Efficient sensing of von Karman vortices using compressive sensing

Bayındır C. , Namli B.

COMPUTERS & FLUIDS, vol.226, 2021 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 226
  • Publication Date: 2021
  • Doi Number: 10.1016/j.compfluid.2021.104975
  • Title of Journal : COMPUTERS & FLUIDS
  • Keywords: Von Karman vortices, Compressive sensing, Time series of drag and lift, Sparse signal, CIRCULAR-CYLINDER, SIGNAL RECOVERY, TRAVELING-WAVE, VORTEX STREET, NUMBER, WIND, FLOW


In this paper, we discuss the usage and implementation of the compressive sensing (CS) for the efficient measurement and analysis of the von Karman vortices. We consider two different flow fields, the flow fields around a circle and an ellipse. We solve the governing k - c transport equations numerically in order to model the flow fields around these bodies. Using the time series of the drag, C-D, and the lift, C-L, coefficients, and their Fourier spectra, we show that compressive sampling can be effectively used to measure and analyze Von Karman vortices. We discuss the effects of the number of samples on reconstruction and the benefits of using compressive sampling over the classical Shannon sampling in the flow measurement and analysis where Von Karman vortices are present. We comment on our findings and indicate their possible usage areas and extensions. Our results can find many important applications including but are not limited to measure, control, and analyze vibrations around coastal and offshore structures, bridges, aerodynamics, and Bose-Einstein condensation, just to name a few. (C) 2021 Elsevier Ltd. All rights reserved.