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Random vibration and statistical linearization
J.B. Roberts,Pol D. Spanos +1 more
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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.read more
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Stochastic Approach for Analytical Fragility Curves
TL;DR: In this paper, the authors focused on an analytical method for constructing fragility curves of existing structures based on a stochastic approach, which describes the probability of a structure to suffer a given damage level when it is subject to a given seismic excitation level.
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Dual Faceted Linearization of Nonlinear Dynamical Systems Based on Physical Modeling Theory
TL;DR: In this paper, NSF, Science and Technology Center - STC & Emergent Behaviors in Integrated Cellular Systems (EBICS) grant CBET-0939511 was used to support the development of an integrated cellular system.
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Efficient response determination of a M-D-O-F gear model subject to combined periodic and stochastic excitations
TL;DR: In this article, the nonlinear response of a multi-degree-of-freedom (M-D-O-F) gear model subject to combined periodic and stochastic excitations is investigated by an efficient linearization scheme, accounting for the time-variant stiffness, and the backlash feature involved in the model.
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Spectral identification of nonlinear multi-degree-of-freedom structural systems with fractional derivative terms based on incomplete non-stationary data
TL;DR: In this article, a spectral identification technique is developed for determining the parameters of nonlinear and time-variant multi-degree-of-freedom (MDOF) structural systems based on available input-output (excitation-response) realizations.
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Variations in steepness of the probability density function of beam random vibration
TL;DR: In this article, the non-Gaussian kurtosis parameter of the beam response was analyzed and approximated making use of different theoretical models, and a numerical procedure for prediction of the nonlinear random response of a clamped-clamped beam under the Gaussian excitations was based on a linear modal expansion.