Abstract
Constrained and unconstrained transonic airfoil design optimization problems are investigated by applying the simultaneous perturbation stochastic approximation (SPSA) method to objective functions which are estimated using a finite volume computational fluid dynamics (CFD) flow solver solving the Navier-Stokes equations during each design cycle. The performance and advantages of SPSA method over Simulated Annealing, another global optimization method are assessed. The computed results show that the SPSA method is robust in reaching optimal aerodynamic shapes, is easy to implement and efficient in decreasing the computational cost compared with Simulated Annealing.
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