Journal Article10.1016/J.PROBENGMECH.2006.08.001
Tail equivalent linearization method for nonlinear random vibration
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TL;DR: The Tail-Equivalent Linearization Method (TELM) as discussed by the authors is a non-parametric linearization method for nonlinear random vibration analysis, which employs a discrete representation of the stochastic excitation and concepts from the first-order reliability method, FORM.
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About: This article is published in Probabilistic Engineering Mechanics. The article was published on 01 Jan 2007. The article focuses on the topics: Linearization & Feedback linearization.
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Citations
A stochastic ground motion model with separable temporal and spectral nonstationarities
TL;DR: A fully nonstationary stochastic model for strong earthquake ground motion is developed, employing filtering of a discretized white-noise process that has the important advantage of separating the temporal and spectral non stationary characteristics of the process, thereby allowing flexibility and ease in modeling and parameter estimation.
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A review and assessment of importance sampling methods for reliability analysis
TL;DR: In this paper , the authors discuss the mathematical foundation of the importance sampling technique and discuss two general classes of methods to construct the importance sample density (or probability measure) for reliability analysis, and explore the performances of the two classes of importance sampling methods through several benchmark numerical examples.
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The role of the design point for calculating failure probabilities in view of dimensionality and structural nonlinearities
TL;DR: In this paper, the authors present a collection of observations on the performance of different methods for assessing structural reliability in view of dimensionality and structural nonlinearities and assess the role of the design point in approximate reliability methods and the range of applicability of these methods.
130
Cross-entropy-based adaptive importance sampling using von Mises-Fisher mixture for high dimensional reliability analysis
Ziqi Wang,Junho Song +1 more
TL;DR: In this paper, a cross-entropy-based adaptive importance sampling technique that employs a von Mises-Fisher mixture as the sampling density model was proposed to address challenges in performing importance sampling in a high dimensional space of random variables.
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Simulation of orthogonal horizontal ground motion components for specified earthquake and site characteristics
TL;DR: In this article, a method for generating an ensemble of orthogonal horizontal ground motion components with correlated parameters for specified earthquake and site characteristics is presented, which employs a parameterized stochastic model that is based on a time-modulated filtered white-noise process with the filter having time-varying characteristics.
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References
Incremental dynamic analysis
TL;DR: Incremental dynamic analysis (IDA) is a parametric analysis method that has recently emerged in several different forms to estimate more thoroughly structural performance under seismic loads as mentioned in this paper, which involves subjecting a structural model to one or more ground motion record(s), each scaled to multiple levels of intensity, thus producing one (or more) curve(s) of response parameterized versus intensity level.
Method for Random Vibration of Hysteretic Systems
TL;DR: In this paper, a new method of modeling and solution of a large class of hysteretic systems (softening or hardening, narrow or wideband) under random excitation is proposed.
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Structural Reliability Methods
Ove Ditlevsen,H. O. Madsen +1 more
- 01 Jun 1996
TL;DR: Partial Safety Factor Method Probabilistic Information Simple Reliability Index Geometricreliability Index Generalized Reliability index Transformation Sensitivity Analysis Monte Carlo Methods Load Combinations Statistical and Model Uncertainty Decision Philosophy Reliability of Existing Structures System Reliability Analysis.
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Random vibration and statistical linearization
J.B. Roberts,Pol D. Spanos +1 more
- 01 Jan 1990
TL;DR: 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.
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