Model-Order Reduction For Hyperbolic Relaxation Systems

2021/04/30 by Sara Grundel, Grundel, Sara, Michaël Herty +1
Mathematics · Physics and Astronomy · Engineering · #Numerical methods for differential equations #Model Reduction and Neural Networks #Computational Fluid Dynamics and Aerodynamics

paper · pdf · doi:10.48550/arxiv.2104.14823

Abstract

We propose a novel framework for model-order reduction of hyperbolic differential equations. The approach combines a relaxation formulation of the hyperbolic equations with a discretization using shifted base functions. Model-order reduction techniques are then applied to the resulting system of coupled ordinary differential equations. On computational examples including in particular the case of shock waves we show the validity of the approach and the performance of the reduced system.

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