Turbulent kinetic energy spectrum in very anisothermal flows

2012 ◽  
Vol 376 (45) ◽  
pp. 3177-3184 ◽  
Author(s):  
Sylvain Serra ◽  
Adrien Toutant ◽  
Françoise Bataille ◽  
Ye Zhou
Keyword(s):  
Energy Spectrum ◽  
Kinetic Energy ◽  
Turbulent Kinetic Energy ◽  
Kinetic Energy Spectrum

On the Spectra of Turbulent Velocity Field in a Stably Stratified Flow

1991 ◽  
Vol 46 (5) ◽  
pp. 462-468
Author(s):  
A. K. Chakraborty ◽  
B. E. Vembe ◽  
H. P. Mazumdar
Keyword(s):  
Heat Flux ◽  
Energy Spectrum ◽  
Kinetic Energy ◽  
Turbulent Kinetic Energy ◽  
Eddy Viscosity ◽  
Three Dimensional ◽  
Inertial Subrange ◽  
Coefficient Function ◽  
One Dimensional ◽  
Kinetic Energy Spectrum

Abstract This paper describes a method to solve the spectral equation for the balance of turbulent kinetic energy in a stably stratified turbulent shear flow. The cospectra of vertical momentum and heat flux arc modelled with the aid of a basic eddy-viscosity (or turbulent exchange coefficient) function. For the term representing the inertial transfer of turbulent kinetic energy, Pao's [Phys. Fluids 8 (1965)] form is assumed. Analytical expressions for the three-dimensional kinetic energy spectrum as well as the cospectra of momentum and heat flux are obtained over the range of wave numbers k≥kb, which includes the inertial subrange kb≪k≪ks and the viscous subrange k>ks (kb and ks are the buoyancy and Kolmogorov wavenumbers, respectively). The two one-dimensional spectra, e.g., the kinetic energy spectra of the horizontal and vertical components of turbulence are derived from the three-dimensional kinetic energy spectrum. These one-dimensional spectra are compared with the measured data of Gargett et al. [J. Fluid Mech. 144 (1984)] for the case I ( = ks/kb) = 630. Finally, we compute the basic eddy-viscosity function and discuss its behavio

Aerodynamic Drag Reduction Design of Concept Sports Car

2012 ◽  
Vol 184-185 ◽  
pp. 24-27
Author(s):  
Ying Chao Zhang ◽  
Fang Zhao ◽  
Shu Xin Shao ◽  
Guang Yin Jin
Keyword(s):  
Energy Spectrum ◽  
Kinetic Energy ◽  
Drag Reduction ◽  
Drag Coefficient ◽  
Turbulent Kinetic Energy ◽  
Aerodynamic Drag ◽  
Kinetic Energy Spectrum ◽  
Before And After ◽  
Aerodynamic Drag Reduction

Simulations analysis of the aerodynamic for a sports car modeling before and after optimization was introduced in the paper by using commercial CFD code--STAR-CCM+. In the first simulation, we got the drag coefficient, the pressure of convective and the turbulent kinetic energy spectrum，then we found the positions that may affect the drag coefficient. Further analysis inferred that our modifications accorded with the aerodynamic principles. These results can provide the basis for the modeling design and further optimization.

scholarly journals Calculating Energy Spectra from Drifters

2016 ◽  
Author(s):  
Joseph H. LaCasce
Keyword(s):  
Energy Spectrum ◽  
Kinetic Energy ◽  
Structure Function ◽  
Two Dimensions ◽  
Longitudinal Structure ◽  
Kinetic Energy Spectrum ◽  
Longitudinal Structure Function ◽  
Large Pair ◽  
Non Local ◽  
Lagrangian Data

The relations between the kinetic energy spectrum and the second order longitudinal structure function in two dimensions are derived, and several examples are considered. The forward conversion (from spectrum to structure function) is illustrated first with idealized power law spectra, representing turbulent inertial ranges. The forward conversion is also applied to the zonal kinetic energy spectrum of Nastrom and Gage (1985) and the result agrees well with the longitudinal structure function of Lindborg (1999). The inverse conversion (from structure function to spectrum) is tested with data from 2D turbulence simulations. When applied to the theoretical structure function (derived from the forward conversion of the spectrum), the result closely resembles the original spectrum, except at the largest wavenumbers. However the inverse conversion is much less successful when applied to the structure function obtained from pairs of particles in the flow. This is because the inverse conversion favors large pair separations, which are typically noisy with particle data. Fitting the structure function to a polynomial improves the result, but not sufficiently to distinguish the correct inertial range dependencies. Furthermore the inversion of non-local spectra is largely unsuccessful. Thus it appears that focusing on structure functions with Lagrangian data is preferable to estimating spectra.

Kinetic energy spectrum of large-and mesoscale atmospheric processes

Nature ◽  
1984 ◽  
Vol 310 (5972) ◽  
pp. 36-38 ◽  
Author(s):  
G. D. Nastrom ◽  
K. S. Gage ◽  
W. H. Jasperson
Keyword(s):  
Energy Spectrum ◽  
Kinetic Energy ◽  
Atmospheric Processes ◽  
Kinetic Energy Spectrum
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