High-Reynolds number stratified turbulent wakes

Project1a_1Submerged stratified turbulent wakes are a canonical turbulent flow where one can examine the competition between stratification and shear in suppressing and enhancing turbulence, respectively. Moreover, stratified wakes are of interest to researchers in geophysical fluid dynamics and naval hydrodynamics. Our existing spectral multidomain penalty method (SMPM) flow solver has allowed us to conduct implicit large eddy simulations (LES) of the intermediate-to-late wake of a towed sphere at Reynolds number values O(10) larger than those of the laboratory. The unprecedented high resolution of the wake core, enabled by the SMPM, has revealed novel physics inside within it in the form of secondary Kelvin-Helmholtz instabilities and turbulence. These secondary events drive a significant prolongation of the commonly perceived life-cycle of the original turbulence with important implications for the parameterization of vertical transport and mixing by stratified turbulence.

Project1cWe have also analyzed the high-frequency internal gravity wave field radiated by stratified turbulent wakes. The wave-emission process by localized stratified turbulence becomes increasingly inviscid at high Reynolds numbers. As a result, the radiated wave-field extracts non-negligible momentum from the wake and the waves show an increasing likelihood for near-field breaking (leading to additional sources of dissipation and mixing).

Ongoing efforts are focused towards characterizing the (sub)surface manifestation of the wake-radiated wave-field, namely in terms of the induced surface strain field and mean flows. The associated results can be used by remote sensing researchers. Very recently, we have begun pursuing the formulation of universal scaling laws for high-Reynolds number stratified wakes. We will also soon explore the development of subgrid scale parameterizations informed by the state-of-the-art homogeneous stratified turbulence simulations of Prof. Steve de Bruyn Kops at the University of Massachussetts. The PhD student working on this project is Mr. Qi Zhou.