Three-dimensional random vibrations of a high-speed-train–bridge time-varying system with track irregularities

Zhu, Yan; Li, Xiaozhen; Jin, Zhibin

doi:10.1177/0954409715616836

Cited by 22 publications

(18 citation statements)

References 25 publications

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“…Based on the stochastic vibration theory and coupling dynamics of the rail track and wheel-set, the coupling vibration method [2][3][4] has been widely applied to the security analysis of high-speed trains. To analyze the reliability of moving trains on a bridge under stochastic excitations, random vibration methods, such as the pseudo-excitation method [5,6], spectral approach [7,8], and probability density evolution method [9] have been applied in the stochastic analysis of train-bridge systems. Additionally, the Monte Carlo simulation (MCS) method has been applied to reliability analysis of the train-bridge systems [10], and the stochastic characteristics of coupling systems have been explored in a way of the multi-sample calculation [11].…”

Section: Introductionmentioning

confidence: 99%

Random dynamic analysis of vertical train–bridge systems under small probability by surrogate model and subset simulation with splitting

et al. 2020

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The response of the train–bridge system has an obvious random behavior. A high traffic density and a long maintenance period of a track will result in a substantial increase in the number of trains running on a bridge, and there is small likelihood that the maximum responses of the train and bridge happen in the total maintenance period of the track. Firstly, the coupling model of train–bridge systems is reviewed. Then, an ensemble method is presented, which can estimate the small probabilities of a dynamic system with stochastic excitations. The main idea of the ensemble method is to use the NARX (nonlinear autoregressive with exogenous input) model to replace the physical model and apply subset simulation with splitting to obtain the extreme distribution. Finally, the efficiency of the suggested method is compared with the direct Monte Carlo simulation method, and the probability exceedance of train responses under the vertical track irregularity is discussed. The results show that when the small probability of train responses under vertical track irregularity is estimated, the ensemble method can reduce both the calculation time of a single sample and the required number of samples.

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Section: Introductionmentioning

confidence: 99%

Random dynamic analysis of vertical train–bridge systems under small probability by surrogate model and subset simulation with splitting

et al. 2020

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“…To obtain an efficient and accurate calculation method for the random dynamics of the TTBS, many studies have been conducted. For instance, the pseudo-excitation method was used for the random dynamics analysis of the train-track system and TTBS [12][13][14][15][16]. It is convenient to use the pseudo-excitation method for response power spectrum calculation in both nonstationary and stationary random excitation structural analysis with a high application value.…”

Section: Introductionmentioning

confidence: 99%

Application of KLE-PEM for Random Dynamic Analysis of Nonlinear Train-Track-Bridge System

Jiang

Liu

Zhou

et al. 2020

Shock and Vibration

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A nonlinear train-track-bridge system (TTBS) considering the random track irregularity and mass of train is discussed. Based on the Karhunen–Loéve theory, the track irregularity is expressed and input into the TTBS, and the result of random response is calculated using the point estimation method. Two cases are used to compare and validate the applicability of the proposed method, which show that the proposed method has a high precision and efficiency. Then, taking a 7-span bridge and a high-speed train as an example, the calculation results of random response of the nonlinear and linear wheel-rail model are compared, and the results show that for the bridge and rail response, the nonlinear and linear models are almost the same. Finally, comparing the calculated probability distribution results with the test results, it shows that the method can be applied to the prediction of actual response range.

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“…The stationary random loading is a usual practical situation for the high-speed trains, in which the stress range and stress ratio vary with constant statistical characteristics (the mean and standard deviation). 5,6 Realistic random loading will give rise to the fatigue damage high-nonlinear accumulation. One big challenge is the explanation of random loading interaction effects.…”

Section: Introductionmentioning

confidence: 99%

Time-variant fatigue reliability evaluation of riveted lap joint under stationary random loading

Jiang

2020

Proceedings of the Institution of Mechanical Engineers, Part O:

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This article focuses on the time-variant reliability assessment of riveted lap joint structure subjected to fatigue. A physics-based fatigue crack growth model that can take the crack closure into account is derived to calculate the crack length at different time under arbitrary loading. In addition, several uncertainties are quantified, including the material, initial crack size, and loading condition. The stationary random loading is a common service environment in practice, in which the stress range and stress ratio vary with constant statistical characteristics (the mean and standard deviation). The time-variant fatigue reliability of riveted lap joint under stationary random loading is assessed by introducing the outcrossing concept. The experimental data of 2024-T3 aluminum alloy riveted lap joint under constant amplitude loading are used to validate the physics-based fatigue crack growth model. It is verified that this proposed model can predict the fatigue life probability distribution with a reasonable accuracy. In addition, the simulation of riveted lap joint under stationary random loading is performed. The time-variant fatigue reliability is evaluated. The results with or without considering crack closures are also compared. It is noted that the results from the time-variant fatigue reliability assessment considering crack closure has higher reliability level.

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Three-dimensional random vibrations of a high-speed-train–bridge time-varying system with track irregularities

Cited by 22 publications

References 25 publications

Random dynamic analysis of vertical train–bridge systems under small probability by surrogate model and subset simulation with splitting

Random dynamic analysis of vertical train–bridge systems under small probability by surrogate model and subset simulation with splitting

Application of KLE-PEM for Random Dynamic Analysis of Nonlinear Train-Track-Bridge System

Time-variant fatigue reliability evaluation of riveted lap joint under stationary random loading

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