نوع مقاله : مقاله پژوهشی
نویسندگان
1 دانشکده مهندسی هوافضا- دانشگاه صنعتی امیرکبیر
2 دانشکده مهندسی هوافضا - دانشگاه صنعتی امیرکبیر
چکیده
کلیدواژهها
عنوان مقاله [English]
نویسندگان [English]
Wing section optimization is aceomplished using a combined strategy consisting of a genetic algorithm (GA ) and an artificial neural network (A::-..r:K) . A real coded genetic algmi.t hm is utilized for an op timum search in design space. The numerical so lution of inviscid flow governing equations is used for evaluation of the design candidates. In order to red uce the number of these
time consuming eval uations required by GA, every M generat ion, all chromosomes fitness are trained to a neural net work. Then, a control based genetic local search is handled by AX':\ as a fitness estimator to find new promising regions in design space. It is demon strated that this approach could save considerable computational time in application fields, such as
aerodynamic design . Results are presented for a constrained optimization of an airfoil at transonic flow conditions. The PARSEC method of airfoil generator and unstructured grid movement tech nique are used in this work. Event ually, optimum airfoil geometry is achieved by about 50% less com putational effort compared with the conventional GA method.
کلیدواژهها [English]
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