JOURNAL ARTICLE

Gaussian mixture–based equivalent linearization method (GM‐ELM) for fragility analysis of structures under nonstationary excitations

Sang‐ri YiZiqi WangJunho Song

Year: 2019 Journal:   Earthquake Engineering & Structural Dynamics Vol: 48 (10)Pages: 1195-1214   Publisher: Wiley

Abstract

Summary Gaussian mixture–based equivalent linearization method (GM‐ELM) is a recently developed stochastic dynamic analysis approach which approximates the random response of a nonlinear structure by collective responses of equivalent linear oscillators. The Gaussian mixture model is employed to achieve an equivalence in terms of the probability density function (PDF) through the superposition of the response PDFs of the equivalent linear system. This new concept of linearization helps achieve a high level of estimation accuracy for nonlinear responses, but has revealed some limitations: (1) dependency of the equivalent linear systems on ground motion intensity and (2) requirements for stationary condition. To overcome these technical challenges and promote applications of GM‐ELM to earthquake engineering practice, an efficient GM‐ELM‐based fragility analysis method is proposed for nonstationary excitations. To this end, this paper develops the concept of universal equivalent linear system that can estimate the stochastic responses for a range of seismic intensities through an intensity‐augmented version of GM‐ELM. Moreover, the GM‐ELM framework is extended to identify equivalent linear oscillators that could capture the temporal average behavior of nonstationary responses. The proposed extensions generalize expressions and philosophies of the existing response combination formulations of GM‐ELM to facilitate efficient fragility analysis for nonstationary excitations. The proposed methods are demonstrated by numerical examples using realistic ground motions, including design code–conforming nonstationary ground motions.

Keywords:
Fragility Superposition principle Response analysis Gaussian Nonlinear system Linearization Range (aeronautics) Probability density function Mathematics Applied mathematics Statistical physics Computer science Engineering Mathematical analysis Physics Structural engineering Statistics

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15
Cited By
1.17
FWCI (Field Weighted Citation Impact)
49
Refs
0.78
Citation Normalized Percentile
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Citation History

Topics

Seismic Performance and Analysis
Physical Sciences →  Engineering →  Civil and Structural Engineering
Probabilistic and Robust Engineering Design
Social Sciences →  Decision Sciences →  Statistics, Probability and Uncertainty
Wind and Air Flow Studies
Physical Sciences →  Environmental Science →  Environmental Engineering

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