epsilon ^+ \propto {x_2^+}^{-1}$ for streamwise homogeneous flows and a nearly indistinguishable power law, $\epsilon \propto {x_2^+}^{\gamma -1}$ , for boundary layers. In spite of the modest Reynolds number, the predictions seem to be correct. Then the statistical character of the velocity derivatives is examined in detail, and a particular problem is identified with the breakdown of local homogeneity inside $x_2^+ = 100$ . A more general alternative for partially homogeneous turbulence flows is offered which is consistent with the observations. With the help of DNS, the spatial characteristics of the dissipation very near the wall are also examined in detail.

International audience; The denoising of Lagrangian trajectories based on regularized B-spline is investigated. The aim is to find systematic criteria for optimization of algorithms used in 4D-PTV in order to optimize the quality of 4D-PTV measurements of turbulent flows as well as high-order of turbulence statistics. We introduce and adapt to this context two innovative tuning strategies which are commonly used in the Tikhonov regularization of inverse problems based on -curve shape and Normalized Cumulative Periodogram (NCP). The corresponding strategies are tested on synthetic Lagrangian trajectories computed from Direct Numerical Simulation with additional white Gaussian noise. Error-based quantities like Signal-to-Noise Ratio as well as statistical Lagrangian quantities are investigated to compare the different strategies. We then apply the algorithm to experimental data from a 4D-PTV Lagrangian measurements in a turbulent Von Kármán flow. We show the ability of those strategies to optimize the quality of the signal compared to conventional methods. Moreover, the strategies are more adaptable to real experimental noise.

In this paper, the turbulence fields generated by a group of modified fractal grids, referred to as the rectangular fractal grids (RFGs), are documented and discussed. The experiments were carried out using hot-wire anemometry in three facilities at Imperial College London and the Laboratory of Fluid Mechanics in Lille, France. Due to the large Reynolds number of the resulting turbulence, several data processing methods for turbulence properties are carefully evaluated. Two spectral models were adopted, respectively, to correct the large and small wave-number ranges of the measured spectrum. After the technical discussion, the measurement results are presented in terms of one-point statistics, length scales, homogeneity, isotropy, and dissipation. The main conclusions are twofold. First, the location of maximum turbulence intensity xpeak is shown to be independent of the inlet Reynolds number but dependent on the ratio between the lengths of the largest grid bars in the transverse and vertical directions. This is crucial to the production of prescribed features of turbulent flows in laboratory. Second, these RFG-generated turbulent flows are shown to be quasihomogeneous in the decay region for x/xpeak>1.5, but the isotropy is poorer than that of the previous studied fractal square grid-generated turbulence. In the beginning of the decay region, a decreasing pattern of the integral length scale Lu and Taylor microscale λ was observed, yet the ratio Lu/λ remained roughly constant along the centerline, so Cε∼Re−1λ, complying with the nonequilibrium scaling relation reported in previous studies for various turbulent flows.

Uniform blowing in wall bounded shear flows is well known for its drag reducing effects and has long been investigated ever since. However, many contemporary and former research on this topic has c...

We propose a novel closed-loop control strategy of turbulent flows using machine learning methods in a model-free manner. This strategy, called Machine Learning Control (MLC), allows – for the first time – to detect and exploit all enabling nonlinear actuation mechanisms in an un-supervised automatic manner. In this communication, we focus on MLC applications for in-time control of experimental shear flows and demonstrate how it outperforms state-of-the-art control. In particular, MLC is applied to three different experimental closed-loop control setups: (1) the TUCOROM mixing layer tunnel, (2) the Gortler PMMH water tunnel with a backward facing step, and (3) the LML Boundary Layer wind tunnel with a separating turbulent boundary layer. In all three cases, MLC finds a control which yields a significantly better performance with respect to the given cost functional as compared to the best previously tested open-loop actuation. We foresee numerous potential applications to most nonlinear multiple-input multiple-output (MIMO) flow control problems, particularly in experiments. In particular, the model-free architecture of MLC enables its application to a large class of complex nonlinear systems in all areas of science.

International audience; The flow over a ramp model is characterised in detail in the present study. In the selected configuration, a turbulent boundary layer developed on a flat plate is first accelerated in a curved contraction. It is then submitted to a mild adverse pressure gradient on a flat plate followed by a separation above a flap. Inlet boundary conditions and pressure distribution are provided to allow numerical simulations. The flow in the mild adverse pressure gradient region is characterised with hot-wire anemometry. In this region, the boundary layer thickness is of the order of 20 cm, the momentum Reynolds number is about 11,000 and the Clauser pressure gradient parameter β in the stabilised region is about 0.4. Particular emphasis is laid on the separation to provide quantitative information to evaluate turbulence models. This is achieved through a large streamwise two-dimensional two-component particle image velocimetry (2D2C PIV) plane which contains all the separation bubble and part of the flow upstream and downstream of it. The separation border is detected using the backflow coefficient, resulting in a separation length of about 3.49 Hs (with Hs the flap step height) and a maximum height of about 0.17 Hs. The Reynolds stresses and their main production terms are also determined. A region of high turbulence intensity develops above the separation border for all the measured components. The production of dominates the production of turbulent kinetic energy which implies a redistribution from to to explain the increase observed. The production term drives the production of in the first part of the flap which is not the case for zero pressure gradient boundary layers. Finally, a high similarity is observed between and as the production of the latter is dominated by . This flow appears as a challenging test case for Reynolds averaged Navier–Stokes (RANS) and large eddy simulation (LES) validation.