When
Where
Student: Aaron Larsen, Program in Applied Mathematics
Title: Vibrational State-to-State Modeling of High-Enthalpy Flows: From Data-Driven Kinetics to Shock-Tube Simulations
Advisors: Dr. Kyle Hanquist, Department of Aerospace and Mechanical Engineering
Location: Zoom link: https://arizona.zoom.us/j/88281738930
Abstract: Hypersonic flows exhibit strong thermochemical nonequilibrium, requiring high-fidelity models to accurately capture energy transfer and chemical kinetics among excited molecular states. While rotational modes equilibrate rapidly with translational energy, vibrational modes remain in nonequilibrium over much larger timescales. State-to-state (STS) modeling provides a detailed description of these processes, but it is limited by the computational cost of generating state-resolved reaction rates and solving the resulting systems of equations governing the flow.
This work develops a comprehensive computational framework for vibrational STS modeling of nonequilibrium oxygen flows. First, a generalized STS framework is developed and implemented within Mutation++ to allow arbitrary state-resolved reaction rate datasets to be incorporated into computational fluid dynamics (CFD) simulations. Second, conservative mapping approaches are developed to transfer reaction rates between different vibrational energy ladders while preserving macroscopic thermodynamic behavior. Third, data-driven kinetic approaches are developed to improve the computational tractability of STS modeling. Gaussian process regression is employed in order to enhance forced harmonic oscillator theory with quasi-classical trajectory data, while machine learning approaches are investigated to predict state-resolved vibrational populations from two-temperature flow quantities through prediction of vibrational state mass-fraction evolution. The resulting STS framework is then applied to canonical flows, including pure- and diluted-oxygen flows, where comparisons to experimental measurements and other reaction rate datasets demonstrate accurate reproduction of vibrational energy transfer. Finally, CFD methodologies for simulating reflected shock tubes are proposed and validated through comparisons with analytical shock-tube theory and experimental data. These developments establish a unified computational framework for integrating inconsistent state-resolved kinetic datasets, data-driven modeling, and validated shock-tube simulations to enable predictive STS modeling of high-enthalpy nonequilibrium flows.