On the impact of dimensionally-consistent and physics-based inner products for POD-Galerkin and least-squares model reduction of compressible flows

TL;DR

This paper investigates the use of dimensionally-consistent, physics-based inner products in POD-Galerkin and least-squares model reduction of compressible flows, demonstrating improved robustness and accuracy over traditional L2 inner products.

Contribution

It introduces and evaluates physics-based, dimensionally-consistent inner products for ROMs of compressible Euler equations, enhancing model robustness and accuracy.

Findings

Physics-based inner products improve ROM robustness.

Non-dimensional inner products positively impact ROM performance.

Physics-based inner products outperform L2 inner products in test cases.

Abstract

Model reduction of the compressible Euler equations based on proper orthogonal decomposition (POD) and Galerkin orthogonality or least-squares residual minimization requires the selection of inner product spaces in which to perform projections and measure norms. The most popular choice is the vector-valued L2({\Omega}) inner product space. This choice, however, yields dimensionally-inconsistent reduced-order model (ROM) formulations which often lack robustness. In this work, we try to address this weakness by studying a set of dimensionally-consistent inner products with application to the compressible Euler equations. First, we demonstrate that non-dimensional inner products have a positive impact on both POD and Galerkin/least-squares ROMs. Second, we further demonstrate that physics-based inner products based on entropy principles result in drastically more accurate and robust ROM formulations than those based on non-dimensional L2({\Omega}) inner products.As test cases, we consider the following well-known problems: the one-dimensional Sod shock tube, the two-dimensional Kelvin-Helmholtz instability and two-dimensional homogeneous isotropic turbulence.