Turbomachinery Blade Design Using a Navier-Stokes Solver and Artificial Neural Network PUBLIC ACCESS

[+] Author Affiliations
Stéphane Pierret, R. A. Van den Braembussche

von Karman Institute for Fluid Dynamics, Rhode-Saint-Genèse, Belgium

Paper No. 98-GT-004, pp. V001T01A002; 8 pages
  • ASME 1998 International Gas Turbine and Aeroengine Congress and Exhibition
  • Volume 1: Turbomachinery
  • Stockholm, Sweden, June 2–5, 1998
  • Conference Sponsors: International Gas Turbine Institute
  • ISBN: 978-0-7918-7862-0
  • Copyright © 1998 by ASME


This paper describes a knowledge-based method for the automatic design of more efficient turbine blades. An Artificial Neural Network (ANN) is used to construct an approximate model (response surface) using a database containing Navier Stokes solutions for all previous designs. This approximate model is used for the optimization, by means of Simulated Annealing (SA), of the blade geometry which is then analyzed by a Navier-Stokes solver.

This procedure results in a considerable speed-up of the design process by reducing both the interventions of the operator and the computational effort. It is also shown how such a method allows the design of more efficient blades while satisfying both the aerodynamic and mechanical constraints. The method has been applied to different types of 2D turbine blades of which three examples are presented in this paper.

Copyright © 1998 by ASME
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