Hypersonic Shock Wave Boundary Layer Interaction Studies on a Flat Plate at Elevated Surface Temperature
Abstract
Experimental shock wave boundary layer interactions (SBLI) at a compression corner of a flat plate model with deflectable flap and variable surface temperature were studied in the High Enthalpy Shock Tunnel Göttingen (HEG) of the German Aerospace Center (DLR) at Mach 7.4 and \({6.65\times 10^6}\,{\text {m}^{-1}}\) unit Reynolds number. The present paper focuses on the effect of the leading edge bluntness and surface temperature. The effects are discussed based on surface heat flux and surface pressure measurements as well as schlieren visualizations. The study confirms that the state of the incoming boundary layer is crucial for the interaction. A small change of the leading edge bluntness was found to affect the boundary layer stability and thus the SBLI. In contrast, surface heating was found to destabilize the boundary layer. Tests at different flap deflection angles and transitional incoming boundary layers revealed that the transition process was completed in the separated shear layer, leading to a fully turbulent reattachment on the flap. The experimental effort is complemented by Reynolds-Averaged Navier–Stokes (RANS) computations providing insights into fundamental trends. The 2D simulations underpredict the size of the separation bubble in the compression corner but qualitatively mirrored the experimental trends. The wall heating resulted in an increased boundary layer thickness, reduced the extent of the separation bubble and elevated the peak boundary layer temperature on the flap.
Notes
Acknowledgements
This work was performed within the Aero-Thermodynamic Loads on Lightweight Advanced Structures II project investigating high-speed transport. ATLLAS II, coordinated by ESA-ESTEC, is supported by the EU within the 7th Framework Programme Theme 7 Transport, Contract no.: ACP0-GA-2010-263913. Further info on ATLLAS II can be found on http://www.esa.int/techresources/atllas_II. Computations were performed on the GPC supercomputer at the SciNet HPC Consortium through Compute Canada’s Resource Allocation Competition (RAC).
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