Dynamic Response of Railway Bridges under Heavy‐Haul Freight Trains

Xiao, Ye Long; Luo, Xiaoyong; Liu, Jinhong; Wang, Kun

doi:10.1155/2020/7486904

Cited by 10 publications

(4 citation statements)

References 31 publications

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“…Heavy-haul trains involve the significant amplitude and frequency of loading cycles, resulting in the excessive deformation and degradation of tracks and bridges [4][5][6]. The track system, consisting of rails, sleepers, and ballast, serves as a conduit for transferring the dynamic load of heavy-haul trains to the bridge deck.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Train–Track–Bridge Coupling Vibration Characteristics for Heavy-Haul Railway Based on Virtual Work Principle

Wu,

Yang,

Afsar

et al. 2023

Sensors

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This paper introduces an innovative model for heavy-haul train–track–bridge interaction, utilizing a coupling matrix representation based on the virtual work principle. This model establishes the relationship between the wheel–rail contact surface and the bridge–rail interface concerning internal forces and geometric constraints. In this coupled system’s motion equation, the degrees of freedom (DOFs) of the wheelsets in a heavy-haul train lacking primary suspension are interdependent. Additionally, the vertical and nodding DOFs of the bogie frame are linked with the rail element. A practical application, a Yellow River Bridge with a heavy-haul railway line, is used to examine the accuracy of the proposed model with regard to discrepancy between the simulated and measured displacement ranging from 1% to 11%. A comprehensive parametric analysis is conducted, exploring the impacts of track irregularities of varying wavelengths, axle load lifting, and the degradation of bridge stiffness and damping on the dynamic responses of the coupled system. The results reveal that the bridge’s dynamic responses are particularly sensitive to track irregularities within the wavelength range of 1 to 20 m, especially those within 1 to 10 m. The vertical displacement of the bridge demonstrates a nearly linear increase with heavier axle loads of the heavy-haul trains and the reduction in bridge stiffness. However, there is no significant rise in vertical acceleration under these conditions.

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Section: Introductionmentioning

confidence: 99%

Analysis of Train–Track–Bridge Coupling Vibration Characteristics for Heavy-Haul Railway Based on Virtual Work Principle

Wu,

Yang,

Afsar

et al. 2023

Sensors

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“…Based on the above, research is conducted in three aspects regarding the adaptability of existing railway steel bridges to heavy hauls and strengthening measures (Sun, 2014; Li & Luo, 2013; Walbridge & Liu, 2018; Cui, Zhang, Bao, Kang, & Bu, 2018; Wang, Wang, Duan, Wang, & Zhai, 2019; Li & Zhang, 2019; Zhang & Li, 2017; Wang, 2016; Zhang & Sun, 2019; Liu & He, 2020; Wang, 2018; Guo & Xu, 2017; Li, 2020; Al-Karawi, 2023; Han, Zhao, & Zhang, 2022; Wallin, Leander, & Karoumi, 2011; Han et al. , 2022; Yu, Shan, Yuan, & Li, 2018; Xiao, Luo, Liu, & Wang, 2020):Overall analysis of the adaptability of existing steel bridge structures to heavy hauls.Evaluation of fatigue life for existing steel bridges.Study of strengthening measures for existing steel bridges.…”

Section: Introductionmentioning

confidence: 99%

“…Some of them have already exhibited fatigue problems caused by structural defects. Based on the above, research is conducted in three aspects regarding the adaptability of existing railway steel bridges to heavy hauls and strengthening measures (Sun, 2014;Li & Luo, 2013;Walbridge & Liu, 2018;Cui, Zhang, Bao, Kang, & Bu, 2018;Wang, Wang, Duan, Wang, & Zhai, 2019;Li & Zhang, 2019;Zhang & Li, 2017;Wang, 2016;Zhang & Sun, 2019;Liu & He, 2020;Wang, 2018;Guo & Xu, 2017;Li, 2020;Al-Karawi, 2023;Han, Zhao, & Zhang, 2022;Wallin, Leander, & Karoumi, 2011;Han et al, 2022;Yu, Shan, Yuan, & Li, 2018;Xiao, Luo, Liu, & Wang, 2020):…”

Section: Introductionmentioning

confidence: 99%

Research on heavy-haul adaptive technology and strengthening measures for existing railway steel bridge

2023

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PurposeThis research addresses the diverse characteristics of existing railway steel bridges in China, including variations in construction age, design standards, structural types, manufacturing processes, materials and service conditions. It also focuses on prominent defects and challenges related to heavy transportation conditions, particularly low live haul reserves and severe fatigue problems.Design/methodology/approachThe study encompasses three key aspects: (1) Adaptability assessment: It begins with assessing the suitability of existing railway steel bridges for heavy-haul operations through comprehensive analyses, experiments and engineering applications. (2) Strengthening: To combat frequent crack defects in the vertical stiffener end structure of girder webs, fatigue performance tests and reinforcement scheme experiments were conducted. These experiments included the development of a hot-spot stress S-N curve for this structure, validating the effectiveness of methods like crack stop holes, ultrasonic hammering and flange angle steel. (3) Service life extension: Research on the cruciform welded joint structure (non-fusion transfer type) focused on fatigue performance over the long life cycle. This led to the establishment of a fatigue S-N curve, enhancing Chinese design codes.FindingsThe research achieved several significant outcomes: (1) Successful implementation of strengthening and retrofitting measures on a 64-m single-span double-track railway steel truss girder on an existing heavy-duty line. (2) Post-reinforcement, a substantial 26% to 32% reduction in live haul stress on bridge members was achieved. (3) The strengthening and retrofitting efforts met design expectations, enabling the bridge to accommodate vehicles with a 30-ton axle haul on the railway line.Originality/valueThis research systematically tackles challenges and defects associated with Chinese existing railway steel bridges, providing valuable insights into adaptability assessment, strengthening techniques and service life extension methods. Furthermore, the development of fatigue S-N curves and the successful implementation of bridge enhancements have practical implications for improving the resilience and operational capacity of railway steel bridges in China.

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“…The validation of numerical models of the train–bridge system is generally based on dynamic measurements derived from forced vibration tests under traffic actions [ 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 ]. Authors such as Zhai et al [ 12 ], Kwark et al [ 14 ], Liu et al [ 2 ], and Chellini et al [ 40 ] compared the numerical responses, derived from advanced train–bridge dynamic interaction models, with experimental responses, and they obtained a very good agreement between both records.…”

Section: Introductionmentioning

confidence: 99%

Train–Track–Bridge Dynamic Interaction on a Bowstring-Arch Railway Bridge: Advanced Modeling and Experimental Validation

Ribeiro

Calçada

Brehm³

et al. 2022

Sensors

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This article describes the validation of a 3D dynamic interaction model of the train–track–bridge system on a bowstring-arch railway bridge based on experimental tests. The train, track, and bridge subsystems were modeled on the basis of large-scale and highly complex finite elements models previously calibrated on the basis of experimental modal parameters. The train–bridge dynamic interaction problem, in the vertical direction, was efficiently solved using a dedicated computational application (TBI software). This software resorts to an uncoupled methodology that considers the two subsystems, bridge and train, as two independent structures and uses an iterative procedure to guarantee the compatibility of the forces and displacements at the contact points at each timestep. The bridge subsystem is solved by the mode superposition method, while the train subsystem is solved by a direct integration method. The track irregularities were included in the dynamic problem based on real measurements performed by a track inspection vehicle. A dynamic test under traffic actions allowed measuring the responses in the bridge, track, and vehicles, which were synchronized by GPS systems. The test results demonstrated the occurrence of upward displacements on the deck, which is a characteristic of structures with an arch structural behavior, as well as an alternation of tensile/compressive stresses between the rail and deck due to the deck–track composite effect. Furthermore, the acceleration response of the bridge proved to be significantly influenced by the train operating speed. The validation procedure involved comparing the dynamic responses obtained from the train–bridge interaction model, including track irregularities, and the responses obtained experimentally, through the test under traffic actions. A very good correlation was obtained between numerical and experimental results in terms of accelerations, displacements, and strains. The contributions derived from the parametric excitation of the train, the global/local dynamic behavior of the bridge, and the excitation derived from the track irregularities were decisive to accurately reproduce the complex behavior of the train–track–bridge system.

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Dynamic Response of Railway Bridges under Heavy‐Haul Freight Trains

Cited by 10 publications

References 31 publications

Analysis of Train–Track–Bridge Coupling Vibration Characteristics for Heavy-Haul Railway Based on Virtual Work Principle

Analysis of Train–Track–Bridge Coupling Vibration Characteristics for Heavy-Haul Railway Based on Virtual Work Principle

Research on heavy-haul adaptive technology and strengthening measures for existing railway steel bridge

Train–Track–Bridge Dynamic Interaction on a Bowstring-Arch Railway Bridge: Advanced Modeling and Experimental Validation

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