TURBULENCE ENERGY SPECTRA IN BAFFLED MIXING VESSELS

The maximum entropy principle states that the energy distribution will tend toward a state of maximum entropy under the physical constraints, such as the zero energy at the boundaries and a fixed total energy content. For the turbulence energy spectra, a distribution function that maximizes entropy with these physical constraints is a lognormal function due to its asymmetrical descent to zero energy at the boundary lengths scales. This distribution function agrees quite well with the experimental data over a wide range of energy and length scales. For turbulent flows, this approach is effective since the energy and length scales are determined primarily by the Reynolds number. The total turbulence kinetic energy will set the height of the distribution, while the ratio of length scales will determine the width. This makes it possible to reconstruct the power spectra using the Reynolds number as a parameter.

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Reynolds stress and turbulence energy spectra analysis of <italic>Re</italic>-understanding the turbulence constitutive equation DNS data in square and rectangular annular ducts

SCIENTIA SINICA Physica, Mechanica & Astronomica ◽

10.1360/sspma2016-00389 ◽

2017 ◽

Vol 47 (8) ◽

pp. 084701 ◽

Cited By ~ 1

Author(s):

HongYi XU

Keyword(s):

Constitutive Equation ◽

Reynolds Stress ◽

Energy Spectra ◽

Turbulence Energy ◽

Spectra Analysis

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Scaling of the maximum-entropy turbulence energy spectra

European Journal of Mechanics - B/Fluids ◽

10.1016/j.euromechflu.2021.01.011 ◽

2021 ◽

Vol 87 ◽

pp. 128-134

Author(s):

T.-W. Lee

Keyword(s):

Maximum Entropy ◽

Energy Spectra ◽

Turbulence Energy

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Effects of small streamline curvature on turbulent duct flow

Journal of Fluid Mechanics ◽

10.1017/s0022112079000380 ◽

1979 ◽

Vol 91 (4) ◽

pp. 633-659 ◽

Cited By ~ 63

Author(s):

I. A. Hunt ◽

P. N. Joubert

Keyword(s):

Turbulence Intensity ◽

Central Region ◽

Flow Region ◽

Energy Spectra ◽

Turbulent Shear ◽

Turbulence Energy ◽

Wall Region ◽

Mean Flow ◽

Streamline Curvature ◽

Central Flow

Mean velocity profiles, turbulence intensity distributions and streamwise energy spectra are presented for turbulent air flow in a smooth-walled, high aspect ratio rectangular duct with small streamwise curvature, and are compared with measurements taken in a similar straight duct.The results for the present curved flow are found to differ significantly from those for the more highly curved flows reported previously, and suggest the need to distinguish between ‘shear-dominated’ flows with small curvature and ‘inertia-dominated’ flows with high curvature. Velocity defect and angular-momentum defect hypotheses fail to correlate the central-region mean flow data, but the wall-region data are consistent with the conventional straight-wall similarity hypothesis. A secondary flow of Taylor–Goertler vortex pattern is found to occur in the central flow region.An examination of the flow equations yields a model for the mechanisms by which streamline curvature affects turbulent flow, in which a major effect is a direct change in the turbulent shear stress through a conservative reorientation of the turbulence intensity components. Data for the streamwise and transverse turbulence intensities show behaviour consistent with that expected from the equations, and the distribution of total turbulence energy in the central flow region is found to be nearly invariant with Reynolds number and wall curvature, in agreement with the model.Energy spectra for the streamwise component are examined in terms of a Townsend-type two-component turbulence model. They indicate that a universal, ‘active’ component exists in all flow regions, with an ‘inactive’ component which affects only the low wavenumber spectra intensities. This is taken to imply that the effects of streamline curvature are determined by the central-region flow structure alone.

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Selection of a leading edge noise prediction method for PNoise

The Academic Society Journal ◽

10.32640/tasj.2018.4.214 ◽

2018 ◽

pp. 214-223

Author(s):

AM Faria ◽

MM Pimenta ◽

JY Saab Jr. ◽

S Rodriguez

Keyword(s):

Wind Turbine ◽

Turbine Blades ◽

Prediction Method ◽

Leading Edge ◽

Wind Farms ◽

Broadband Noise ◽

Turbulence Energy ◽

Noise Prediction ◽

Migration Routes ◽

Turbulent Inflow

Wind energy expansion is worldwide followed by various limitations, i.e. land availability, the NIMBY (not in my backyard) attitude, interference on birds migration routes and so on. This undeniable expansion is pushing wind farms near populated areas throughout the years, where noise regulation is more stringent. That demands solutions for the wind turbine (WT) industry, in order to produce quieter WT units. Focusing in the subject of airfoil noise prediction, it can help the assessment and design of quieter wind turbine blades. Considering the airfoil noise as a composition of many sound sources, and in light of the fact that the main noise production mechanisms are the airfoil self-noise and the turbulent inflow (TI) noise, this work is concentrated on the latter. TI noise is classified as an interaction noise, produced by the turbulent inflow, incident on the airfoil leading edge (LE). Theoretical and semi-empirical methods for the TI noise prediction are already available, based on Amiet’s broadband noise theory. Analysis of many TI noise prediction methods is provided by this work in the literature review, as well as the turbulence energy spectrum modeling. This is then followed by comparison of the most reliable TI noise methodologies, qualitatively and quantitatively, with the error estimation, compared to the Ffowcs Williams-Hawkings solution for computational aeroacoustics. Basis for integration of airfoil inflow noise prediction into a wind turbine noise prediction code is the final goal of this work.

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