Turbomachinery blade design using a Navier-Stokes solver and artificial neural network
- von Karman Inst. for Fluid dynamics, Rhode-Saint-Genese (Belgium). Turbomachinery Dept.
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 two-dimensional turbine blades, of which three examples are presented in this paper.
- Sponsoring Organization:
- USDOE
- OSTI ID:
- 351627
- Report Number(s):
- CONF-980615--
- Journal Information:
- Journal of Turbomachinery, Journal Name: Journal of Turbomachinery Journal Issue: 2 Vol. 121; ISSN JOTUEI; ISSN 0889-504X
- Country of Publication:
- United States
- Language:
- English
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