Modelling and control of turbulent and transitional flows
Time: Thu 2020-06-04 10.00
Location: Live-streaming: https://kth-se.zoom.us/j/62627066334 If you lack computer or computer skills, contact Luca Brandt, firstname.lastname@example.org, Stockholm (English)
Subject area: Engineering Mechanics
Doctoral student: Pierluigi Morra , Teknisk mekanik
Opponent: Professor Aimee S. Morgans, Imperial College London
Supervisor: Dan S. Henningson, Linné Flow Center, FLOW, Mekanik, SeRC - Swedish e-Science Research Centre; Docent Ardeshir Hanifi, Linné Flow Center, FLOW, SeRC - Swedish e-Science Research Centre; André V. G. Cavalieri, ; Shervin Bagheri, Linné Flow Center, FLOW, SeRC - Swedish e-Science Research Centre
The dynamics of fluid motion can accurately be described by the Navier– Stokes equations. Manipulating these equations to reduce their complexity but preserving their main characteristics has always been a key research activity in the field of fluid mechanics. Effort has been made to provide high-fidelity models for wall-bounded turbulent flows or reduced-order models for applications such as drag reduction, lift enhancement, or noise suppression. Model order reduction has also been employed for studying the dynamics of the Navier-Stokes equations. In this PhD thesis, the emphasis is on providing computationally inexpensive methods for industrial applications.
Numerical simulations are performed to tackle model order reduction for flow control of transitional boundary-layer flows for drag reduction. It is assumed that localized wall sensors and actuators are available, and that only the time signals accessible in experiments are provided. Thus, a method to include unknown high-dimensional input disturbances in a reduced-order model of a transitional boundary-layer flow is presented. The method is applied for the design of an optimal controller for drag reduction through delay of transition. Moreover, the role of the actuator is discussed and a comparison between realistic actuators and actuators computed using optimization methods is presented. Here, the emphasis is on the effectiveness of the actuators for the studied flow control cases.
Numerical simulations are also performed to tackle high-fidelity modeling in wall-bounded turbulent flows. The accuracy of the resolvent analysis in predicting the most energetic flow structures in a wall-bounded turbulent flow is quantified for different temporal frequencies. A direct comparison between the predictions from the resolvent analysis and the flow structures identified in DNS data is presented. Moreover, the beneficial effects attained with the inclusion of the Reynolds-stresses via an eddy-viscosity model are clarified for flows with friction Reynolds number up to 1007.