Generalised quasilinear approximations of turbulent channel flow: Part 1. Streamwise nonlinear energy transfer
Carlos G. Hern\'andez, Qiang Yang, Yongyun Hwang

TL;DR
This paper applies a generalized quasilinear approximation to turbulent channel flow to better understand energy transfer across scales, showing improved modeling of turbulence statistics compared to simpler models.
Contribution
It introduces a GQL model that captures streamwise nonlinear energy transfer with minimal additional complexity over QL models.
Findings
GQL significantly improves turbulence statistics prediction.
The scattering mechanism depends on the Lyapunov spectrum.
High threshold wavenumber can eliminate energy scattering.
Abstract
A generalised quasilinear (GQL) approximation (Marston \emph{et al.}, \emph{Phys. Rev. Lett.}, vol. 116, 104502, 2016) is applied to turbulent channel flow at ( is the friction Reynolds number), with emphasis on the energy transfer in the streamwise wavenumber space. The flow is decomposed into low and high streamwise wavenumber groups, the former of which is solved by considering the full nonlinear equations whereas the latter is obtained from the linearised equations around the former. The performance of the GQL approximation is subsequently compared with that of a QL model (Thomas \emph{et al.}, \emph{Phys. Fluids.}, vol. 26, no. 10, 105112, 2014), in which the low-wavenumber group only contains zero streamwise wavenumber. It is found that the QL model exhibits a considerably reduced multi-scale behaviour at the given moderately high Reynolds number.…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
