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Reduced-order kinetic plasma models using principal component analysis: Model formulation and manifold sensitivity

Aurélie Bellemans* and Thierry Magin†

Axel Coussement‡ and Alessandro Parente§

  • Aeronautics and Aerospace Department, von Karman Institute for Fluid Dynamics, 72 Chaussée de Waterloo, 1640 Rhode-Saint-Genèse, Belgium

  • Service d'Aéro-Thermo-Mécanique, Université libre de Bruxelles, 50 avenue F.D. Roosevelt, 1050 Bruxelles, Belgium

  • *Present address: ATM, Université libre de Bruxelles; aurelie.bellemans@vki.ac.be
  • †thierry.magin@vki.ac.be
  • ‡axel.coussement@ulb.ac.be
  • §alessandro.parente@ulb.ac.be
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Phys. Rev. Fluids 2, 073201 – Published 24 July, 2017

DOI: https://doi.org/10.1103/PhysRevFluids.2.073201

Abstract

Plasma flows involve hundreds of species and thousands of reactions at different time scales, resulting in a very large set of governing equations to solve. Simulating large reacting systems in nonequilibrium plasma mixtures remains a challenge with the currently available computational resources. Principal component analysis (PCA) offers a general and rather simple and automated method to reduce large kinetic mechanisms by principal variable selection. This work shows how to adapt and apply the PCA-scores technique, which has its origin in the combustion field, to a collisional-radiative model. We have successfully applied this technique to argon plasmas, reducing the set of governing equations by more than 90%, leading to an important speed-up of the calculation and a reduction of computational cost.

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Phys. Rev. Fluids 2, 073201– Published 24 July, 2017
  • Received 31 January 2017

©2017 American Physical Society

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