Petrov-Galerkin model reduction for collisional-radiative argon plasma
Ivan Zanardi, Alessandro Meini, Alberto Padovan, Daniel J. Bodony, Marco Panesi

TL;DR
This paper introduces a Petrov-Galerkin reduced-order model for collisional-radiative argon plasma that significantly reduces computational costs while accurately capturing complex plasma dynamics in high-speed flow simulations.
Contribution
The paper develops a novel Petrov-Galerkin ROM that balances state trajectories and sensitivities, enabling efficient and accurate simulation of nonequilibrium plasmas.
Findings
3x reduction in state dimension
Over 10x decrease in computational effort
Errors below 1% in key quantities
Abstract
High-fidelity simulation of nonequilibrium plasmas -- crucial to applications in electric propulsion, hypersonic re-entry, and astrophysical flows -- requires state-specific collisional-radiative (CR) kinetic models, but these come at a prohibitive computational cost. Traditionally, this cost has been mitigated through empirical or physics-based simplifications of the governing equations. However, such approaches often fail to retain the essential features of the original dynamics, particularly under strong nonequilibrium conditions. To address these limitations, we develop a Petrov-Galerkin reduced-order model (ROM) for CR argon plasma based on oblique projections that optimally balance the covariance of full-order state trajectories with that of the system's output sensitivities. This construction ensures that the ROM captures both the dominant energetic modes and the directions most…
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Taxonomy
TopicsModel Reduction and Neural Networks · Gas Dynamics and Kinetic Theory · Computational Fluid Dynamics and Aerodynamics
