Data-Driven Science and Engineering

Data-Driven Science and Engineering

Author: Steven L. Brunton

Publisher: Cambridge University Press

Published: 2022-05-05

Total Pages: 615

ISBN-13: 1009098489

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A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.


Linearization Methods for Stochastic Dynamic Systems

Linearization Methods for Stochastic Dynamic Systems

Author: Leslaw Socha

Publisher: Springer Science & Business Media

Published: 2007-12-20

Total Pages: 392

ISBN-13: 3540729968

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For most cases of interest, exact solutions to nonlinear equations describing stochastic dynamical systems are not available. This book details the relatively simple and popular linearization techniques available, covering theory as well as application. It examines models with continuous external and parametric excitations, those that cover the majority of known approaches.


Dramatic Effect of Cross-Correlations in Random Vibrations of Discrete Systems, Beams, Plates, and Shells

Dramatic Effect of Cross-Correlations in Random Vibrations of Discrete Systems, Beams, Plates, and Shells

Author: Isaac Elishakoff

Publisher: Springer Nature

Published: 2020-04-11

Total Pages: 356

ISBN-13: 3030403947

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This volume explains the dramatic effect of cross-correlations in forming the structural response of aircraft in turbulent excitation, ships in rough seas, cars on irregular roads, and other dynamic regimes. It brings into sharp focus the dramatic effect of cross correlations often neglected due to the analytical difficulty of their evaluation. Veteran author Professor Isaac Elishakoff illustrates how neglect of cross correlations could result in underestimation of the response by tens or hundreds of percentages the effect of the random vibrations of structures’ main elements, including beams, plates, and shells.


Nonstationary Systems: Theory and Applications

Nonstationary Systems: Theory and Applications

Author: Fakher Chaari

Publisher: Springer Nature

Published: 2021-07-21

Total Pages: 439

ISBN-13: 3030821102

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This book offers an overview of current and recent methods for the analysis of the nonstationary processes, focusing on cyclostationary systems that are ubiquitous in various application fields. Based on the 13th Workshop on Nonstationary Systems and Their Applications, held on February 3-5, 2020, in Grodek nad Dunajcem, Poland, the book merges theoretical contributions describing new statistical and intelligent methods for analyzing nonstationary processes, and applied works showing how the proposed methods can be implemented in practice and do perform in real-world case studies. A significant part of the book is dedicated to nonstationary systems applications, with a special emphasis on those in condition monitoring.


Non-Gaussian Random Vibration Fatigue Analysis and Accelerated Test

Non-Gaussian Random Vibration Fatigue Analysis and Accelerated Test

Author: Yu Jiang

Publisher: Springer Nature

Published: 2021-09-15

Total Pages: 171

ISBN-13: 981163694X

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This book discusses the theory, method and application of non-Gaussian random vibration fatigue analysis and test. The main contents include statistical analysis method of non-Gaussian random vibration, modeling and simulation of non-Gaussian/non-stationary random vibration, response analysis under non-Gaussian base excitation, non-Gaussian random vibration fatigue life analysis, fatigue reliability evaluation of structural components under Gaussian/non-Gaussian random loadings, non-Gaussian random vibration accelerated test method and application cases. From this book, the readers can not only learn how to reproduce the non-Gaussian vibration environment actually experienced by the product, but also know how to evaluate the fatigue life and reliability of the structure under non-Gaussian random excitation.


Identification of Dynamic Systems

Identification of Dynamic Systems

Author: Rolf Isermann

Publisher: Springer

Published: 2011-04-08

Total Pages: 705

ISBN-13: 9783540871552

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Precise dynamic models of processes are required for many applications, ranging from control engineering to the natural sciences and economics. Frequently, such precise models cannot be derived using theoretical considerations alone. Therefore, they must be determined experimentally. This book treats the determination of dynamic models based on measurements taken at the process, which is known as system identification or process identification. Both offline and online methods are presented, i.e. methods that post-process the measured data as well as methods that provide models during the measurement. The book is theory-oriented and application-oriented and most methods covered have been used successfully in practical applications for many different processes. Illustrative examples in this book with real measured data range from hydraulic and electric actuators up to combustion engines. Real experimental data is also provided on the Springer webpage, allowing readers to gather their first experience with the methods presented in this book. Among others, the book covers the following subjects: determination of the non-parametric frequency response, (fast) Fourier transform, correlation analysis, parameter estimation with a focus on the method of Least Squares and modifications, identification of time-variant processes, identification in closed-loop, identification of continuous time processes, and subspace methods. Some methods for nonlinear system identification are also considered, such as the Extended Kalman filter and neural networks. The different methods are compared by using a real three-mass oscillator process, a model of a drive train. For many identification methods, hints for the practical implementation and application are provided. The book is intended to meet the needs of students and practicing engineers working in research and development, design and manufacturing.