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>\zeta</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>\int_{k_1}^{k_2} \Psi(k)\, \mathrm{d}k \ \ .</math> | ||
Thus, a spectrum has units of variance per wavenumber. | |||
Latest revision as of 19:35, 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 maybe discussed within the wiki.
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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 . The variance located in the wavenumber band of to is
Thus, a spectrum has units of variance per wavenumber.
- Missing the y-axi variables
- Lowest frequency and wavenumber resolvable
