Data-driven active control of a thin elliptical cylinder undergoing transverse flow-induced vibrations

Jonathan C.C. Lo, Kerry Hourigan, Jisheng Zhao, Mark C. Thompson

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Abstract

This experimental study employs Bayesian optimisation to maximise the cross-flow (transverse) flow-induced vibration (FIV) of an elastically mounted thin elliptical cylinder by implementing axial (or angular) flapping motions. The flapping amplitude was in proportion to the vibration amplitude, with a relative phase angle imposed between the angular and transverse displacements of the cylinder. The control parameter space spanned over the ranges of proportional gain and phase difference of and, respectively, over a reduced velocity range of. The corresponding Reynolds number range was. Here, is the free stream velocity, is the major cross-sectional diameter of the cylinder, is the natural frequency of the system in quiescent fluid (water) and is the kinematic viscosity of the fluid. It was found that the controlled body rotation extended the wake-body synchronisation across the entire range tested, with a larger amplitude response than the non-rotating case for all flow speeds. Interestingly, two new wake-body synchronisation regimes were identified, which have not been reported in previous studies. As this geometry acts as a 'hard-oscillator' for, an adaptive gain (i.e. one that varies as a function of oscillation amplitude) was also implemented, allowing the body vibration, achieved for a non-rotating cylinder using increasing increments, to be excited from rest. The findings of the present study hold potential implications for the use of FIV as a means to efficiently extract energy from free-flowing water sources, a topic of increasing interest over the last decade.

Original languageEnglish
Article numberA35
Number of pages35
JournalJournal of Fluid Mechanics
Volume1001
DOIs
Publication statusPublished - 13 Dec 2024

Keywords

  • flow-structure interactions
  • machine learning
  • vortex streets

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