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Transition to Turbulence Over Convex Surfaces and Utilization of Instabilities for Optimal Laminar Separation Delay

Transition to Turbulence Over Convex Surfaces and Utilization of Instabilities for Optimal Laminar Separation Delay

Monday 17/12/2018
  • Dr. Michael Karp
  • Classroom 165, ground floor, Library, Aerospace Eng.
  • Center for Turbulence Research, Faculty of Mechanical Engineering
  • Stanford University
  • The talk will be given in English.

Understanding flow instability mechanisms in boundary layers is valuable for designing more efficient aerodynamic and hydrodynamic surfaces. This talk consists of two parts; the first discusses instabilities and transition to turbulence in boundary layers over convex surfaces, such as a wing’s leading edge. The second part discusses the utilization of instability mechanisms for optimal separation delay.

Contrary to flows over concave surfaces, which are prone to the Görtler instability, boundary layers over convex surfaces are stabilized as a result of the curvature. Nevertheless, non-modal mechanisms may enable significant disturbance growth which can make the flow susceptible to secondary instabilities. The influence of curvature on primary and secondary instabilities is investigated theoretically and numerically. The predictions of local stability theory are verified by direct numerical simulations, which demonstrate that only sufficiently long and energetic streaks trigger the breakdown to turbulence.

Flow separation often leads to reduced aerodynamic performance. Passive control devices, such as vortex generators, successfully delay separation by triggering turbulence. Although the turbulence induces flow reattachment, its adverse effects are increased drag and heat transfer. Moreover, finding the optimal parameters for the design of vortex generators is oftentimes based on trial and error, especially their spanwise spacing. Our aim is to find the optimal perturbation that one needs to generate, such that the separation location is delayed as downstream as possible. It is shown that a perturbation from linear stability theory leads to significant delay of separation and serves as a good starting point for the nonlinear optimization algorithm. The mechanism responsible for separation delay is a mean flow distortion, generated by nonlinear interactions during the non-modal growth stage. The mean flow distortion augments the velocity close to the wall, counteracting the velocity deceleration in that region.

Light refreshments will be served before the lecture
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