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Machine Learning Control – Taming Nonlinear Dynamics and Turbulence
This is the first textbook on a generally applicable control strategy for turbulence and other complex nonlinear systems. The approach of the book employs powerful methods of machine learning for optimal nonlinear control laws. This machine learning control (MLC) is motivated and detailed in Chapters 1 and 2. In Chapter 3, methods of linear control theory are reviewed. In Chapter 4, MLC is shown to reproduce known optimal control laws for linear dynamics (LQR, LQG). In Chapter 5, MLC detects and exploits a strongly nonlinear actuation mechanism of a low-dimensional dynamical system when linear control methods are shown to fail. Experimental control demonstrations from a laminar shear-layer t...
Reduced-Order Modelling for Flow Control
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.
Data-Driven Science and Engineering
A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.
Data-Driven Fluid Mechanics
Data-driven methods have become an essential part of the methodological portfolio of fluid dynamicists, motivating students and practitioners to gather practical knowledge from a diverse range of disciplines. These fields include computer science, statistics, optimization, signal processing, pattern recognition, nonlinear dynamics, and control. Fluid mechanics is historically a big data field and offers a fertile ground for developing and applying data-driven methods, while also providing valuable shortcuts, constraints, and interpretations based on its powerful connections to basic physics. Thus, hybrid approaches that leverage both methods based on data as well as fundamental principles are the focus of active and exciting research. Originating from a one-week lecture series course by the von Karman Institute for Fluid Dynamics, this book presents an overview and a pedagogical treatment of some of the data-driven and machine learning tools that are leading research advancements in model-order reduction, system identification, flow control, and data-driven turbulence closures.
Active Flow Control II
The interest in the field of active flow control (AFC) is steadily increasing. In - cent years the number of conferences and special sessions devoted to AFC org- ized by various institutions around the world continuously rises. New advanced courses for AFC are offered by the American Institute of Aeronautics and Ast- nautics (AIAA), the European Research Community on Flow, Turbulence and Combustion (ERCOFTAC), the International Centre for Mechanical Sciences (CISM), the von Karman Institute for Fluid Dynamics (VKI), to name just a few. New books on AFC are published by prominent colleagues of our field and even a new periodical, the ‘International Journal of Flow Control’, appeared. Desp...
Fluid-Structure-Sound Interactions and Control
This book presents the proceedings of the Symposium on Fluid-Structure-Sound Interactions and Control (FSSIC), (held in Tokyo on Aug. 21-24, 2017), which largely focused on advances in the theory, experiments on, and numerical simulation of turbulence in the contexts of flow-induced vibration, noise and their control. This includes several practical areas of application, such as the aerodynamics of road and space vehicles, marine and civil engineering, nuclear reactors and biomedical science, etc. Uniquely, these proceedings integrate acoustics with the study of flow-induced vibration, which is not a common practice but can be extremely beneficial to understanding, simulating and controlling vibration. The symposium provides a vital forum where academics, scientists and engineers working in all related branches can exchange and share their latest findings, ideas and innovations – bringing together researchers from both east and west to chart the frontiers of FSSIC.
Numerical Simulation of Turbulent Flows and Noise Generation
Large Eddy Simulation (LES) is a high-fidelity approach to the numerical simulation of turbulent flows. Recent developments have shown LES to be able to predict aerodynamic noise generation and propagation as well as the turbulent flow, by means of either a hybrid or a direct approach. This book is based on the results of two French/German research groups working on LES simulations in complex geometries and noise generation in turbulent flows. The results provide insights into modern prediction approaches for turbulent flows and noise generation mechanisms as well as their use for novel noise reduction concepts.
Mechanics of the 21st Century
"This volume ... consists of a book with full texts of invited talks and attached CD-ROM with Extended Summaries of 1225 papers presented during the Congress"--p. x.
Fluids Under Control
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