Project Description: The development of future high-speed flight vehicles requires a deep understanding of boundary-layer transition, which is critical for vehicle design and performance. However, predicting transition remains challenging, especially when extrapolating from wind tunnel experiments to flight conditions. In hypersonic flows (typically exceeding 5 times the speed of sound), transition is strongly influenced by the 2nd mode instability. The maximum amplitude of these 2nd mode waves plays a key role in determining the onset of transition, directly impacting aerodynamic performance and heat transfer. This project investigates how maximum second-mode amplitudes vary with Mach number in wind tunnel and flight conditions for a 7-degree half-angle cone. The intern will perform numerical simulations using the UA High Performance Computing system to determine 2nd mode amplitudes at different Mach numbers and compare results against experimental data to evaluate the validity of the simulation approach.
NASA Relevance: This project advances NASA-relevant research by improving predictive capabilities for hypersonic boundary-layer transition, supporting safer and more efficient high-speed vehicle design for future air and space missions.
Work Description: The intern will perform linear stability calculations and Navier-Stokes simulations using in-house codes to compute maximum second-mode amplitudes for a hypersonic boundary layer on a 7-degree half-angle cone at varying Mach numbers. These simulations will be conducted on the University of Arizona High-Performance Computing (HPC) system. The intern will learn to use custom pre- and post-processing tools written in Python and Fortran to set up simulations and analyze data. They will also gain experience with Tecplot for data visualization and develop proficiency in using the command line terminal for executing simulations. Additionally, they will assist in updating Python scripts to automate workflows for simulation setup, execution, and data processing.
In summary, the intern will gain hands-on experience in high-performance computing, large-scale simulations, and automation of numerical workflows using Python.
Open or Reserved Project: Reserved, 2 positions