2 results
A data-driven quasi-linear approximation for turbulent channel flow
- Jacob J. Holford, Myoungkyu Lee, Yongyun Hwang
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- Journal:
- Journal of Fluid Mechanics / Volume 980 / 10 February 2024
- Published online by Cambridge University Press:
- 31 January 2024, A12
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A data-driven implementation of a quasi-linear approximation is presented, extending a minimal quasi-linear approximation (MQLA) (Hwang & Ekchardt, J. Fluid Mech., vol. 894, 2020, p. A23) to incorporate non-zero streamwise Fourier modes. A data-based approach is proposed, matching the two-dimensional wavenumber spectra for a fixed spanwise wavenumber between a direct numerical simulation (DNS) (Lee & Moser, J. Fluid Mech., vol. 774, 2015, pp. 395–415) and that generated by the eddy viscosity enhanced linearised Navier–Stokes equations at $Re_\tau \approx 5200$, where $Re_\tau$ is the friction Reynolds number. Leveraging the self-similar nature of the energy-containing part in the DNS velocity spectra, a universal self-similar streamwise wavenumber weight is determined for the linearised fluctuation equations at $Re_\tau \simeq ~5200$. The data-driven quasi-linear approximation (DQLA) provides noteworthy enhancements in the wall-normal and spanwise turbulence intensity profiles. It exhibits a qualitatively similar structure in the spanwise wavenumber velocity spectra compared with the MQLA. Additionally, the DQLA offers extra statistical outputs in the streamwise wavenumber coordinates, enabling a comprehensive global analysis of this modelling approach. By comparing the DQLA results with DNS results, the limitations of the presented framework are discussed, mainly pertaining to the lack of the streak instability (or transient growth) mechanism and energy cascade from the linearised model. The DQLA is subsequently employed over a range of Reynolds numbers up to $Re_\tau = 10^5$. Overall, the turbulence statistics and spectra produced by the DQLA scale consistently with the available DNS and experimental data, with the Townsend–Perry constants displaying a mild Reynolds dependence (Hwang, Hutchins & Marusic, J. Fluid Mech., vol. 933, 2022, p. A8). The scaling behaviour of the turbulence intensity profiles deviates away from the classic $\ln (Re_\tau )$ scaling, following the inverse centreline velocity scaling for the higher Reynolds numbers.
Optimal white-noise stochastic forcing for linear models of turbulent channel flow
- Jacob J. Holford, Myoungkyu Lee, Yongyun Hwang
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- Journal:
- Journal of Fluid Mechanics / Volume 961 / 25 April 2023
- Published online by Cambridge University Press:
- 24 April 2023, A32
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In the present study an optimisation problem is formulated to determine the forcing of an eddy-viscosity-based linearised Navier–Stokes model in channel flow at $Re_\tau \approx 5200$ ($Re_\tau$ is the friction Reynolds number), where the forcing is white-in-time and spatially decorrelated. The objective functional is prescribed such that the forcing drives a response to best match a set of velocity spectra from direct numerical simulation (DNS), as well as remaining sufficiently smooth. Strong quantitative agreement is obtained between the velocity spectra from the linear model with optimal forcing and from DNS, but only qualitative agreement between the Reynolds shear stress co-spectra from the model and DNS. The forcing spectra exhibit a level of self-similarity, associated with the primary peak in the velocity spectra, but they also reveal a non-negligible amount of energy spent in phenomenologically mimicking the non-self-similar part of the velocity spectra associated with energy cascade. By exploiting linearity, the effect of the individual forcing components is assessed and the contributions from the Orr mechanism and the lift-up effect are also identified. Finally, the effect of the strength of the eddy viscosity on the optimisation performance is investigated. The inclusion of the eddy viscosity diffusion operator is shown to be essential in modelling of the near-wall features, while still allowing the forcing of the self-similar primary peak. In particular, reducing the strength of the eddy viscosity results in a considerable increase in the near-wall forcing of wall-parallel components.