Tutorial School on Fluid Dynamics: Aspects of Turbulence ...
Transcript of Tutorial School on Fluid Dynamics: Aspects of Turbulence ...
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Tutorial School on Fluid Dynamics: Aspects of Turbulence
Session I: Refresher Material
Instructor: James Wallace
Johns Hopkins UniversityCenter for Scientific Computation and Applied Mathematical Modeling
Institute for Physical Science and Technology
National Science Foundation
Adapted from Publisher: John S. Wiley & Sons2002
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Describe how properties of a fluid element change, as given by the
substantial derivative, D( )/Dt, as the element is transported through
the flow field.
mean and fluctuating velocity
components are divergence free
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Decomposing into mean and fluctuating parts, invoking continuity
and averaging using Reynolds rules yields
Reynolds stress tensor
This equation and together are called the Reynolds Averaged
Navier-Stokes Equations (RANS). This equation describes the transport of the
Mean momentum in the xi direction
There are more unknowns than the four available equations. To “close” the
set of equations the Reynolds stress term must be related to the
velocity gradient in some way through a model equation.
(N-S)
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Reynolds Shear stress or velocity fluctuation covariance
For i = j, and summing over i, half this covariance becomes the turbulent kinetic
energy (TKE) when multiplied by the density
The square roots of these variance are the root-mean-square values of the
velocity fluctuation components. They are a measure of the amplitudes of
the fluctuations.
T
The components of the TKE are related to the variances of the velocity fluctuations
K
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By decomposing the N-S equation for momentum and subtracting the
RANS equation from it, a transport equation for the momentum of the
fluctuations is obtained
Multiply the transport equation for the fluctuating momentum, term by term, by
The fluctuating velocity components, uj.
Exchange the subscripts, i and j
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Add these last two equations together, average the result and simplify using
Reynolds rules to obtain the transport equation for the Reynolds stress tensor.
Let i = j in the turbulent transport equation and divide each term by 2 ρ to
obtain the transport equation for turbulent kinetic energy (per unit mass).
Here K is uiui/2.
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(turbulent transport)
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Averaged Vorticity Transport Equation
The Instantaneous Vorticity Transport Equation is obtained
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Multiply the instantaneous vorticity transport equation term by term
with Ω /2, average and separate the last term into its diffusive and
dissipative parts to obtain an averaged transport equation for
enstrophy,
This is different from and simpler than the transport equation for mean enstrophy
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Transport equation of mean enstrophy
Transport equation of fluctuating enstrophy
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Diffusion rate in units of scalar/area/sec,
Transport equation for a passive scalar
where is the diffusivity coefficient
Applying Reynolds decomposition and averaging
scalar flux
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CORRELATION
Two-point correlation
dividing this by the variances of ui and uj gives the correlation coefficient,
Rij, which has a limiting maximum value of +1 when I = j and x and y are
coincident. It can also take on negative values with a limiting value of -1
when ui and uj are the same signals but are 180o out of phase.
Space-time correlations are formed when we let x and y be at different
locations and let the time be different for the two variables being
correlated.
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Energy Spectrum Tensor
Define the separation distance between locations as r and take the
Fourier transform of the two-point correlation tensor
For a fixed location x
Here k is the wavenumber vector. Of course, the inverse Fourier transform
is the two-point correlation tensor.
where dk = dk1dk2dk3.is the differential volume in wavenumber space.
Letting i = j, r = 0 and dividing by 2, yields the spectrum of TKE
SPECTRA
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In spherical coordinates this can be written as
The term in brackets is defined as the energy density function or, in short,
the energy spectrum.
so that
E(k,t) represents all the energy in a spherical shell in k-space located at
k = │k│ .
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Time Auto-correlation Function (of a single signal at one location in
space correlated with itself as a function of time delay)
Integral time scale
TE =
The Fourier transform of is
where ω’ = 2π ω is the angular frequency (radians) and ω is the
frequency (rev/s).
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The inverse transform is, of course, the time auto-correlation function itself
Evaluating at τ = 0 and defining
after a change of variable we have
If is symmetric
E11 is called the frequency spectrum. It can easily be determined
From time series of experimental data.
For isotropic turbulence R11(r,t) can be related to by means of
“Taylor’s Hypothesis, and E(k,t) can be calculated from E11 (ω).
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to determine streamwise gradients
Streamwise wavenumber approximated from frequency
Alternatively, setting the acceleration equal to zero in the N-S equations
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k1 = 2πω/UC
ω = k1UC/2π
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Smallest scales of turbulence are in a state of universal equilibrium,
according to Kolmogorov, that should depend only on the rate of
dissipation, ε, and the viscosity,
Kolomogorov length scale
Kolmogorov time scale
Kolmogorov velocity scale
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Isotropic dissipation rate,
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Le
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Two spatial correlations that play a special role in isotropic turbulence
theory and are found from Rij (r, t) are longitudinal and transverse
correlation functions
where ei is the unit vector in the coordinate direction.
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Micro length-scale
Defined from Taylor series of f(r) near r = 0. It is a measure of the scales
at which turbulent dissipation occurs.
So for f = 0, r = λ
~0
The microscale, λ, is the intercept of this parabola with the r-axis. It is obviously related to the curvature of f at r = 0.
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Ratios of Scales
Choosing a different Reynolds number,
based on the physical size of the flow domain and from the definition of
For isotropic turbulence
Le
Le
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Range of scales over which there is no significant kinetic energy production or
dissipation and where the energy spectrum depends only on the dissipation
rate, ε, and not on the viscosity. This is the idea of the “energy cascade.”
Dimensionally this requires that the spectrum have the form
The one-dimensional spectrum also has a dependency.
and
C = 55/18 C1 ~ 3
C1 ≈ 0.49 C'1 ≈ 0.65
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Local isotropy
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PROBABILITY DENSITY FUNCTIONS & CENTRAL MOMENTS
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Mean value of S
nth moment of S
nth moment of
Fluctuation s
Skewness factor
with σ the standard deviation (rms) of s
Flatness factor
(Kurtosis)
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JPDF
Joint Moment
Statistical independence when
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Detection Method for Phase Averaging
Spectral bump in v
spectrum at upper edge of
mixing layer
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Phase averaged velocity vectors
in a moving frame of reference
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Phase Averaged Dissipation Rate & Vorticity Covariance