Optimizing the control of transition to turbulence using a Bayesian method

Anton Pershin (Lead / Corresponding author), Cédric Beaume, Tom S. Eaves, Steven M. Tobias

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)
33 Downloads (Pure)

Abstract

The nonlinear robustness of laminar plane Couette flow is considered under the action of in-phase spanwise wall oscillations by computing properties of the edge of chaos, i.e. the boundary of its basins of attraction. Three measures are used to quantify the chosen control strategy on laminar-to-turbulent transition: the kinetic energy of edge states (local attractors on the edge of chaos), the form of the minimal seed (least energetic perturbation on the edge of chaos), and the laminarization probability (the probability that a random perturbation from the laminar flow of given kinetic energy will laminarize). A novel Bayesian approach is introduced to enable the accurate computation of the laminarization probability at a fraction of the cost of previous methods. While the edge state and the minimal seed provide useful information about the dynamics of transition to turbulence, neither measure is particularly useful to judge the effectiveness of the control strategy since they are not representative of the global geometry of the edge. In contrast, the laminarization probability provides global information about the edge and can be used to evaluate the control effectiveness by computing a laminarization score (the expected laminarization probability) and the associated expected dissipation rate of the controlled flow. These two quantities allow for the determination of optimal control parameter values subject to desired constraints. The results discussed in the paper are expected to be applied to a wide range of transitional flows and control strategies aimed at suppressing or triggering transition to turbulence.

Original languageEnglish
Article numberA25
Number of pages31
JournalJournal of Fluid Mechanics
Volume941
DOIs
Publication statusPublished - 27 Apr 2022

Keywords

  • Control and Optimization
  • Bayesian methods
  • Turbulence
  • Fluid Dynamics
  • transition to turbulence
  • Nonlinear instability
  • instability control
  • nonlinear instability

ASJC Scopus subject areas

  • Control and Optimization
  • Applied Mathematics
  • Condensed Matter Physics
  • Mechanics of Materials
  • Mechanical Engineering

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