article Open AccessTop 1% cited
Modal Analysis of Fluid Flows: Applications and Outlook
AIAA Journal · 2019 · Vol. 58(3) · pp. 998–1022
Kunihiko Taira✉(University of California, Los Angeles)Maziar S. Hemati(University of Minnesota)Steven L. Brunton(University of Washington)Yiyang Sun(University of Minnesota)Karthik Duraisamy(University of Michigan–Ann Arbor)Shervin Bagheri(KTH Royal Institute of Technology)Scott T. M. Dawson(Illinois Institute of Technology)C. Yeh(University of California, Los Angeles)
Model Reduction and Neural NetworksFluid Dynamics and Vibration AnalysisFluid Dynamics and Turbulent FlowsModal analysisComputational fluid dynamicsModalFluid dynamicsMechanicsComputer scienceGeologyFinite element methodPhysicsEngineering
Funding
- National Science Foundation
- Defense Advanced Research Projects Agency
- Office of Naval Research
- Air Force Office of Scientific Research
- Army Research Office
Citations
598
FWCI
34.41
field-weighted impact
References
288
Percentile
100%
vs. same field & year
Citations per year
References
Evaluation of machine learning algorithms for prediction of regions of high Reynolds averaged Navier Stokes uncertainty
Physics of Fluids · 2015 · 395 citations
Dynamic mode decomposition of numerical and experimental data
Journal of Fluid Mechanics · 2010 · 5,551 citations
Nonlinear Dimensionality Reduction by Locally Linear Embedding
Science · 2000 · 14,934 citations
Principal component analysis in linear systems: Controllability, observability, and model reduction
IEEE Transactions on Automatic Control · 1981 · 5,242 citations
Interpolation Method for Adapting Reduced-Order Models and Application to Aeroelasticity
AIAA Journal · 2008 · 665 citations
The three-dimensional nature of boundary-layer instability
Journal of Fluid Mechanics · 1962 · 1,091 citations
Experiments on the flow past a circular cylinder at very high Reynolds number
Journal of Fluid Mechanics · 1961 · 1,317 citations
Multilayer feedforward networks are universal approximators
Neural Networks · 1989 · 20,841 citations
Citation Network
How this paper connects to the literature. Drag to explore, click any node to open that paper.
