Abstract
The objective of the joint research project HINVA (High-Lift In-Flight Validation) funded by the German Federal Ministry of Economics and Technology within the fourth Aeronautical Research Program LuFo IV is to significantly enhance the accuracy and reliability of both numerical and experimental simulation methods with respect to the aerodynamic performance prediction of civil transport aircraft with deployed high-lift devices. To achieve this goal, the most advanced computational fluid dynamics (CFD) and wind tunnel simulation methods currently in industrial use are to be validated against flight test data. DLR’s Airbus A320-200 Advanced Technology Research Aircraft (ATRA) serves as a common configurative basis for the three fields of methodology 1) flight test, 2) high Reynolds-number testing in the European Transonic Wind Tunnel (ETW), and 3) numerical simulation using DLR’s TAU code. To meet the demanding accuracy specified in HINVA, the wind tunnel model wing must be geometrically similar to the ATRA wing in flight, i.e. have the same spanwise twist distribution, when subjected to the aerodynamic loads existing at maximum lift flow conditions in ETW. The inverse design approach of defining the corresponding model jig shape is based on a combined use of measured flow conditions and wing deformations from a selected reference test flight and fluid-structure coupled simulations using a model scale CFD grid, wind tunnel flow conditions equivalent to the reference flight state, and a wind tunnel structural model. When exposed to the aerodynamic loads under ETW flow conditions, the designed model jig shape leads to a final wing shape which closely resembles ATRA’s actual wing shape at maximum lift.
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Bier, N., Keye, S., Rohlmann, D. (2016). Advanced Design Approach for a High-Lift Wind Tunnel Model Based on Flight Test Data. In: Radespiel, R., Niehuis, R., Kroll, N., Behrends, K. (eds) Advances in Simulation of Wing and Nacelle Stall. FOR 1066 2014. Notes on Numerical Fluid Mechanics and Multidisciplinary Design, vol 131. Springer, Cham. https://doi.org/10.1007/978-3-319-21127-5_20
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