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Wake identification of stratified flows using dynamic mode decomposition

Chan-Ye Ohh and Geoffrey R. Spedding

  • Department of Aerospace and Mechanical Engineering, University of Southern California, Los Angeles, California 90089-1191, USA

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Phys. Rev. Fluids 7, 024801 – Published 22 February, 2022

DOI: https://doi.org/10.1103/PhysRevFluids.7.024801

Abstract

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. Here we use dynamic mode decomposition (DMD) to find modes that can be used to characterize and automate such a process. A custom-designed algorithm is proposed that can sort and classify stratified wakes based on a selection of the most energetic DMD modes. The approach is very, or partially successful, depending on the quality and dimension of the input data. The success of these first steps may be used to develop 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.

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Phys. Rev. Fluids 7, 024801– Published 22 February, 2022
  • Received 20 April 2021
  • Accepted 8 November 2021
Article part of CHORUS
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