E-Book, Englisch, 424 Seiten, E-Book
ISBN: 978-0-470-82425-2
Verlag: John Wiley & Sons
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)
Stochastic Dynamics of Structures presents techniques forresearchers and graduate students in a wide variety of engineeringfields: civil engineering, mechanical engineering, aerospace andaeronautics, marine and offshore engineering, ship engineering, andapplied mechanics. Practicing engineers will benefit from theconcise review of random vibration theory and the new methodsintroduced in the later chapters.
"The book is a valuable contribution to the continuingdevelopment of the field of stochastic structural dynamics,including the recent discoveries and developments by the authors ofthe probability density evolution method (PDEM) and itsapplications to the assessment of the dynamic reliability andcontrol of complex structures through the equivalent extreme-valuedistribution."
--A. H-S. Ang, NAE, Hon. Mem. ASCE, Research Professor,University of California, Irvine, USA
"The authors have made a concerted effort to present aresponsible and even holistic account of modern stochasticdynamics. Beyond the traditional concepts, they also discusstheoretical tools of recent currency such as the Karhunen-Loeveexpansion, evolutionary power spectra, etc. The theoreticaldevelopments are properly supplemented by examples from earthquake,wind, and ocean engineering. The book is integrated by alsocomprising several useful appendices, and an exhaustive list ofreferences; it will be an indispensable tool for students,researchers, and practitioners endeavoring in its thematicfield."
--Pol Spanos, NAE, Ryon Chair in Engineering, RiceUniversity, Houston, USA
Autoren/Hrsg.
Weitere Infos & Material
Foreword.
Preface.
1 Introduction.
1.1 Motivations and Historical Clues.
1.2 Contents of the Book.
2 Stochastic Processes and Random Fields.
2.1 Random Variables.
2.2 Stochastic Processes.
2.3 Random Fields.
2.4 Orthogonal Decomposition of Random Functions.
3 Stochastic Models of Dynamic Excitations.
3.1 General Expression of Stochastic Excitations.
3.2 Seismic Ground Motions.
3.3 Fluctuating Wind Speed in the Boundary Layer.
3.4 Wind Wave and Ocean Wave Spectrum.
3.5 Orthogonal Decomposition of Random Excitations.
4 Stochastic Structural Analysis.
4.1 Introductory Remarks.
4.2 Fundamentals of Deterministic Structural Analysis.
4.3 Random Simulation Method.
4.4 Perturbation Approach.
4.5 Orthogonal Expansion Theory.
5 Random Vibration Analysis.
5.1 Introduction.
5.2 Moment Functions of the Responses.
5.3 Power Spectral Density Analysis.
5.4 Pseudo-Excitation Method.
5.5 Statistical Linearization.
5.6 Fokker?Planck?Kolmogorov Equation.
6 Probability Density Evolution Analysis: Theory.
6.1 Introduction.
6.2 The Principle of Preservation of Probability.
6.3 Markovian Systems and State Space Description: Liouville andFokker?Planck?Kolmogorov Equations.
6.4 Dostupov?Pugachev Equation.
6.5 The Generalized Density Evolution Equation.
6.6 Solution of the Generalized Density Evolution Equation.
7 Probability Density Evolution Analysis: NumericalMethods.
7.1 Numerical Solution of First-Order Partial DifferentialEquation.
7.2 Representative Point Sets and Assigned Probabilities.
7.3 Strategy for Generating Basic Point Sets.
7.4 Density-Related Transformation.
7.5 Stochastic Response Analysis of Nonlinear MDOFStructures.
8 Dynamic Reliability of Structures.
8.1 Fundamentals of Structural Reliability Analysis.
8.2 Dynamic Reliability Analysis: First-Passage ProbabilityBased on Excursion Assumption.
8.3 Dynamic Reliability Analysis: Generalized Density EvolutionEquation-Based Approach.
8.4 Structural System Reliability.
9 Optimal Control of Stochastic Systems.
9.1 Introduction.
9.2 Optimal Control of Deterministic Systems.
9.3 Stochastic Optimal Control.
9.4 Reliability-Based Control of Structural Systems.
Appendix A: Dirac Delta Function.
A.1 Definition.
A.2 Integration and Differentiation.
A.3 Common Physical Backgrounds.
Appendix B: Orthogonal Polynomials.
B.1 Basic Concepts.
B.2 Common Orthogonal Polynomials.
Appendix C: Relationship between Power Spectral Density andRandom Fourier Spectrum.
C.1 Spectra via Sample Fourier Transform.
C.2 Spectra via One-sided Finite Fourier Transform.
Appendix D: Orthonormal Base Vectors.
Appendix E: Probability in a Hyperball.
E.1 The Case s is Even.
E.2 The Case s is Odd.
E.3 Monotonic Features of F(r, s).
Appendix F: Spectral Moments.
Appendix G: Generator Vectors in the Number TheoreticalMethod.
References and Bibliography.
Index.