Turbulence spectrum: Difference between revisions
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<math> \Psi(k) = U_P \Psi(f) </math> . | <math> \Psi(k) = U_P \Psi(f) </math> . | ||
If a | If a sampled quantity, say <math>\zeta</math>, has a spectrum, <math>\Psi(k)</math>, then this spectrum provides the wavenumber distribution of the variance of <math>\zeta</math>. | ||
For example, | For example, | ||
<math>\overline{\zeta^2}=\int_0^{ | <math>\overline{\zeta^2}=\int_0^{k_N} \Psi(k)\, \mathrm{d}k </math> | ||
provides the total variance of <math>\zeta</math>, | provides the total variance of <math>\zeta</math>, where <math>k_N = \frac{1}{2} f_s / U_P</math> is the Nyquist wavenumber and <math>f_s</math> is the sampling rate <math>\zata</math>. | ||
The variance located in the wavenumber band of <math>k_1</math> to <math>k_2</math> is | |||
<math>\int_{k_1}^{k_2} \Psi(k)\, \mathrm{d}k </math> | <math>\int_{k_1}^{k_2} \Psi(k)\, \mathrm{d}k \ \ .</math> | ||
Revision as of 19:33, 1 December 2021
| Short definition of Turbulence spectrum |
|---|
| Turbulence energy cascade and its expected spectral representation |
This is the common definition for Turbulence spectrum, but other definitions may be discussed within the wiki.
Spectra in the frequency domain are converted into the spatial domain via Taylor's Frozen Turbulence hypothesis.
Convert time derivatives to spatial gradients along the direction of profiling using
.
Convert frequency spectra into wavenumber spectra using
and .
If a sampled quantity, say , has a spectrum, , then this spectrum provides the wavenumber distribution of the variance of . For example,
provides the total variance of , where is the Nyquist wavenumber and is the sampling rate Failed to parse (unknown function "\zata"): {\displaystyle \zata} . The variance located in the wavenumber band of to is
- Missing the y-axi variables
- Lowest frequency and wavenumber resolvable
