In the past few years the application of machine learning (ML) methods has increased rapidly throughout various domains including several engineering disciplines. In particular artificial neural networks (ANN) have been heavily investigated for reconstruction, clustering and classification problems. In aerodynamics, the main interest is in applying ML methods to predict different quantities of interest such as the lift coefficient or the surface pressure distributions at changing flight conditions based on just a few, well-chosen highly accurate and expensive simulations. The current approach to achieve such predictions is to combine dimensionality reduction methods and interpolation or regression techniques offering reasonable results for a range of aerodynamic problems. Nevertheless, a smart combination of established approaches with carefully selected ANN might yield another boost in accuracy and efficiency.
The emerging potential offered by ANN should be investigated during this master thesis and compared to existing and more established methods. Therefore the following steps could be seen as a rough guideline:
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Dr. Philipp Bekemeyer
Institute of Aerodynamics and Flow Technology
Phone: +49 531 295-3871