Project Description: Predicting boundary-layer transition in high-speed flows is critical for vehicle design and operation. During atmospheric flight, particles impinge on the vehicle surface and generate localized wave packets that grow as they travel downstream. This spreading behavior resembles observations in low-speed flows, for which Emmons developed a spot-based transition model. A parameter in that model is the wave packet spreading angle. No systematic investigation of wave packet spreading angles exists for the hypersonic regime. This project aims to close this gap and determine spreading angles for various Mach numbers, wall temperatures, and geometries. Using direct numerical simulations (DNS), the intern will perform wave packet simulations in flat plate and cone boundary layers to extract spreading angles in the linear and early nonlinear stages. Results will provide insight into how compressibility and wall cooling influence spreading behavior relevant to spot-based transition models.
NASA Relevance: This project supports NASA-relevant research by improving understanding of wave packet dynamics in hypersonic boundary layers, contributing to more accurate transition prediction models that improve the design of high-speed vehicles and their thermal protection systems.
Work Description: The intern will perform linear stability calculations and Navier-Stokes simulations using in-house codes to simulate the development of three-dimensional wave packets at various Mach numbers for a flat plate and a cone. 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