Dissipation rate estimates: Difference between revisions
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# High-pass filter the shear-probe and (optionally) the vibration data. | # High-pass filter the shear-probe and (optionally) the vibration data. | ||
# Identify each diss-length segment in the profile. | # Identify each diss-length segment in the profile. | ||
# De-spike the shear-probe data, and track the fraction of data affected by de-spiking within each diss-length segment. This will become a quality-control metric. | # [[De-spike the shear-probe data]], and track the fraction of data affected by de-spiking within each diss-length segment. This will become a quality-control metric. | ||
# Calculate the frequency spectra and cross-spectra of shear and vibrations for each diss-length segment | # Calculate the [[frequency spectra and cross-spectra of shear and vibrations]] for each diss-length segment. | ||
# Extract the original and the vibration-coherent clean shear-probe frequency spectra. | # Extract the original and the vibration-coherent clean shear-probe frequency spectra. | ||
# Correct shear and vibration frequency spectra for the high-pass filter. | # Correct shear and vibration frequency spectra for [[the high-pass filter]]. | ||
# Correct the cleaned frequency spectra for the bias induced by the Goodman algorithm. | # Correct the cleaned frequency spectra for the bias induced by the Goodman algorithm. | ||
# Convert the frequency spectra into wavenumber spectra using the mean speed for each diss-length segment. That is, make the wavenumber <math> \begin{equation}k=f/U\end{equation}</math> and the wavenumber [[Here|kinetic energy spectrum]] <math> \begin{equation}E(k)=UE(f)\end{equation}</math> . | # Convert the frequency spectra into wavenumber spectra using the mean speed for each diss-length segment. That is, make the wavenumber <math> \begin{equation}k=f/U\end{equation}</math> and the wavenumber [[Here|kinetic energy spectrum]] <math> \begin{equation}E(k)=UE(f)\end{equation}</math> . | ||
# Correct the spectra of shear for the wavenumber response of the shear probe. | # Correct the spectra of shear for the [[wavenumber response of the shear probe]]. | ||
# Apply an iterative spectral integration algorithm to estimate the variance of shear | # Apply an [[iterative spectral integration algorithm]] to estimate the variance of shear. | ||
# Calculate the rate | # Calculate the turbulent dissipation rate by multiplying the shear variance by <math> \begin{equation} \frac{15}{2}\nu\end{equation}</math> where <math> \nu </math> is the temperature-dependent kinematic viscosity. | ||
# Determine the [[figure of merit (FM)]] for each shear-probe spectrum using the method described here. | |||
# Calculate the expected variance of each dissipation estimate using the method described here. |
Revision as of 17:33, 20 August 2021
dissipation rate estimates
The following items break down the derivation of the turbulent dissipation rate of kinetic energy ([math]\displaystyle{ \varepsilon }[/math]). Explanations for each step can be found after.
- Extract the section defined in step 2 ("Section" selection).
- High-pass filter the shear-probe and (optionally) the vibration data.
- Identify each diss-length segment in the profile.
- De-spike the shear-probe data, and track the fraction of data affected by de-spiking within each diss-length segment. This will become a quality-control metric.
- Calculate the frequency spectra and cross-spectra of shear and vibrations for each diss-length segment.
- Extract the original and the vibration-coherent clean shear-probe frequency spectra.
- Correct shear and vibration frequency spectra for the high-pass filter.
- Correct the cleaned frequency spectra for the bias induced by the Goodman algorithm.
- Convert the frequency spectra into wavenumber spectra using the mean speed for each diss-length segment. That is, make the wavenumber [math]\displaystyle{ \begin{equation}k=f/U\end{equation} }[/math] and the wavenumber kinetic energy spectrum [math]\displaystyle{ \begin{equation}E(k)=UE(f)\end{equation} }[/math] .
- Correct the spectra of shear for the wavenumber response of the shear probe.
- Apply an iterative spectral integration algorithm to estimate the variance of shear.
- Calculate the turbulent dissipation rate by multiplying the shear variance by [math]\displaystyle{ \begin{equation} \frac{15}{2}\nu\end{equation} }[/math] where [math]\displaystyle{ \nu }[/math] is the temperature-dependent kinematic viscosity.
- Determine the figure of merit (FM) for each shear-probe spectrum using the method described here.
- Calculate the expected variance of each dissipation estimate using the method described here.