Prandtl and the Göttingen school

Bodenschatz, Eberhard; Eckert, Michael

doi:10.1017/cbo9781139018241.003

Cited by 30 publications

(14 citation statements)

References 69 publications

(49 reference statements)

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“…An unsteady structure of the wake appears at higher Re, and was reported by Fornberg (1988) among others [8,9]. The drag coefficient C D of a sphere, which varies with the roughness of the sphere surface and Re, was studied in detail, for example, by Eichhorn and Small (1964) and others experimentally [10][11][12][13] and by Tabata and Itakura (1998) [14], Birouk and Al-Sood(2007) [15] numerically. At present, how the drag, lift and pressure coefficients vary both locally as well as globally with respect to the sphere is well known [4,15,16].…”

Section: Introductionmentioning

confidence: 80%

Population Distribution in the Wake of a Sphere

et al. 2020

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The physics of heat and mass transfer from an object in its wake has significant importance in natural phenomena as well as across many engineering applications. Here, we report numerical results on the population density of the spatial distribution of fluid velocity, pressure, scalar concentration, and scalar fluxes of a wake flow past a sphere in the steady wake regime (Reynolds number 25 to 285). Our findings show that the spatial population distributions of the fluid and the transported scalar quantities in the wake follow a Cauchy-Lorentz or Lorentzian trend, indicating a variation in its sample number density inversely proportional to the squared of its magnitude. We observe this universal form of population distribution both in the symmetric wake regime and in the more complex three dimensional wake structure of the steady oblique regime with Reynolds number larger than 225. The population density distribution identifies the increase in dimensionless kinetic energy and scalar fluxes with the increase in Reynolds number, whereas the dimensionless scalar population density shows negligible variation with the Reynolds number. Descriptive statistics in the form of population density distribution of the spatial distribution of the fluid velocity and the transported scalar quantities is important for understanding the transport and local reaction processes in specific regions of the wake, which can be used e.g., for understanding the microphysics of cloud droplets and aerosol interactions, or in the technical flows where droplets interact physically or chemically with the environment.

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Section: Introductionmentioning

confidence: 80%

Population Distribution in the Wake of a Sphere

et al. 2020

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“…A central device for the good results obtained is a power law for the wind profile of the type

\bar{u} (z) = \frac{u_{*}}{m C_{0}} {true(\frac{z}{z_{0}} true)}^{m},

with

C_{0} = 14 / 11

m = 1 / 8

, for the mean wind speed at height z as a function of

u_{*}

and the roughness length z 0 for momentum. Such power laws were at the heart of the early theories by L. Prandtl on turbulent boundary layers [ Bodenschatz and Eckert , ]; they were later largely replaced by the log law, but their analytical tractability was one of the reasons that Prandtl let the opportunity of claiming the log law pass to von Kármán (see reference above); the same tractability—and not any deeper physical reason—is the main reason for its adoption in a number of papers by Brutsaert and his collaborators. It is of interest, however, to note that the issue is not settled in favor of the log law.…”

Section: The Seminal Years: Results From the Semi‐empirical Or K Thmentioning

confidence: 99%

Research on atmospheric turbulence by Wilfried Brutsaert and collaborators

Dias

2013

Water Resources Research

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[1] In this paper, several lines of investigation of atmospheric turbulence, by Wilfried Brutsaert, his students, and collaborators, are reviewed. Overall, we classify these lines as K-theory, surface roughness parameterization dealing with momentum and scalar fluxes, radiative effects on temperature fluctuations, stable conditions, scalar similarity, and atmospheric boundary-layer parameterization. Emphasis is placed on turbulence parameterization. Although these topics are presented more or less in chronological order, this order is broken whenever connections need to be established. Hopefully, these connections are the most interesting part of this review: it is there that Brutsaert's insights and long-range scientific questions may be found. His approach invariably included a careful formulation of the physical and mathematical basis of the problem at hand, and proceeded to focus on some essential issues that allowed analytical, numerical or statistical treatment. There is much to be learned from this approach; it is hoped that some of it can be glimpsed here.

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“…While the active grid was designed for use in the VDTT described in Sec. 2.1, the results presented in this paper were acquired with the grid mounted in an openreturn wind tunnel built in 1935 at the Kaiser-Wilhelm-Institut für Strömungsforschung in Göttingen run by L. Prandtl and H. Reichardt (Reichardt, 1938;Bodenschatz and Eckert, 2011). The original test section of this tunnel was replaced with the present test section, which has the same cross-sectional profile as the VDTT test section.…”

Section: Wind-tunnel Setup and Inflow Conditionsmentioning

confidence: 99%

Control of long-range correlations in turbulence

et al. 2019

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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.

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Prandtl and the Göttingen school

Cited by 30 publications

References 69 publications

Population Distribution in the Wake of a Sphere

Population Distribution in the Wake of a Sphere

Research on atmospheric turbulence by Wilfried Brutsaert and collaborators

Control of long-range correlations in turbulence

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