DSMC and Beyond: Modeling Nonequilibrium Flow in Aerospace Application- Eunji Jun Ph.D.
Eunji Jun is an associate professor in the Department of Aerospace Engineering at KAIST, South Korea. Her research focuses on rarefied gas dynamics, kinetic theory, and plasma dynamics, with an emphasis on particle-based modeling methods for aerospace applications. She received her Ph.D. in 2012 from the University of Michigan, where she conducted research in the Nonequilibrium Gas and Plasma Dynamics Laboratory (NGPDL) under the supervision of Prof. Iain D. Boyd. Prior to joining KAIST, she held research positions at the University of Hawaii, University of Edinburgh, DLR, and the University of Michigan.
Quantum Mechanics To Aerothermodynamics: A High-Fidelity Approach for Reactive Flows
Maninder S. Grover NASA Johnson Space Center, Houston, TX 77058
Particle-based methods such as Direct Simulation Monte Carlo (DSMC) technique present a powerful framework for simulating rarefied gas flows by explicitly modeling molecular collisions. Traditionally, these methods have relied on semi-empirical models or experimental data to define collision dynamics. However, with recent advances in quantum mechanical modeling of interatomic and intermolecular interactions, DSMC can now directly incorporate fundamental physics into flow field simulations. This allows for high-fidelity modeling grounded purely in first-principles data, eliminating the need for empirical inputs. Simulations using scattering trajectory integration within the DSMC framework are called Direct Molecular Simulations (DMS) to distinguish them from DSMC simulations using stochastic collision models.
DMS provides a framework to study molecular level behavior predicted by ab initio interaction potentials. Such insights can be leveraged to improve on relaxation and reaction models currently used in DSMC and even Navier-Stokes Computational Fluid Dynamics (CFD). Additionally, macroscopic properties from these first principle simulations can be used to obtain collision cross sections, relaxation rates, and reaction rates over a wide range of temperatures, including extreme environments where experimental measurements are limited or unavailable. Such improvements to current simulations techniques can greatly increase confidence in predictive studies of thermochemically complex flows such as atmospheric reentry or combustive detonation. Advancements in computational infrastructure in combination with scalability of the underlying DSMC form as allowed for larger and complex DMS calculations. The latest iteration of such calculations are able to simulate near continuum fluid mechanics experiments. Providing an unbroken link between fluid mechanics and quantum mechanics. Such simulations can be used as reliable and well-defined benchmarks for lower fidelity models to verify their accuracy.
This course covers the implementation of DMS and its key applications. It explores molecular-level mechanisms captured by DMS calculations and their impact on macroscopic behavior. Finally, it demonstrates how insights from DMS can enhance the accuracy of lower-fidelity DSMC and CFD models.