25th Congress of International Council of the Aeronautical Sciences, 3 - 8 September 2006, Hamburg, Germany
Paper ICAS 2006-2.6.3

AERODYNAMIC COEFFICIENT PREDICTION OF A GENERAL TRANSPORT AIRCRAFT USING NEURAL NETWORK

R. Wallach, B. S. de Mattos, R. da Mota Girardi
Instituto Tecnológico de Aeronáutica (ITA), Brazil

Keywords: neural network, aircraft design

The present work is concerned with the development of a fast and accurate methodology based on artificial neural networks for predicting aerodynamic coefficients of a generic transport aircraft. The training and validation data sets were generated by CFD code, enclosing a wide range of wing geometries and flow conditions.

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