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Author: Miguel A. Mendez
Publisher: Cambridge University Press
Published: 2023-01-31
Total Pages: 469
ISBN-13: 1108842143
DOWNLOAD EBOOK →This is the first book dedicated to data-driven methods for fluid dynamics, with applications in analysis, modeling, control, and closures.
Author: Steven L. Brunton
Publisher: Cambridge University Press
Published: 2022-05-05
Total Pages: 615
ISBN-13: 1009098489
DOWNLOAD EBOOK →A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.
Author: Stefano Discetti
Publisher: CRC Press
Published: 2017-03-16
Total Pages: 454
ISBN-13: 1498704026
DOWNLOAD EBOOK →Experimental Aerodynamics provides an up to date study of this key area of aeronautical engineering. The field has undergone significant evolution with the development of 3D techniques, data processing methods, and the conjugation of simultaneous measurements of multiple quantities. Written for undergraduate and graduate students in Aerospace Engineering, the text features chapters by leading experts, with a consistent structure, level, and pedagogical approach. Fundamentals of measurements and recent research developments are introduced, supported by numerous examples, illustrations, and problems. The text will also be of interest to those studying mechanical systems, such as wind turbines.
Author: Thomas Duriez
Publisher: Springer
Published: 2016-11-02
Total Pages: 211
ISBN-13: 3319406248
DOWNLOAD EBOOK →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 to turbulent boundary-layers are reviewed in Chapter 6, followed by general good practices for experiments in Chapter 7. The book concludes with an outlook on the vast future applications of MLC in Chapter 8. Matlab codes are provided for easy reproducibility of the presented results. The book includes interviews with leading researchers in turbulence control (S. Bagheri, B. Batten, M. Glauser, D. Williams) and machine learning (M. Schoenauer) for a broader perspective. All chapters have exercises and supplemental videos will be available through YouTube.
Author: J. Nathan Kutz
Publisher: SIAM
Published: 2016-11-23
Total Pages: 241
ISBN-13: 1611974496
DOWNLOAD EBOOK →Data-driven dynamical systems is a burgeoning field?it connects how measurements of nonlinear dynamical systems and/or complex systems can be used with well-established methods in dynamical systems theory. This is a critically important new direction because the governing equations of many problems under consideration by practitioners in various scientific fields are not typically known. Thus, using data alone to help derive, in an optimal sense, the best dynamical system representation of a given application allows for important new insights. The recently developed dynamic mode decomposition (DMD) is an innovative tool for integrating data with dynamical systems theory. The DMD has deep connections with traditional dynamical systems theory and many recent innovations in compressed sensing and machine learning. Dynamic Mode Decomposition: Data-Driven Modeling of Complex Systems, the first book to address the DMD algorithm, presents a pedagogical and comprehensive approach to all aspects of DMD currently developed or under development; blends theoretical development, example codes, and applications to showcase the theory and its many innovations and uses; highlights the numerous innovations around the DMD algorithm and demonstrates its efficacy using example problems from engineering and the physical and biological sciences; and provides extensive MATLAB code, data for intuitive examples of key methods, and graphical presentations.
Author: J. Nathan Kutz
Publisher: Oxford University Press
Published: 2013-08-08
Total Pages: 657
ISBN-13: 0199660336
DOWNLOAD EBOOK →Combining scientific computing methods and algorithms with modern data analysis techniques, including basic applications of compressive sensing and machine learning, this book develops techniques that allow for the integration of the dynamics of complex systems and big data. MATLAB is used throughout for mathematical solution strategies.
Author: Werner Heisenberg
Publisher: CUP Archive
Published: 1949
Total Pages: 64
ISBN-13:
DOWNLOAD EBOOK →Author: Brian J. Kirby
Publisher: Cambridge University Press
Published: 2010-07-26
Total Pages: 536
ISBN-13: 1139489836
DOWNLOAD EBOOK →This text focuses on the physics of fluid transport in micro- and nanofabricated liquid-phase systems, with consideration of gas bubbles, solid particles, and macromolecules. This text was designed with the goal of bringing together several areas that are often taught separately - namely, fluid mechanics, electrodynamics, and interfacial chemistry and electrochemistry - with a focused goal of preparing the modern microfluidics researcher to analyse and model continuum fluid mechanical systems encountered when working with micro- and nanofabricated devices. This text serves as a useful reference for practising researchers but is designed primarily for classroom instruction. Worked sample problems are included throughout to assist the student, and exercises at the end of each chapter help facilitate class learning.
Author: Andrew Pollard
Publisher: Springer
Published: 2016-08-30
Total Pages: 574
ISBN-13: 3319412175
DOWNLOAD EBOOK →This volume provides a snapshot of the current and future trends in turbulence research across a range of disciplines. It provides an overview of the key challenges that face scientific and engineering communities in the context of huge databases of turbulence information currently being generated, yet poorly mined. These challenges include coherent structures and their control, wall turbulence and control, multi-scale turbulence, the impact of turbulence on energy generation and turbulence data manipulation strategies. The motivation for this volume is to assist the reader to make physical sense of these data deluges so as to inform both the research community as well as to advance practical outcomes from what is learned. Outcomes presented in this collection provide industry with information that impacts their activities, such as minimizing impact of wind farms, opportunities for understanding large scale wind events and large eddy simulation of the hydrodynamics of bays and lakes thereby increasing energy efficiencies, and minimizing emissions and noise from jet engines. Elucidates established, contemporary, and novel aspects of fluid turbulence - a ubiquitous yet poorly understood phenomena; Explores computer simulation of turbulence in the context of the emerging, unprecedented profusion of experimental data,which will need to be stewarded and archived; Examines a compendium of problems and issues that investigators can use to help formulate new promising research ideas; Makes the case for why funding agencies and scientists around the world need to lead a global effort to establish and steward large stores of turbulence data, rather than leaving them to individual researchers.
