Assessment of Dynamic Behaviour and Performance of Existing Composite Railway Bridges Under the Impact of a High-Speed LHB Train Using a Coupled Approach

Bridge responses that are excited by high-speed trains have the characteristics of high amplitude, high cycle, and large dynamic effects, which greatly affect the fatigue bearing capacity of affected bridges. To achieve reliable analysis of the fatigue performance of high-speed railway bridges, this study developed a bridge fatigue life prediction method based on the reconstruction of the train-induced dynamic stress time history. First, the equations for solving the static stress time history under influence line virtual loading are derived, and then the dynamic stress time history reconstruction method based on two types of dynamic correction factors is proposed. The statistical characteristics of the train loads and dynamic correction factors are fit according to monitoring data, and bridge fatigue life prediction is realized by use of the reliability theory. Finally, the applicability and effectiveness of the proposed method are verified by using a train-bridge interaction model and monitoring data from a long-span high-speed railway bridge. The results show that the proposed method can greatly improve the accuracy of fatigue performance analysis and can effectively predict the fatigue life of high-speed railway bridges under complex loads. These results can provide an important reference for fatigue evaluation of high-speed railway bridges.

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Assessment of Dynamic Behaviour and Performance of Existing Composite Railway Bridges Under the Impact of a High-Speed LHB Train Using a Coupled Approach

Cited by 2 publications

References 82 publications

Improving Train Speed in Existing Short-Span Reinforced Concrete Railway Bridges Using Ballasted Pavement Retrofitting Method

Improving Train Speed in Existing Short-Span Reinforced Concrete Railway Bridges Using Ballasted Pavement Retrofitting Method

Fatigue life prediction for high-speed railway bridges by reconstructing monitoring-based dynamic stress

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