Title :
Intelligent aerodynamic design for airfoil based on Artificial Neural Network Method
Author :
Jie, Chen ; Gang, Sun ; Xin, Jin
Author_Institution :
Dept. of Mech. & Eng. Sci., Fudan Univ., Shanghai, China
Abstract :
The Artificial Neural Network (ANN) method is applied to intelligent aerodynamic design for airfoils. A Self-Organizing Map (SOM) network is demonstrated selecting referenced airfoils which mostly meet or close to the design requirement from airfoil database. Then a Back-Propagation (BP) network automatically learns the relationship between referenced airfoil geometry and aerodynamic performance by means of supervised learning approach. After a set of training, the BP network is able to estimate airfoil aerodynamic characteristics using knowledge and criteria learned before. Design results indicate that trained network can give effective prediction and excellent aerodynamic efficiency for airfoil.
Keywords :
aerodynamics; aerospace components; aerospace computing; backpropagation; intelligent design assistants; self-organising feature maps; airfoil database; artificial neural network method; back propagation network; design requirement; intelligent aerodynamic design; self-organizing map network; supervised learning approach; training; Aerodynamics; Artificial intelligence; Artificial neural networks; Automotive components; Data mining; Intelligent networks; Learning systems; Neurons; Shape; Spatial databases; BP; SOM; artificial neural network; intelligent airfoil design;
Conference_Titel :
Computer and Automation Engineering (ICCAE), 2010 The 2nd International Conference on
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-5585-0
Electronic_ISBN :
978-1-4244-5586-7
DOI :
10.1109/ICCAE.2010.5451445