Control of flow separation over a forward-facing step by model reduction

Abstract

Design and implementation of reduced-order optimal controller for flow separation are investigated. The reduced-order controller design is based on proper orthogonal decomposition (POD) and Galerkin projection. Detailed finite element simulations are performed, and POD is applied to the resulting data to extract the most energetic eigenmodes. These global eigenmodes are then used in conjunction with the Galerkin projection to obtain a reduced-order (low-dimensional) model. Reduced-order models are not only attractive for real-time control computation but also crucial for detailed stability and bifurcation analysis. We investigate the design of optimal controller for flow separation in a channel with this model where actuation is performed on a small part of the boundary. Two different types of surface actuation are considered––tangential blowing and suction through a single slot. Best locations for actuation and adaptive procedure for reduced-order model are explored. The proposed approaches are evaluated by investigating the control of flow separation over a forward-facing step channel. Our methods are found to be efficient and fast, and our methods demonstrate a significant reduction in computational time and feasibility. Dramatic separation delays are observed on all cases. It is found that the tangential blowing is more efficient in mitigating flow separation and reducing wake spread.