Turbulent energy flux and eddy diffusivity

1971 ◽  
Vol 1 (4) ◽  
pp. 385-388
Author(s):  
Helmut Kraus
Keyword(s):  
Energy Flux ◽  
Eddy Diffusivity ◽  
Turbulent Energy

Algebraic turbulent energy flux models for hypersonic shear flows

2010 ◽  
Vol 46 (2-3) ◽  
pp. 49-61 ◽  
Author(s):  
Rodney D.W. Bowersox ◽  
Simon W. North
Keyword(s):  
Energy Flux ◽  
Shear Flows ◽  
Turbulent Energy

The two-dimensional mixing region

1970 ◽  
Vol 41 (2) ◽  
pp. 327-361 ◽  
Author(s):  
I. Wygnanski ◽  
H. E. Fiedler
Keyword(s):  
Velocity Profile ◽  
Eddy Viscosity ◽  
Mixing Layer ◽  
Outer Part ◽  
Eddy Diffusivity ◽  
Turbulent Energy ◽  
Two Dimensional ◽  
Low Velocity ◽  
Mean Velocity ◽  
Axial Velocity Profile

The two-dimensional incompressible mixing layer was investigated by using constant-temperature, linearized hot wire anemometers. The measurements were divided into three categories: (1) the conventional average measurements; (2) time-average measurements in the turbulent and the non-turbulent zones; (3) ensemble average measurements conditioned to a specific location of the interface. The turbulent energy balance was constructed twice, once using the conventional results and again using the turbulent zone results. Some differences emerged between the two sets of results. It appears that the mixing region can be divided into two regions, one on the high velocity side which resembles the outer part of a wake and the other on the low velocity side which resembles a jet. The binding turbulent–non-turbulent interfaces seem to move independently of each other. There is a strong connexion between the instantaneous location of the interface and the axial velocity profile. Indeed the well known exponential mean velocity profile never actually exists at any given instant. In spite of the complexity of the flow the simple concepts of eddy viscosity and eddy diffusivity appear to be valid within the turbulent zone.

A Turbulent Energy Dissipation Model for Flows With Drag Reduction

1978 ◽  
Vol 100 (1) ◽  
pp. 107-112 ◽  
Author(s):  
Samuel Hassid ◽  
Michael Poreh
Keyword(s):  
Energy Dissipation ◽  
Drag Reduction ◽  
Eddy Diffusivity ◽  
Turbulent Energy ◽  
Momentum Equation ◽  
Mean Velocity ◽  
Turbulent Length Scale ◽  
Dissipation Model ◽  
The Mean ◽  
Good Agreement

A turbulent-energy-dissipation model is proposed for flows with and without drag reduction. The model is based on an eddy diffusivity approximation in the momentum equation, and on transport equations for the turbulent energy and the turbulent energy dissipation. The model describes the mean velocity profile and the turbulent energy distribution as a function of the reduction in the friction coefficient. It also yields a turbulent length scale which is shown to grow with drag reduction. The predictions of the model are in good agreement with the available experimental data.

scholarly journals TURBULENT MIXING PROCESSES IN LABANI CHANNEL, THE MAKASSAR STRAIT

2016 ◽  
Vol 8 (1) ◽  
Author(s):  
Yuli Naulita
Keyword(s):  
Turbulent Mixing ◽  
Eddy Diffusivity ◽  
Turbulent Energy ◽  
Wavelet Denoising ◽  
Mixing Processes ◽  
Ozmidov Scale ◽  
Thorpe Scale ◽  
Order Of Magnitude ◽  
O 10 ◽  
Temperature Depth

<p><em>Study on turbulent mixing processes in Labani Channel, the Makassar Strait, was conducted by using the INSTANT (International Nusantara Stratification And Transport) program dataset, in Juli 2005. The turbulent mixing process was evaluated using Thorpe method, where the overturning eddies were revealed by density inversions in CTD (Conductivity Temperature Depth) profiles. All individual identified-overturn regions was validated by the GK’s test (Galbraith and Kelly test) where at first noise on CTD signals had been removed  by applying wavelet denoising.   A large number of overturn regions with Thorpe scale (L<sub>T</sub>) less than 0.5 m were detected in the thermocline layer of Makassar Strait. Based on linear relationship between Thorpe and Ozmidov scale, order of magnitude of the turbulent energy kinetic dissipation rate in Labani Channel was estimated about </em><em>10<sup>-11</sup>- 10<sup>-5</sup>Wkg<sup>-1</sup> and </em><em>density eddy diffusivity K<sub>ρ</sub></em><em>(10<sup>-6  </sup>– 10<sup>-2</sup>) m<sup>2</sup>/s . The strong of turbulen mixing was found at the layer of  NPSW at 150 m depth and NPIW at 300 m depth, indicated by high values of K<sub>ρ </sub> (O = 10<sup>-3</sup> – 10<sup>-2</sup> m<sup>2</sup>s<sup>-1</sup>).  It reveals that turbulent mixing has an important role on determining ITF water mass character.  </em></p><p><strong><em>Keywoods</em></strong><em>: turbulent mixing, wavelet denoising, overturn region, Thorpe method, Labani Channel, Makassar Srait.</em></p>

Turbulent energy flux generated by shock/homogeneous-turbulence interaction

2016 ◽  
Vol 796 ◽  
pp. 113-157 ◽  
Author(s):  
Russell Quadros ◽  
Krishnendu Sinha ◽  
Johan Larsson
Keyword(s):  
Shock Wave ◽  
Turbulent Flows ◽  
Energy Flux ◽  
High Speed ◽  
Isotropic Turbulence ◽  
Interaction Analysis ◽  
Turbulent Energy ◽  
Angle Of Incidence ◽  
Two Dimensional ◽  
Linear Interaction

High-speed turbulent flows with shock waves are characterized by high localized surface heat transfer rates. Computational predictions are often inaccurate due to the limitations in modelling of the unclosed turbulent energy flux in the highly non-equilibrium regions of shock interaction. In this paper, we investigate the turbulent energy flux generated when homogeneous isotropic turbulence passes through a nominally normal shock wave. We use linear interaction analysis where the incoming turbulence is idealized as being composed of a collection of two-dimensional planar vorticity waves, and the shock wave is taken to be a discontinuity. The nature of the postshock turbulent energy flux is predicted to be strongly dependent on the angle of incidence of the incoming waves. The energy flux correlation is also decomposed into its vortical, entropy and acoustic contributions to understand its rapid non-monotonic variation behind the shock. Three-dimensional statistics, calculated by integrating two-dimensional results over a prescribed upstream energy spectrum, are compared with available data from direct numerical simulations. A detailed budget of the governing equation is also considered in order to gain insight into the underlying physics.

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