Anisotropic Turbulence Models for Wakes in an Active Ocean Environment


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Virginia Tech


A set of second-moment closure turbulence models are implemented for the study of wake evolution in an oceanic environment. The effects of density stratification are considered, and the models are validated against laboratory experiments mimicking the stratified ocean environment, and against previous experimental study of wakes subjected to a density stratification. The turbulence models are found to reproduce a number of important behaviors which differentiate stratified wakes from those in a homogeneous environment, including the appropriate decay rates in turbulence quantities, buoyant suppression of turbulence length scales, and canonical stages in wake evolution. The existence of background turbulence is considered both through the introduction of production terms to the turbulence model equations and the replication of scale-resolved simulations of wakes embedded in turbulence. It is found that the freestream turbulence causes accelerated wake growth and faster decay of wake momentum. Wakes are then simulated at a variety of Re and Fr representative of full-scale vehicles operating in an ocean environment, to downstream distances several orders of magnitude greater than existing RANS studies. The models are used to make some general predictions concerning the dependence of late-wake behavior on these parameters, and specific insights into expected behavior are gained. The wake turbulence is classified using "fossil turbulence" and stratification strength criteria from the literature. In keeping with experimentally observed behavior, the stratification is predicted to increase wake persistence. It is also predicted that, regardless of initial Re or F r, the wake turbulence quickly becomes a mixture of overturning eddies and internal waves. It is found that the high Re wakes eventually become strongly affected by the stratification, and enter the strongly-stratified or LAST regime. Additional model improvements are proposed based on the predicted late wake behavior.



Wakes, Stratified, Turbulence Modeling, Second-Moment, RANS