Published online by Cambridge University Press: 03 February 2016
A new similarity parameter has been used for analyzing the unsteady aerodynamic behaviour of vehicles undergoing sinusoidal pitching motion. If this parameter is identical for two unsteady manoeuvres with different reduced frequencies and oscillation amplitudes, the corresponding hysteresis loops of the force and moment collapse on each other. To support and verify this, extensive unsteady wind tunnel tests have been conducted on a standard model, which is a well known fighter type configuration. The acquired data were used to train a certain type of neural network, called the Generalised Regression Neural Network (GRNN), to reduce the number of wind tunnel runs. The scheme, once proved to give the correct results for various conditions, was applied to extend the experimental data to other conditions that have not been tested in the tunnel. Both the predicted and acquired tunnel data were used to show the performance of the similarity parameter.
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