The wake behind a bluff body in the presence of a density gradient is characterized by competing effects of buoyancy, momentum, and ultimately viscosity as the flow decays. Consequently, there are a number of distinct flow regimes into which the wakes can be placed, and there is some interest in whether any given wake can be traced back to its source through interrogation of selected fluid mechanical properties in the wake.
Chan-Ye Ohh and Geoff Spedding, University of California Los Angeles, USA, utilized dynamic mode decomposition (DMD) to find modes that can be used to characterize and automate such a process. The team created a custom-designed algorithm that can sort and classify stratified wakes based on a selection of the most energetic DMD modes. This method can potentially lead to the development of similar methods for more challenging and fully turbulent wakes, and also can serve as a guide for data-driven methods that require no prior knowledge of the flow structure. Their research was recently published in PRFluids.
Ohh and Spedding sit down with the Physical Review Journal Club April 13, 2022, providing a brief presentation of the results and answering all attendee questions in a session moderated by PRFluids Editorial Board Member Keith Julien, University of Colorado Boulder, USA. Registration is free and a video recording will be provided to all registrants.
