33th Congress of the International Council of the Aeronautical Sciences

01.1 - Aircraft Design and Integrated System (Basics and Theory)

SUCCESSIVE KNOWLEDGE BUILDUP AND TRANSFER DURING THE ANALYSIS OF SCALED UAV WINGS BY MEANS OF MACHINE LEARNING

T. Klaproth╣, M. Hornung╣; ╣Technical University of Munich, Germany

We provide formulas for scaling factors to estimate higher-fidelity results from low-fidelity methods. We demonstrate succesful correction of semi-empiric formulas that are intended for other aircraft classes. We explore the potential for knowledge buildup and transfer within an automated design optimization loop. We show an approach that avoids unquestioned imitation of higher-fidelity aero data.


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