Sessa, Salvatore (2008) Application of the Tail-Equivalent Linearization Method for Stochastic Dynamic Analysis with Asymmetric Hysteresis. [Tesi di dottorato] (Unpublished)

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Item Type:	Tesi di dottorato
Lingua:	English
Title:	Application of the Tail-Equivalent Linearization Method for Stochastic Dynamic Analysis with Asymmetric Hysteresis
Creators:	Creators Email Sessa, Salvatore sal.sessa@gmail.com
Date:	30 November 2008
Number of Pages:	178
Institution:	Università degli Studi di Napoli Federico II
Department:	Ingegneria dei materiali e della produzione
Dottorato:	Ingegneria dei materiali e delle strutture
Ciclo di dottorato:	21
Coordinatore del Corso di dottorato:	nome email Acierno, Domenico UNSPECIFIED
Coordinatore del Corso di dottorato (extra):	nome email Prota, Andrea UNSPECIFIED
Tutor:	nome email Rosati, Luciano rosati@unina.it
Date:	30 November 2008
Number of Pages:	178
Uncontrolled Keywords:	Nonlinear Random Vibrations Analysis
Settori scientifico-disciplinari del MIUR:	Area 08 - Ingegneria civile e Architettura > ICAR/09 - Tecnica delle costruzioni Area 08 - Ingegneria civile e Architettura > ICAR/08 - Scienza delle costruzioni
Date Deposited:	13 Nov 2009 14:07
Last Modified:	09 Dec 2014 10:09
URI:	http://www.fedoa.unina.it/id/eprint/3329

Abstract

The tail-equivalent linearization method (TELM) is used to investigate the stationary response of a system having a highly asymmetric hysteretic behavior and subjected to a discretized white-noise excitation. The equivalent linear system is defined by equating its tail probability with the first-order approximation of the tail probability of the nonlinear response. The equivalent linear system is determined in a non-parametric form in terms of its impulse response function, which depends on the response threshold of interest. The method is able to capture the non-Gaussian and asymmetric distribution of both the point-in-time response and the extreme response over a time interval (the first-passage probability) for large thresholds (small exceedance probabilities), which are of interest in reliability analysis.

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