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 flowfield, 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 1–8.
%0 Journal Article
%1 taira2017modal
%A Taira, Kunihiko
%A Brunton, Steven L.
%A Dawson, Scott T. M.
%A Rowley, Clarence W.
%A Colonius, Tim
%A McKeon, Beverley J.
%A Schmidt, Oliver T.
%A Gordeyev, Stanislav
%A Theofilis, Vassilios
%A Ukeiley, Lawrence S.
%D 2017
%I American Institute of Aeronautics and Astronautics (AIAA)
%J AIAA Journal
%K 76e09-stability-and-instability-of-nonparallel-flows 76e30-hydrodynamic-stability-nonlinear-effects
%N 12
%P 4013--4041
%R 10.2514/1.j056060
%T Modal Analysis of Fluid Flows: An Overview
%U https://arc.aiaa.org/doi/10.2514/1.J056060
%V 55
%X 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 flowfield, 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 1–8.
@article{taira2017modal,
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 flowfield, 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 [1–8].},
added-at = {2020-08-19T01:47:48.000+0200},
author = {Taira, Kunihiko and Brunton, Steven L. and Dawson, Scott T. M. and Rowley, Clarence W. and Colonius, Tim and McKeon, Beverley J. and Schmidt, Oliver T. and Gordeyev, Stanislav and Theofilis, Vassilios and Ukeiley, Lawrence S.},
biburl = {https://www.bibsonomy.org/bibtex/2a96d373994d05e2ab92b4f29c89fbc2c/gdmcbain},
doi = {10.2514/1.j056060},
interhash = {fc5f57b90cb3f06a2186029a755001d7},
intrahash = {a96d373994d05e2ab92b4f29c89fbc2c},
journal = {{AIAA} Journal},
keywords = {76e09-stability-and-instability-of-nonparallel-flows 76e30-hydrodynamic-stability-nonlinear-effects},
month = dec,
number = 12,
pages = {4013--4041},
publisher = {American Institute of Aeronautics and Astronautics ({AIAA})},
timestamp = {2020-09-02T02:32:24.000+0200},
title = {Modal Analysis of Fluid Flows: An Overview},
url = {https://arc.aiaa.org/doi/10.2514/1.J056060},
volume = 55,
year = 2017
}