Document Type : Research Article
department of aerospace engineering Amirkabir university of technology
صنعتی امیرکبیر*مهندسی هوافضا
This paper proposes an efficient meta-heuristic method for aerodynamic shape design. The method is relied on four principles and starts from a random initial population. Population members are then divided into two expert groups: the free group and the guided group; each has specific tasks for effective search of the domain, but with a single new operator. This operator has an intelligent mechanism so that diversification and intensification of the population can lead the members by passing the local optimal to the global one. The new method is validated through a standard test function. Then its performance evaluates in the application of an inverse geometric reconstruction and results compared with Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Mean-Variance Mapping Optimization (MVMO). Results show that the new method outperforms the alternative methods in terms of convergence rate and reaching the global optimum. Finally, the performance of the new method is evaluated in an engineering problem with high computational cost. In this case, the goal is drag coefficient minimization of the RAE 2822 airfoil at a fixed lift coefficient with constraints on the pitching moment and airfoil area. An unstructured grid Navier-Stokes flow solver with a two-equation turbulence model is used to evaluate the aerodynamic objective function. The results show that the optimal solutions obtained by the new method outperform those of MVMO with faster convergence.