Stochastic Analysis of Train–Bridge System Using the Karhunen–Loéve Expansion and the Point Estimate Method

The bridge-vehicle interaction (BVI) system vibration is caused by the vehicles passing through the bridge. The road roughness has a great impact on the system vibration. In this regard, poor road roughness is known to affect the comfort of the vehicle crossing the bridge and aggravate the fatigue damage of the bridge. Road roughness is usually regarded as a random process in numerical calculation. To fully consider the influence of road roughness randomness on the response of the BVI system, a random BVI model was established. Thereafter, the random process of road roughness was expressed by Karhunen–Loeve expansion (KLE), after which the moment method was used to calculate the maximum probability value of the BVI system response. The proposed method has higher accuracy and efficiency than the Monte Carlo simulation (MCS) calculation method. Subsequently, the influences of vehicle speed, roughness grade, and bridge span on the impact factor (IMF) were analyzed. The results show that the road roughness grade has a greater impact on the bridge IMF than the bridge span and vehicle speed.

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“…After obtaining enough samples of road roughness, we can use the method introduced in [26] to solve λ i and φ i (x) numerically.…”

Section: Dynamic Statistics Calculation Approachmentioning

confidence: 99%

“…Xu et al [21][22][23][24][25] carried out extensive research on the vehicle-bridge coupling vibration considering track irregularity. In the studies conducted by Liu et al [26][27][28], KLE was also used to represent the stochastic process and combined with the point estimate method (PEM) [29,30].…”

Section: Introductionmentioning

confidence: 99%

Evaluating the Dynamic Response of the Bridge‐Vehicle System considering Random Road Roughness Based on the Moment Method

Feng

Huang

Wan

et al. 2021

Advances in Civil Engineering

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“…is paper is a further discussion of the previous works [24,26,27]. Hertz contact theory has been used for the calculation of normal contact force between a wheel and rail; the relationship between force and wheel/rail displacement is nonlinear.…”

Section: Introductionmentioning

confidence: 98%

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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“…Currently, train-track-bridge (TTB) model analysis is maturing [2][3][4]. ese studies based on finite element (FE) modeling have formed a relatively complete theoretical system of the response of TTB system.…”

Section: Introductionmentioning

confidence: 99%

An Efficient Model for Train‐Track‐Bridge‐Coupled System under Seismic Excitation

Jiang

Zhou

Liu

et al. 2021

Shock and Vibration

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When an earthquake occurs, due to the high operation speed of the train group, there is still a long distance from braking to stopping, so it needs a large number of bridge spans to calculate the integrated dynamic response, which leads to a large amount of calculation of the train-track-bridge (TTB) system under a seismic event. In order to reduce the amount of calculation, this paper proposed an efficient model called closed-loop model for simply supported railway bridge. The proposed model is realized by coupling the head and end of the rail-slab-bridge system through the utilization of pseudo-element. Simulation comparison of TTB response with and without seismic excitation between conventional TTB model and efficient model indicates that, under the premise of ensuring calculation accuracy, the efficient model shows the advantage of fewer degrees of freedom (DOF) of model and higher computational efficiency. For instance, under El Centro earthquake excitation, the time cost of proposed model is only 6% of conventional model. Meanwhile, six seismic events with different acceleration amplitudes are imposed on the efficient model, and the results of car-body acceleration, wheel-rail force, and wheel load reduction ratio are gathered and discussed; it can be concluded that, except Trinidad earthquake, for other earthquake samples investigated in this paper, with acceleration amplitude larger than 0.8 g, the train operation is at the risk of derailment.

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Stochastic Analysis of Train–Bridge System Using the Karhunen–Loéve Expansion and the Point Estimate Method

Cited by 49 publications

References 45 publications

Evaluating the Dynamic Response of the Bridge‐Vehicle System considering Random Road Roughness Based on the Moment Method

Evaluating the Dynamic Response of the Bridge‐Vehicle System considering Random Road Roughness Based on the Moment Method

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

An Efficient Model for Train‐Track‐Bridge‐Coupled System under Seismic Excitation

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