Skin friction accounts for as much as 50% of the drag affecting aircraft and 100% of the drag in channels and pipes, with turbulent drag being roughly twice that of laminar drag. The motivation behind using transition control to maintain laminar shear flows is thus readily apparent, however, a practical manner of doing so is far less readily apparent.
Application of the linear systems approach to the problem of transition control in shear flows has seen great progress over the past two decades, particularly in simulations where one can use techniques which are not physically implementable and without the computational speed constraints which apply to real-time application. The primary obstacles standing in the way of physical application include physically realizable sensor and actuator arrays and system models which are computationally tractable for control and estimation in real-time.
This research takes a new approach toward overall model order reduction, and subsequently sensor and actuator resolution reduction, by utilizing insights regarding the physical mechanisms of transition to turbulence in plane Poiseuille flow. Preliminary results of a state estimator designed using this approach toward model order and sensor resolution reduction are promising, with state augmentation of the Kalman filter successfully handling aliased measurements. Moving forward, the methodology will be extended and refined to accommodate process noise, actuator input, and further model order reduction. Control algorithms will be developed and the system’s ability to control transition to turbulence under various disturbance types will be tested and evaluated. If satisfactory performance is obtained, the methodology may be extended to other shear flow configurations such as round pipes and boundary layers.