Modal Analysis of Fluid Flows: An Overview
Kunihiko Taira, Steven L. Brunton, Scott T. M. Dawson, Clarence W., Rowley, Tim Colonius, Beverley J. McKeon, Oliver T. Schmidt, Stanislav, Gordeyev, Vassilios Theofilis, Lawrence S. Ukeiley

TL;DR
This paper provides an accessible overview of key modal analysis techniques used in fluid dynamics, including POD, DMD, Koopman, and stability analysis, highlighting their recent developments and applications.
Contribution
It offers a clear introduction to various modal decomposition methods, framing them with familiar linear algebra concepts for the fluid dynamics community.
Findings
Summarizes dominant modal analysis techniques in fluid flows.
Highlights recent advancements in modal decomposition methods.
Provides a unified framework for understanding these techniques.
Abstract
Simple aerodynamic configurations under even modest conditions can exhibit complex flows with a wide range of temporal and spatial features. It has become common practice in the analysis of these flows to look for and extract physically important features, or modes, as a first step in the analysis. This step typically starts with a modal decomposition of an experimental or numerical dataset of the flow field, or of an operator relevant to the system. We describe herein some of the dominant techniques for accomplishing these modal decompositions and analyses that have seen a surge of activity in recent decades. For a non-expert, keeping track of recent developments can be daunting, and the intent of this document is to provide an introduction to modal analysis that is accessible to the larger fluid dynamics community. In particular, we present a brief overview of several of the…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsModel Reduction and Neural Networks · Fluid Dynamics and Vibration Analysis · Fluid Dynamics and Turbulent Flows
