Abstract
In the airfoil and wing optimization design process, both the convergence speed of optimization algorithm and the precision of surrogate model will be greatly influenced by the number of design variables. So it is very important for airfoil optimization design to develop a precise airfoil parametric approach with less design variables. The precision of Kriging model was studied based on CST(class function/shape function transformation)airfoil parametric approach in this article. An optimization design system was developed based on improved particle swarm optimization algorithm. Through the subsonic wing's drag reduction design and robust design, the system has been proved to be reliable, useful and of high design quality in engineering.
Original language | English |
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Pages (from-to) | 443-449 |
Number of pages | 7 |
Journal | Kongqi Donglixue Xuebao/Acta Aerodynamica Sinica |
Volume | 30 |
Issue number | 4 |
State | Published - Aug 2012 |
Keywords
- Breed
- Class function/shape function transformation
- Kriging model
- Particle swarm optimization(PSO) algorithm
- Robust design
- Surrogate model