applying evolutionary optimization on the airoil design
Publish place: Journal of Computational and Applied Research in Mechanical Engineering، Vol: 2، Issue: 1
Publish Year: 1392
نوع سند: مقاله ژورنالی
زبان: English
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شناسه ملی سند علمی:
JR_JCARME-2-1_006
تاریخ نمایه سازی: 17 خرداد 1393
Abstract:
in this paper lift and drag coefficients were numerically investigated using NUMECA software in a set of 4-digit NACA airfoils two metamodels based on the evolved group method of data handling GMDH type neural networks were then obtained for modeling both lift coefficient CL and drag coefficieng CD with respect to the geometrical design parameters after using such obtained polynomial neural networks modified non-dominated sorting genetic algorithm NSGAII was used for pareto based optimization of 4-digit NACA airfoils considering two conflicting objectives such as CL and CD.further evaluations of the design points in the obtained pareto fronts using the NUMECA software showed the effectiveness of such an approach moreover it was shown that some interesting and important relationships as the useful optimal design principles involved in the performance of the airfoils can be discovered by the pareto-based multi-objective optimization of the obtained polynomial meta-models ,such important optimal principles would not have been obtained without using the approach presented in this paper.
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Authors
abolfazl khalkhali
school of automotive engineering iran university of science and technology/tehran.iran
hamed safikhani
department of mechanical engineering amirkabir university of technology tehran.iran