4.6 Article

Tail-equivalent linearization method for nonlinear random vibration

Journal

PROBABILISTIC ENGINEERING MECHANICS
Volume 22, Issue 1, Pages 63-76

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.probengmech.2006.08.001

Keywords

discretization; earthquake engineering; first-order approximation; first-passage probability; hysteresis; linearization; nonlinear problems; nonparametric methods; random vibrations; tail probability

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A new, non-parametric linearization method for nonlinear random vibration analysis is developed. The method employs a discrete representation of the stochastic excitation and concepts from the first-order reliability method, FORM. For a specified response threshold of the nonlinear system, the equivalent linear system is defined by matching the design points of the linear and nonlinear responses in the space of the standard normal random variables obtained from the discretization of the excitation. Due to this definition, the tail probability of the linear system is equal to the first-order approximation of the tail probability of the nonlinear system, this property motivating the name Tail-Equivalent Linearization Method (TELM). It is shown that the equivalent linear system is uniquely determined in terms of its impulse response function in a non-parametric form from the knowledge of the design point. The paper examines the influences of various parameters on the tail-equivalent linear system, presents an algorithm for finding the needed sequence of design points, and describes methods for determining various statistics of the nonlinear response, such as the probability distribution, the mean level-crossing rate and the first-passage probability. Applications to single- and multi-degree-of-freedom, non-degrading hysteretic systems illustrate various features of the method, and comparisons with results obtained by Monte Carlo simulations and by the conventional equivalent linearization method (ELM) demonstrate the superior accuracy of TELM over ELM, particularly for high response thresholds. (C) 2006 Elsevier Ltd. All rights reserved.

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