A robust dynamic mode decomposition methodology for an airfoil undergoing transonic shock buffet

TL;DR

This paper develops a robust methodology for applying dynamic mode decomposition (DMD) to analyze transonic shock buffet flows, addressing sensitivities and pitfalls to improve accuracy and reliability.

Contribution

It introduces a modular framework for DMD, evaluates sensitivities to parameters, and provides practical guidelines for robust analysis of transonic buffet flows.

Findings

Identified sensitivities of DMD to parameters like POD rank and sampling rate.

Highlighted dangers of aliasing with low sampling rates.

Provided best practices for robust DMD application in transonic flows.

Abstract

Dynamic mode decomposition (DMD) is a data-driven technique widely used to analyze and model fluid problems including transonic buffet flows. Despite its strengths, DMD is known to suffer from sensitivities to the selected settings and the characteristics of the employed data. In this work, we closely examine the aforementioned sensitivities, identify possible pitfalls, and provide best practices to robustly perform DMD on a flow exhibiting transonic shock buffet. Specifically, we assess various DMD variants and test their sensitivity to the POD rank truncation and the sampling rate. A critical enabler to our analysis is a new presentation of the DMD algorithm as a modular framework consisting of five distinct steps. The tests also highlight the existing dangers of aliasing, when the sampling rate is too low. Finally, a list of practical recommendations and guidelines on how to accurately and robustly perform DMD on a transonic buffet flow is provided.