State-dependent convergence of Galerkin-based reduced-order models for Couette flow
Zilin Zong, Igor Maia, Andr\'e Cavalieri, Yongyun Hwang

TL;DR
This paper investigates how the choice of basis functions affects the convergence and performance of Galerkin-based reduced-order models in Couette flow, revealing that effectiveness depends on the flow state and basis function type.
Contribution
It demonstrates the state-dependent performance of ROMs using different basis functions, linking basis choice to flow regime and dynamics captured.
Findings
LNSE-based modes excel near laminar states
POD modes best reproduce turbulent statistics
Eddy viscosity models improve LNSE-based ROMs
Abstract
In this study, we explore the effect of basis functions on the performance and convergence of the Galerkin projection-based reduced-order model (ROM) in the minimal flow unit of Couette flow. POD (proper orthogonal decomposition) modes obtained from direct numerical simulation and controllability and balanced truncation modes from the linearised Navier-Stokes equations (LNSE) with different base flows (laminar base flow and turbulent mean flow) and an eddy viscosity model are considered. In the neighbourhood of the laminar base state, the ROMs based on the modes from the LNSE with the laminar base flow and molecular viscosity are found to perform very well as they are able to capture the linear stability of the laminar base flow for each plane Fourier component only with a single degree of freedom. In particular, the ROM based on the balanced truncation modes models the linear dynamics…
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