Marcel Staats

Iterative Learning Active Flow Control Applied to a Compressor Stator Cascade With Periodic Disturbances

This paper presents the capability of iterative learning active flow control to decrease the impact of periodic disturbances in an experimental compressor stator cascade with sidewall actuation. The periodic disturbances of the individual passage flows are generated by a damper flap device that is located downstream of the trailing edges of the blades. The device mimics the throttling effect of periodically closed combustion tubes in a pulsed detonation engine (PDE). For the purpose of rejecting this disturbance, the passage flow is manipulated by fluidic actuators that introduce an adjustable amount of pressurized air through slots in the sidewalls of the cascade. Pressure sensors that are mounted flush to the suction surface of the middle blade provide information on the current flow situation. These data are fed back in real-time to an optimization-based iterative learning controller (ILC). By learning from period to period, the controller modifies the actuation amplitude such that, eventually, a control command trajectory is calculated that reduces the impact of the periodic disturbance on the flow in an optimal manner.

Active Flow Control on a Highly Loaded Compressor Cascade with Non-steady Boundary Conditions

This paper discusses the effect of a periodical disturbance in the wake of a highly loaded axial compressor on the pressure distribution and the secondary flow characteristics of the turbo machinery stator blades. A large scale axial compressor cascade, consisting of six two dimensional passages, has been used for this investigation. The test rig is equipped with an active flow control system to enhance the operating range of the compressor. Results that have been achieved by means of side wall actuation are also presented.

Active Control of the Corner Separation on a Highly Loaded Compressor Cascade With Periodic Non-Steady Boundary Conditions by Means of Fluidic Actuators

This contribution discusses the impact of a non-steady outflow condition on the compressor stator flow that is forced through a mimic in the wake of a linear low speed cascade to simulate the conditions that would be expected in a pulsed detonation engine. 2D/3C-PIV measurements were made to describe the flow field in the passage. Detailed wake measurements provide information about static pressure rise as well as total pressure loss. The stator profile used for the investigations is highly loaded and operates with three-dimensional flow separations under design conditions and without active flow control. It is shown that side wall actuation helps to stabilize the flow field at every phase angle and extends the operating range of the compressor stator. Furthermore, the static pressure gain can be increased by 6% with a 4% loss reduction in time averaged data.Copyright

Comparison of Iterative Learning and Repetitive Control Applied to a Compressor Stator Cascade

This contribution deals with learning control algorithms applied as closed-loop flow controllers. The system to be controlled is an experimental linear compressor stator cascade with sidewall actuation. A damper flap device located downstream of the trailing edges of the blades generates periodic disturbances of the individual passage flows. By learning from period to period, the controllers are able to successfully decrease the effect of the disturbance on the pressure coefficient distribution of the blades’ suction surface.