Active flow control is an area of heightened interest in the aerospace community. Previous research on flow control design processes heavily depended on trial and error and the designers knowledge and intuition. Such an approach cannot always meet the growing demands of higher design quality in less time. Successful application of computational fluid dynamics (CFD) to this kind of control problem critically depends on an efficient searching algorithm for design optimization. CFD in conjunction with Genetic Algorithms (GA) potentially offers an efficient and robust optimization method and is a promising solution for current flow control designs. Current research has combined different existing GA techniques and motivation from the two-jet GA-CFD system previously developed at the University of Kentucky propose the applications of a real coded Continuous Genetic Algorithm (CGA) to optimize a four-jet and a synthetic jet control system on a NACA0012 airfoil. The control system is an array of jets on a NACA0012 airfoil and the critical parameters considered for optimization are the angle, the amplitude, the location, and the frequency of the jets. The design parameters of a steady four-jet and an unsteady synthetic jet system are proposed and optimized. The proposed algorithm is built on top of CFD code (GHOST), guiding the movement of jets along the airfoils upper surface. The near optimum control values are determined within the control parameter range. The current study of different Genetic Algorithms on airfoil flow control has been demonstrated to be a successful optimization application.
| Identifer | oai:union.ndltd.org:uky.edu/oai:uknowledge.uky.edu:gradschool_theses-1454 |
| Date | 01 January 2007 |
| Creators | Kotragouda, Narendra Beliganur |
| Publisher | UKnowledge |
| Source Sets | University of Kentucky |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | University of Kentucky Master's Theses |
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