Loading...

Application of multilayer perceptron network for unsteady three dimensional aerodynamic load prediction

Gholamrezaei, M ; Sharif University of Technology | 2007

355 Viewed
  1. Type of Document: Article
  2. Publisher: 2007
  3. Abstract:
  4. Surface pressure measurements were conducted for a pitch oscillation wing in a subsonic closed circuit wind tunnel. Experimental results have been used to train a multilayer perceptron network to foresee the effect of modification of oscillation amplitude and reduced frequency. Consistent results are obtained both for the training data as well as generalization to other amplitudes and reduced frequencies. This work indicates that artificial neural networks can reliably predict aerodynamic coefficients and forecast the effects of oscillation amplitude as well as reduced frequency on the wind turbine blade performance. Moreover, this study introduces a new tool for the designers to have enough knowledge of the model behavior
  5. Keywords:
  6. Multilayer perceptron network ; Oscillation amplitude ; Pitch oscillation wings ; Natural frequencies ; Neural networks ; Turbomachine blades ; Wind tunnels ; Wind turbines ; Wings ; Aerodynamic loads
  7. Source: 25th AIAA Applied Aerodynamics Conference, 2007, Miami, FL, 25 June 2007 through 28 June 2007 ; Volume 2 , 2007 , Pages 1197-1202 ; 10485953 (ISSN) ; 1563478986 (ISBN); 9781563478987 (ISBN)