Work / Research
Understanding transition in hypersonic flow
Investigating Mack second-mode instabilities and working to characterize the acoustic environment at the FAMU–FSU PolySonic Wind Tunnel.
The research question
How do disturbances in the tunnel’s acoustic environment relate to instability growth and boundary-layer transition? My research at the FAMU–FSU PolySonic Wind Tunnel focuses on characterizing that environment and examining how disturbances develop over a cone in hypersonic flow.
Mack second-mode instabilities
Mack second-mode instabilities are high-frequency acoustic disturbances within a hypersonic boundary layer. Their amplification can contribute to the transition from laminar to turbulent flow. The aim is to identify their frequency content and growth, and understand how the incoming disturbance environment influences what is measured on the model.
Characterizing the acoustic environment
A central goal is to characterize the tunnel’s background disturbances: which frequencies are present, their relative strength, and how they relate to the signals measured near the cone. This context matters when interpreting instability growth and transition in a wind tunnel.
Experimental approach
The research uses a 7° half-angle circular cone at zero angle of attack, with removable tips for studying bluntness effects. Flush-mounted PCB pressure transducers and high-speed Schlieren imaging provide complementary ways to examine the flow. My contribution spans experimental diagnostics, signal analysis, literature synthesis, and preparation of the model and instrumentation. I designed and manufactured the modular cone model in SolidWorks, including embedded sensor mounts, and met with tunnel engineers for force-balance testing.
Signal analysis
Time-series and frequency-domain analysis in Python and MATLAB uses FFTs and Welch power spectral density estimates to examine disturbance spectra. The aim is to identify candidate second-mode frequency bands, compare signal content, and relate boundary-layer measurements to the tunnel’s acoustic environment.
Research goals
Research goals included comparisons with linear stability theory and N-factor methods, and a better understanding of transition location, length, and the tunnel acoustic environment.
Diagnostic integration
Worked with the research team on integrating and optimizing focused laser differential interferometry (FLDI) diagnostics and computational analysis.