File:Segment anisotropy.png - Revision history

CynthiaBluteau: /* Summary */

2022-07-05T17:27:21Z

Summary

← Older revision		Revision as of 17:27, 5 July 2022
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	== Summary ==		== Summary ==
	Example spectra for the Tidal shelf high-quality dataset. About 3h worth is shown, and each spectrum was constructed from 128 s (2.13min) worth of data, which was split into FFT-length of 32 s (2048 samples). The speeds past the sensor vary from a minimum of 0.3 m/s and a maximum of 0.8 m/s. The combination of high <math>\varepsilon</math> and fast speeds enables using short segments to compute the spectra. The impact of [[#anisotropy\|turbulence anisotropy]] is also visible with the flattening of the spectra at wavenumbers around 1 cpm.		Example spectra for the Tidal shelf high-quality dataset. About 3h worth is shown, and each spectrum was constructed from 128 s (2.13min) worth of data, which was split into FFT-length of 32 s (2048 samples). The speeds past the sensor vary from a minimum of 0.3 m/s and a maximum of 0.8 m/s. The combination of high <math>\varepsilon</math> and fast speeds enables using short segments to compute the spectra. The impact of [[Velocity inertial subrange model#anisotropy\|turbulence anisotropy]] is also visible with the flattening of the spectra at wavenumbers around 1 cpm.

CynthiaBluteau: /* Summary */

2022-07-05T17:26:25Z

Summary

← Older revision		Revision as of 17:26, 5 July 2022
Line 1:		Line 1:
	== Summary ==		== Summary ==
	Example spectra for the Tidal shelf high-quality dataset. About 3h worth is shown, and each spectrum was constructed from 128 s (2.13min) worth of data, which was split into FFT-length of 32 s (2048 samples). The speeds past the sensor vary from a minimum of 0.3 m/s and a maximum of 0.8 m/s. The combination of high <math>\varepsilon<\math> and fast speeds enables using short segments to compute the spectra.		Example spectra for the Tidal shelf high-quality dataset. About 3h worth is shown, and each spectrum was constructed from 128 s (2.13min) worth of data, which was split into FFT-length of 32 s (2048 samples). The speeds past the sensor vary from a minimum of 0.3 m/s and a maximum of 0.8 m/s. The combination of high <math>\varepsilon</math> and fast speeds enables using short segments to compute the spectra. The impact of [[#anisotropy\|turbulence anisotropy]] is also visible with the flattening of the spectra at wavenumbers around 1 cpm.

CynthiaBluteau: Example spectra for the Tidal shelf high-quality dataset. About 3h worth is shown, and each spectrum was constructed from 128 s (2.13min) worth of data, which was split into FFT-length of 32 s (2048 samples). The speeds past the sensor vary from a minimum of 0.3 m/s and a maximum of 0.8 m/s. The combination of high $\varepsilon<\math> and fast speeds enables using short segments to compute the spectra.$

2022-07-05T16:35:39Z

Example spectra for the Tidal shelf high-quality dataset. About 3h worth is shown, and each spectrum was constructed from 128 s (2.13min) worth of data, which was split into FFT-length of 32 s (2048 samples). The speeds past the sensor vary from a minimum of 0.3 m/s and a maximum of 0.8 m/s. The combination of high <math>\varepsilon<\math> and fast speeds enables using short segments to compute the spectra.

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== Summary ==
Example spectra for the Tidal shelf high-quality dataset. About 3h worth is shown, and each spectrum was constructed from 128 s (2.13min) worth of data, which was split into FFT-length of 32 s (2048 samples). The speeds past the sensor vary from a minimum of 0.3 m/s and a maximum of 0.8 m/s. The combination of high <math>\varepsilon<\math> and fast speeds enables using short segments to compute the spectra.