Optimization of Active Flow Control over an Airfoil Using a Surrogate-Management Framework

• Published in: Journal of aircraft 2010-03, Vol.47 (2), p.603-612
• Main Authors: Han, Z.-H, Zhang, K.-S, Song, W.-P, Qiao, Z.-D
• Format: Article
• Language: English
• Subjects: Accuracy; Aerodynamics; Aircraft; Applied fluid mechanics; Approximation; Comparative analysis; Computational methods in fluid dynamics; Exact sciences and technology; Flow control; Fluid dynamics; Fundamental areas of phenomenology (including applications); Optimization; Physics; Simulation
• ISSN: 0021-8669; 1533-3868
• DOI: 10.2514/1.45899

An efficient method based on the surrogate-management framework has been excised to optimize the actuation parameters of active flow control over an airfoil via a synthetic jet. In this approach, sample points are chosen by the design of experiments method, and approximation models are built based on the sampled data obtained from unsteady Reynolds-averaged Navier-Stokes simulations. The accuracy of these approximation models is evaluated at some test points by comparing the approximated values with the accurate values obtained from unsteady Reynolds-averaged Navier-Stokes simulations. Three types of approximation models (quadratic response-surface model, kriging model, and radial-basis-function neutral network) are built from the same data set. The model with highest accuracy is chosen as the surrogate model to be used to replace the unsteady Reynolds-averaged Navier-Stokes analysis during optimization. The optimization objective is to maximize the lift coefficient of a NACA 0015 airfoil at given angles of attack (14 to 22...), with the jet momentum coefficient, nondimensional frequency, and jet angle being the design variables. The surrogate model is coupled with a simulated annealing genetic algorithm optimizer to efficiently obtain the global optimum. As a result of the optimization process, the lift coefficient at an angle of attack of 16... is increased by 16.9% and the corresponding drag is decreased by 13.4% with respect to the initial controlled flow. It is preliminarily shown that the presented method is efficient and applicable for optimization of active flow control via a synthetic jet. (ProQuest: ... denotes formulae/symbols omitted.)