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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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Derivation of response spectrum compatible non-stationary stochastic processes relying on Monte Carlo-based peak factor estimation

TL;DR: In this paper, the problem of deriving non-stationary stochastic processes which are compatible with a given (target) response (uniform hazard) spectrum (UHS) as commonly desired in the aseismic structural design regulated by contemporary codes of practice is addressed by solving a standard over-determined minimization problem in conjunction with appropriate median peak factors.
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Random uncertainties model in dynamic substructuring using a nonparametric probabilistic model

TL;DR: In this paper, a nonparametric model of random uncertainties is proposed for dynamic substructuring, which does not require identifying uncertain parameters in the reduced matrix model of each substructure as is usually done for the parametric approach.
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On the cumulant-neglect closure method in stochastic dynamics

TL;DR: In this paper, an algorithm was developed and presented for the efficient and automated generation of the moment equations for dynamical systems with an arbitrary number of states and closed at an arbitrary level (limited only by available computational resources).
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POMs analysis of randomly vibrating systems obtained from Karhunen–Loève expansion

TL;DR: In this article, the proper orthogonal decomposition (POD) method is applied to the responses of randomly excited vibrating systems with a view to performing a POD in separated-variables (time and space) form.
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Response of nonlinear single-degree-of-freedom structures to random acceleration sequences

TL;DR: In this article, a simple stochastic model for representing repeated acceleration sequences is proposed, which is used in investigating the response of nonlinear single-degree-of-freedom (SDOF) structures to random earthquakes of repeated sequences.