1. February 2020
up to German TVöD 13
Future aircraft will use laminar flow wings in order to reduce the fuel consumption and the ecological footprint of aviation. For the design of laminar wings, state-of-the-art CFD codes currently use empirical criteria, database methods, transport equation models or concepts based linear stability theory (LST) for transition prediction. The different methods vary significantly in the amount of physics modelled, and usually the consideration of more boundary layer physics leads to a significant increase in computational costs. For the design of aircraft, however, a physics-based transition model is required at low computational cost.
A large number of transition studies using LST theory have been performed at DLR in the last two decades. These studies cover a variety of different configurations at different flight Reynolds numbers, Mach numbers, angles of attack, etc. Due to this, a huge data base of laminar boundary-layer flow data with corresponding linear stability results and transition locations exists, already covering a wide range of flow parameters relevant for laminar-turbulent transition for future aircraft. These data can be used for the development and training of new transition prediction concepts based on machine learning (ML), either for predicting directly the transition location or for estimating the local boundary-layer instability characteristics as an alternative to the database methods.
This research project/PhD Position is envisaged to comprise the following steps:
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Dr. Stefan Hein
Institute of Aerodynamics and Flow Technology
Phone: +49 551 709-2687