Random dynamic analysis of a train-bridge coupled system involving random system parameters based on probability density evolution method

Mao, Jianfeng; Yu, Zhiwu; Xiao, Yuanjie; Jin, Cheng; Bai, Yu

doi:10.1016/j.probengmech.2016.08.003

Cited by 66 publications

(20 citation statements)

References 19 publications

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“…According to Eq. (16), k steps are needed to determine the initial probability of failure p f ¼ PðFÞ ¼ PðF k Þ by SS. Hence, the quantity of the required SS steps, k, depends also on the actual probability of failure of the problem.…”

Section: Subset Simulationmentioning

confidence: 99%

“…From this short discussion it becomes apparent that bridge and high-speed train represent a highly dynamic interacting system, whose reliability should be investigated in more detail by the design engineer. Uncertainties of the train-bridge interaction problem, which considerably influence the structural response, are dispersing material parameters (in particular damping), track irregularities, and environmental effects [16,23]. For instance, if ballast and subsoil start to freeze due to the prevailing temperature conditions, the global stiffness of the bridge, and consequently, its natural frequencies increase.…”

Section: Introductionmentioning

confidence: 99%

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On the optimal strategy of stochastic-based reliability assessment of railway bridges for high-speed trains

et al. 2019

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The scope of this paper is to evaluate the performance and computational efficiency of various stochastic simulation methods for a stochastic based reliability assessment of railway bridges subjected to high-speed trains. Depending on the degree of sophistication, application of crude Monte Carlo simulation to a realistic mechanical model of the uncertain bridge-train interacting dynamical system can be prohibitively expensive. Thus, three alternative stochastic methods, i.e. line sampling, subset simulation, and asymptotic sampling, are tested on two example problems. These examples represent two classes of bridges with different dynamic response characteristics. While in the one class of bridges distinctive resonance peaks govern the dynamic peak response, the random response amplification of the second group of bridges is primarily induced by track irregularities. The studies are conducted on a simplified mechanical model, composed of a plain beam representing the bridge and a planar mass-springdamper system representing the train. This modeling strategy captures the fundamental characteristics of dynamic bridge-train interaction, and thus, facilitates the desired assessment of the stochastic methods with reasonable computational effort. It is shown that both line sampling and subset simulation reduce significantly the computational expense for the first class of bridges, while maintaining the accuracy of the predicted bridge reliability. To ensure accuracy and efficiency, these methods need to be modified when applied to systems where track irregularities dominate the random response. For the latter class of bridges, subset simulation proved to be a suitable method for assessing the reliability of this dynamic interacting system when appropriately modified.

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Section: Subset Simulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

On the optimal strategy of stochastic-based reliability assessment of railway bridges for high-speed trains

et al. 2019

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“…Fourthly, by applying the mechanical similarity mentioned in the specimen design section, it is speculated that the residual midspan deflection for the bridge on site is f r ≈ 2.0 × 6 = 12.0 mm, when the bridge is subjected to the train loading with a 30-ton axle weight experiencing cycle number N ≈ 3.0 × 10 6 . Therefore, the performance deterioration of the bridge may cause serious traffic safety problems, especially considering the dynamic coupling of the train and the bridge [28,29].…”

Section: Performance Deterioration Of Heavy-haul Railwaymentioning

confidence: 99%

Performance Deterioration of Heavy-Haul Railway Bridges under Fatigue Loading Monitored by a Multisensor System

Shan

Yuan

et al. 2018

Journal of Sensors

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Heavy-haul railway bridges play an increasingly essential role in the transportation in China due to the increasing transport volume. The performance deterioration of the scale models of a typical heavy-haul railway bridge under fatigue loading is monitored in this work, based on a multisensor system including the fiber-reinforced polymer optical fiber Bragg grating and electrical resistance strain gauges, linear variable displacement transducer, and accelerometer. Specifically, by monitoring/ observing on the failure mode, fatigue life, load-midspan deflection response, material strain development, and so forth, this work develops an S-N model by comparing the relationship between fatigue life and rebar stress range with that between fatigue life and load level and proposes a damage evolution model considering the coupling of the stiffness degradation and inelastic deformation of specimens. It is found that the fatigue life of specimens is determined by the fatigue life of the rebar at the bottom and it may be lower than 2.0 million cycles with a 30-ton axle weight when environmental factors are taken into account. The predictions of the models agree well with experimental results. Therefore, this work furthers the understanding of the fatigue performance deterioration of the bridges by using a multisensor system.

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“…In recent decades, research on the dynamic interaction of vehicle-rail bridges has increased and primarily focuses on the following aspects: (1) e dynamic response of trains in dangerous areas, such as road bridge transitions, curved bridges, and culvert transition zones [12][13][14][15][16][17][18][19]. (2) e dynamic performance of a train that passes through a bridge under external adverse influences, such as earthquake, wind and bridge skewness, or noise of composite bridge results [20][21][22][23][24][25][26][27].…”

Section: Introductionmentioning

confidence: 99%

Field Test and Numerical Analysis of In‐Service Railway Bridge

Liu

Hou

Fei

et al. 2020

Advances in Materials Science and Engineering

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Field tests and numerical simulations are combined in this paper. Cross-sectional dimension measurements, dynamic performance tests, and forced vibration tests were performed on the NO·40 beam bridge of the Xin-Tai Railway. By comparing the test results with the specifications, the current service status of the bridge was evaluated, and the basis for subsequent correction and verification models was provided. A dynamic coupled finite element model of the passenger-freight-cable-track-bridge was established considering the degree of bridge damage (0%∼50%) and the track irregularity, and the model simulation results for the Xin-Tai Railway NO·40 bridge were measured. The results are compared to verify the correctness of the model. The results show that the damage to the bridge will affect the vertical displacement response and the safety stability of the train. The vertical displacement response of the bridge midspan is twice that of the bridge performance. When the damage level of the bridge is 30%, the passenger and freight trains exceed the safety warning limit, which should cause concern.

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Random dynamic analysis of a train-bridge coupled system involving random system parameters based on probability density evolution method

Cited by 66 publications

References 19 publications

On the optimal strategy of stochastic-based reliability assessment of railway bridges for high-speed trains

On the optimal strategy of stochastic-based reliability assessment of railway bridges for high-speed trains

Performance Deterioration of Heavy-Haul Railway Bridges under Fatigue Loading Monitored by a Multisensor System

Field Test and Numerical Analysis of In‐Service Railway Bridge

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