Supersonic Transition In A Numerically Simulated Tunnel Environment
Abstract
Predicting laminar-to-turbulent transition location is vital for the design of high-speed vehicles. This location depends significantly on the nature of disturbances emanating from tunnel walls, which is difficult to characterize experimentally. Freestream disturbances associated with acoustic radiation from turbulent boundary layers developing spatially over interior walls of a supersonic Mach 2.5 channel are numerically generated, and a reduced order model for the freestream disturbances is developed using data-driven techniques. Transition induced by these perturbations is studied on a canonical flat plate, from freestream receptivity to breakdown stages. The most amplified oblique first mode wave interacts with other perturbations in the inlet spectra generating boundary-layer streaks, which is further confirmed by bicoherence analysis. An intermittent high-frequency signature is revealed by wavelet transformation at the boundary-layer edge, which manifests as short wavelength structures over streamwise streaks. Late non-linear stages of transition are characterized by merging turbulent spots and asymmetrically oscillating low-speed streaks closer to the wall. Further, the development of early turbulent regime is accompanied by multi-scale interactions and an emergence of an inertial sub-range.
Recommended Citation
H. Goparaju et al., "Supersonic Transition In A Numerically Simulated Tunnel Environment," AIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2022, article no. AIAA 2022-1826, American Institute of Aeronautics and Astronautics, Jan 2022.
The definitive version is available at https://doi.org/10.2514/6.2022-1826
Department(s)
Mechanical and Aerospace Engineering
International Standard Book Number (ISBN)
978-162410631-6
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2023 American Institute of Aeronautics and Astronautics, All rights reserved.
Publication Date
01 Jan 2022
Comments
National Science Foundation, Grant CBET 2001127