BookDOI
Reduced-Order Modelling for Flow Control
Bernd R. Noack,Marek Morzyński,Gilead Tadmor +2 more
- Vol. 528
TLDR
Covered areas include optimization techniques, stability analysis, nonlinear reduced-order modelling, model-based control design as well as model-free and neural network approaches.Abstract:
The book focuses on the physical and mathematical foundations of model-based turbulence control: reduced-order modelling and control design in simulations and experiments. Leading experts provide elementary self-consistent descriptions of the main methods and outline the state of the art. Covered areas include optimization techniques, stability analysis, nonlinear reduced-order modelling, model-based control design as well as model-free and neural network approaches. The wake stabilization serves as unifying benchmark control problem.read more
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Journal ArticleDOI
Modal Analysis of Fluid Flows: An Overview
Kunihiko Taira,Steven L. Brunton,Scott T. M. Dawson,Clarence W. Rowley,Tim Colonius,Beverley McKeon,Oliver T. Schmidt,Stanislav Gordeyev,Vassilios Theofilis,Lawrence Ukeiley +9 more
TL;DR: The intent of this document is to provide an introduction to modal analysis that is accessible to the larger fluid dynamics community and presents a brief overview of several of the well-established techniques.
Journal ArticleDOI
Digital Twin: Values, Challenges and Enablers From a Modeling Perspective
TL;DR: This work reviews the recent status of methodologies and techniques related to the construction of digital twins mostly from a modeling perspective to provide a detailed coverage of the current challenges and enabling technologies along with recommendations and reflections for various stakeholders.
Book
Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control
Steven L. Brunton,J. Nathan Kutz +1 more
TL;DR: In this paper, the authors bring together machine learning, engineering mathematics, and mathematical physics to integrate modeling and control of dynamical systems with modern methods in data science, and highlight many of the recent advances in scientific computing that enable data-driven methods to be applied to a diverse range of complex systems, such as turbulence, the brain, climate, epidemiology, finance, robotics, and autonomy.
Journal ArticleDOI
Wave Packets and Turbulent Jet Noise
Peter Jordan,Tim Colonius +1 more
TL;DR: In this paper, the authors review evidence of the existence, energetics, dynamics, and acoustic efficiency of wave packets and highlight how extensive data available from simulations and modern measurement techniques can be used to distill acoustically relevant turbulent motions.
Journal ArticleDOI
Closed-Loop Turbulence Control: Progress and Challenges
Steven L. Brunton,Bernd R. Noack +1 more