A dataset of nonlinear optimals in turbulent channel flow
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| Format: | Dataset Open Access |
| Langue: | en |
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PANGAEA
2025
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| _version_ | 1867169168848060416 |
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| author | Klingenberg, Dario |
| author_facet | Klingenberg, Dario |
| collection | Datos científicos de ciencias marinas y ambientales |
| contents | We investigate the energy transfer from the mean profile to velocity fluctuations in channel flow by calculating nonlinear optimal disturbances, i.e. the initial condition of a given finite energy that achieves the highest possible energy growth during a given fixed time horizon. It is found that for a large range of time horizons and initial disturbance energies, the nonlinear optimal exhibits streak spacing and amplitude consistent with DNS at least at Re_tau = 180, which suggests that they isolate the relevant physical mechanisms that sustain turbulence. Moreover, the time horizon necessary for a nonlinear disturbance to outperform a linear optimal is consistent with previous DNS-based estimates using eddy turnover time, which offers a new perspective on how some turbulent time scales are determined. In this dataset, the initial conditions and temporal evolutions of all calculated optimals are compiled, along with post-processing scripts. |
| format | Dataset Open Access |
| id | pangaea_https___doi_org_10_1594_PANGAEA_983358 |
| institution | PANGAEA |
| language | en |
| publishDate | 2025 |
| publisher | PANGAEA |
| record_format | pangaea |
| spellingShingle | A dataset of nonlinear optimals in turbulent channel flow Klingenberg, Dario Binary Object; Binary Object (File Size); Figure; File name; nonlinear optimisation; Numerical simulated; Title; turbulent channel flow; Variable We investigate the energy transfer from the mean profile to velocity fluctuations in channel flow by calculating nonlinear optimal disturbances, i.e. the initial condition of a given finite energy that achieves the highest possible energy growth during a given fixed time horizon. It is found that for a large range of time horizons and initial disturbance energies, the nonlinear optimal exhibits streak spacing and amplitude consistent with DNS at least at Re_tau = 180, which suggests that they isolate the relevant physical mechanisms that sustain turbulence. Moreover, the time horizon necessary for a nonlinear disturbance to outperform a linear optimal is consistent with previous DNS-based estimates using eddy turnover time, which offers a new perspective on how some turbulent time scales are determined. In this dataset, the initial conditions and temporal evolutions of all calculated optimals are compiled, along with post-processing scripts. |
| title | A dataset of nonlinear optimals in turbulent channel flow |
| topic | Binary Object; Binary Object (File Size); Figure; File name; nonlinear optimisation; Numerical simulated; Title; turbulent channel flow; Variable |
| url | https://doi.org/10.1594/PANGAEA.983358 |