Abstract
We present a new method for blade shape optimization with better aero-dynamical performance; such a method combines a variable learning rate momentum back-propagation neural network (VLMBPNN) algorithm with non-uniform rational B-spline (NURBS) method. This method is used to reshape the second rotor blade of a two stage fan compressor, especially the hub section, to improve its aero-dynamical performance. The computational fluid dynamics (CFD) results of the optimized rotor blade and the optimized whole fan compressor are obtained and compared with those of the original rotor and the original fan compressor. The results show that this method is feasible and can improve the flow field structure of the rotor blade as well as the whole fan compressor. The results also indicate that the isentropic efficiency and total pressure ratio of the whole fan compressor are increased by 0.3794 percent and 0.2254 percent respectively.
| Original language | English |
|---|---|
| Pages (from-to) | 266-269 |
| Number of pages | 4 |
| Journal | Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University |
| Volume | 25 |
| Issue number | 2 |
| State | Published - Apr 2007 |
Keywords
- Blade optimization
- Neural network
- Variable learning rate