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Random vibration and statistical linearization

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TLDR
In this paper, a comprehensive account of statistical linearization with related techniques allowing the solution of a very wide variety of practical non-linear random vibration problems is given, and the principal value of these methods is that they are readily generalized to deal with complex mechanical and structural systems and complex types of excitation such as earthquakes.
Abstract
Interest in the study of random vibration problems using the concepts of stochastic process theory has grown rapidly due to the need to design structures and machinery which can operate reliably when subjected to random loads, for example winds and earthquakes. This is the first comprehensive account of statistical linearization - powerful and versatile methods with related techniques allowing the solution of a very wide variety of practical non-linear random vibration problems. The principal value of these methods is that unlike other analytical methods, they are readily generalized to deal with complex mechanical and structural systems and complex types of excitation such as earthquakes.

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Proceedings ArticleDOI

Determination of non-stationary stochastic processes compatible with seismic response/design spectra

TL;DR: In this paper, the problem of deriving nonstationary stochastic processes defined by a parametric evolutionary power spectrum (EPS) compatible with a given (target) design spectrum is addressed.
Journal ArticleDOI

Convergence Analysis and Cost Estimate of an MLMC-HDG Method for Elliptic PDEs with Random Coefficients

Meng Li, +1 more
TL;DR: In this paper, the authors considered an hybridizable discontinuous Galerkin (HDG) method for discrete elliptic PDEs with random coefficients and obtained the error analysis under the assumption that a(ω,x) is uniformly bounded.
Journal ArticleDOI

Explicit expression of stationary response probability density for nonlinear stochastic systems

TL;DR: In this article, a novel method is proposed to identify the stationary response probability density for general nonlinear stochastic dynamical systems with polynomial nonlinearity and excited by Gaussian white noises, which explicitly includes system and excitation parameters.
Book ChapterDOI

Random Vibration – History and Overview

TL;DR: The history of the mathematical theory of random vibration started in 1905 with the publication by Einstein of his paper, “On the Movement of Small Particles Suspended in a Stationary Liquid Demanded by the Molecular Kinetic Theory of Heat.