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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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Adaptive split/merge-based Gaussian mixture model approach for uncertainty propagation
Kumar Vishwajeet,Puneet Singla +1 more
TL;DR: This paper presents an adaptive splitting and merging scheme for dynamic selection of Gaussian kernels in a Gaussian mixture model and exploits the angle between eigenvectors corresponding to the maximum eigenvalue of covariance matrices corresponding to two differentGaussian kernels to find candidate components for merging.
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Non-linear dynamics of a stochastically excited beam system with impact
TL;DR: It is shown that including more modes to the model causes its response to differ significantly from that of a single-degree-of-freedom model, which can be used to accurately predict the stochastic response characteristics of the original, continuous, non-linear system.
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Optimal design of TVMD with linear and nonlinear viscous damping subjected to white‐noise excitation
Chen Huating,Ping Tan +1 more
Identification and initial characterization of sources of uncertainty affecting the performance of future trajectory management automation systems
TL;DR: An alternative stochastic formulation of the trajectory prediction problem is proposed that explicitly considers the sources of uncertainty affecting a 3 degrees-of-freedom point mass model of the aircraft motion, assumed to represent the aircraft model at the core of any trajectory predictor.
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Non-linear stochastic dynamics of systems with random properties: A spectral approach combined with statistical linearization
H. Grundmann,Holger Waubke +1 more
TL;DR: In this paper, the random properties of a random linear system are described by a Karhunen-Loeve-expansion, and for the response of a linear system with random properties subjected to a stochastic loading a spectral approach introducing Hermitian polynomials for the random response quantities is used according to a proposal of Ghanem and Spanos.