Control of long-range correlations in turbulence

Abstract

The character of turbulence depends on where it develops. Turbulence near boundaries, for instance, is different than in a free stream. To elucidate the differences between flows, it is instructive to vary the structure of turbulence systematically, but there are few ways of stirring turbulence that make this possible. In other words, an experiment typically examines either a boundary layer or a free stream, say, and the structure of the turbulence is fixed by the geometry of the experiment. We introduce a new active grid with many more degrees of freedom than previous active grids. The additional degrees of freedom make it possible to control various properties of the turbulence. We show how long-range correlations in the turbulent velocity fluctuations can be shaped by changing the way the active grid moves. Specifically, we show how not only the correlation length but also the detailed shape of the correlation function depends on the correlations imposed in the motions of the grid. Until now, large-scale structure had not been adjustable in experiments. This new capability makes possible new systematic investigations into turbulence dissipation and dispersion, for example, and perhaps in flows that * These authors contributed equally: N.

Experimental Study of the Bottleneck in Fully Developed Turbulence

“…A detailed account of the autunomous active grid and the algorithm is given in Ref. [17] and briefly summarized here. The algorithm updates the angle of each flap every 0.1s.…”

Exploring the capabilities of active grids

“…Many new experiments were initiated, which are summarized in a recent review by Mydlarski (2017). Alternating the excitation methods, grids are used (a) to generate homogeneous and isotropic turbulence (HIT) (see Mydlarski andWarhaft 1996, 1998;Shen and Warhaft 2000;Poorte and Biesheuvel 2002;Larssen and Devenport 2011;Hearst and Lavoie 2015;Griffin et al 2019;Cekli et al 2015), (b) to create a defined shear flow in the wind tunnel (see Cekli and van de Water 2010;Hearst and Ganapathisubramani 2017), and (c) to reproduce atmospheric wind conditions either directly (see Reinke et al 2017;Kröger et al 2018a) or by their statistical properties (see Knebel et al 2011;Good and Warhaft 2011;Neuhaus et al 2020).…”

“…An even higher variability can be found for the grid by Bodenschatz et al (2014), which allows to control all flaps individually. This grid allows for greater control of the spatial velocity correlations (Griffin et al 2019).…”

The impact of upstream turbulence on a plane jet

“…In the present study, we focus on modulating the flow immediately upstream of the nozzle and measuring what impact this has on the near-field jet spreading and the far-field centreline statistics. The upstream turbulence is generated with a novel active grid where each wing is controlled independently, similar to the work of Griffin et al (2019). The active grid is used because it can produce high levels of turbulence and orders of magnitude changes in the length scales (Larssen and Devenport 2011; Hearst and Lavoie 2015).…”