Seismic reliability evaluation of bridges under spatially varying ground motions using a four-parameter distribution

Chen, Zhiqiang; Zheng, Shixiong; Ding, Zihao; Jin, Zhang; Tai, Yu‐ji

doi:10.1016/j.engstruct.2021.113157

Cited by 15 publications

(3 citation statements)

References 48 publications

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“…After obtaining the fractional moments of Z, an adequate probability distribution model should be employed for the EVD estimation. Generally, the state-of-art distribution models represent the EVD by adopting either maximum entropy density [31,32] or positively skewed distributions such as shifted generalized lognormal distribution [35] and a mixture of lognormal distribution and inverse Gaussian distribution [33]. However, their flexibility is still limited for the EVDs with heavy tails, leading to the inaccuracy of EVD reconstruction for some first-passage problems.…”

Section: Representing Evd By a Mixture Distribution With Fractional M...mentioning

confidence: 99%

“…These methods enable to evaluate first-passage probabilities of high-dimensional and strongly nonlinear stochastic dynamic systems from a small number of simulations. Furthermore, a fractional moments-based shifted generalized lognormal distribution method [35] is utilized to assess seismic reliability of a practical bridge subjected to spatial variate ground motions. Besides, the linear moments-based polynomial normal transformation distribution method [36] is developed to analyze high-dimensional dynamic systems with deterministic structural parameters subjected to stochastic excitations.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

First-passage probability estimation of high-dimensional nonlinear stochastic dynamic systems by a fractional moments-based mixture distribution approach

Ding

Dang²,

Valdebenito³

et al. 2023

Mechanical Systems and Signal Processing

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Section: Representing Evd By a Mixture Distribution With Fractional M...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

First-passage probability estimation of high-dimensional nonlinear stochastic dynamic systems by a fractional moments-based mixture distribution approach

Ding

Dang²,

Valdebenito³

et al. 2023

Mechanical Systems and Signal Processing

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“…Cross PSD models are commonly employed to generate spatially correlated and varied random ground motion time histories, and have been widely applied in the system reliability assessment of large-span structures and lifeline networks. [25][26][27] Results have shown that load spatial correlation is influential on the seismic performance of large-scale engineering systems.…”

Section: Introductionmentioning

confidence: 99%

Structure‐to‐structure seismic damage correlation model

Xiang,

Shen,

et al. 2024

Earthq Engng Struct Dyn

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Strong earthquake disasters can cause noticeable damage correlations among regional buildings with similar mechanical properties, termed structure‐to‐structure seismic damage correlation, which has a pronounced impact on the regional seismic risk assessment and therefore needs to be properly quantified. This study first introduces a time‐domain analytical and equivalent frequency‐domain analysis based on random vibration theory for calculating structure‐to‐structure seismic damage correlation coefficients. Subsequently, by employing the spatially consistent white noise excitation and the spatially varying white noise excitation with the Luco–Wong coherence function, the structural filtering effect and the ground motion spatial correlation effect are progressively incorporated, and an analytical interstructural damage correlation model incorporating structural dynamic properties and spatial distance is derived. Comparations with Monte Carlo simulations and existing empirical models demonstrate that the proposed analytical model possesses a clear physical basis and high reliability. Finally, a case study was conducted on a district having 29,461 buildings in Shanghai, China to illustrate the influence of interstructural damage correlation on the regional seismic risk. Results show that disregarding the interstructural seismic damage correlation can lead to underestimation of overall loss uncertainty.

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Seismic fragility and resilience assessment of large‐span cable‐stayed bridges under multi‐support ground motions with non‐Gaussian characteristics

Lan,

Xu,

Zhong

et al. 2024

Earthq Engng Struct Dyn

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Seismic fragility analysis and resilience assessment of large‐span cable‐stayed bridge structures are critical for evaluating their seismic performance. However, there is a scarcity of research on the effects of multi‐support ground motions and their non‐Gaussian characteristics on seismic fragility and resilience. This paper aims to addresses this issue. Initially, random ground motions with spatial variability and non‐Gaussian characteristics are simulated using the Spectral Representation Method (SRM) and the Unified Hermite Polynomial Model (UHPM). Subsequently, the Fractional Exponential Moments‐based Maximum Entropy Method (FEM‐MEM) and the Adaptive Gaussian Mixture Model (AGMM) are employed for seismic reliability‐based fragility analysis, overcoming the shortcomings of conventional lognormal assumption. Component‐ and system‐level fragility analyses are conducted sequentially, followed by seismic resilience assessment of bridge structures based on the results of system‐level fragility analysis. A numerical example is presented to validate the proposed method. Computational results indicate that: (1) The proposed method offers higher accuracy and broader applicability for seismic fragility analysis of large‐span cable‐stayed bridge structures compared to traditional assumptions. (2) The non‐Gaussian characteristics of ground motions may significantly impact the seismic fragility analysis and resilience assessment of large‐span bridge structures.

show abstract

Seismic reliability evaluation of bridges under spatially varying ground motions using a four-parameter distribution

Cited by 15 publications

References 48 publications

First-passage probability estimation of high-dimensional nonlinear stochastic dynamic systems by a fractional moments-based mixture distribution approach

First-passage probability estimation of high-dimensional nonlinear stochastic dynamic systems by a fractional moments-based mixture distribution approach

Structure‐to‐structure seismic damage correlation model

Seismic fragility and resilience assessment of large‐span cable‐stayed bridges under multi‐support ground motions with non‐Gaussian characteristics

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