scholarly journals Dynamic Response of Railway Bridges under Heavy-Haul Freight Trains

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Ye Xiao ◽  
Xiaoyong Luo ◽  
Jinhong Liu ◽  
Kun Wang
Keyword(s):  
Dynamic Response ◽  
Fe Model ◽  
Bridge Structure ◽  
Railway Bridge ◽  
Running Speed ◽  
Railway Bridges ◽  
Heavy Haul ◽  
Formation Number ◽  
Axle Loads ◽  
Heavy Haul Railway

In the freight railway bridge, the increase of the train running speed and train axle loads can enlarge dynamic response (DR) of the railway bridges, which leads to excessive vibration of bridges and endangers the structural safety. In this paper, a three-dimensional coupled finite element (FE) model of a heavy-haul freight train-track-bridge (HHFTTB) is established using multibody dynamics theory and FE method, and the DR for the coupled system of HHFTTB are solved by ABAQUS/Explicit dynamic analysis method. The field-measured data for a 32 m simply supported prestressed concrete beam of a heavy-haul railway in China are analyzed, and the validity of the FE model is verified. Finally, the effects of train formation number, train running speed, and train axle loads on DR of the heavy-haul railway bridge structures are studied. The results show that increasing the train formation number only has an influence on DR duration of the bridge structure, rather than the peak value of DR, when the train formation number exceeds a certain number; besides, the train axle loads and train running speed have significant influence on DR of the bridge structure. The results of this study can be used as reference for the design of heavy-haul railway bridges and the reinforcement transformation of existing railway bridges.

Urban Railway Bridge Fast Evaluation Based on Cloud Computing

2011 ◽  
Vol 71-78 ◽  
pp. 4501-4505
Author(s):  
Ming Chen ◽  
Wan Zhou
Keyword(s):  
Neural Networks ◽  
Cloud Computing ◽  
Model Updating ◽  
Condition Assessment ◽  
Fe Model ◽  
Railway Bridge ◽  
Fast Evaluation ◽  
Railway Bridges ◽  
Computing Model ◽  
Bridge Condition Assessment

Although modern bridge are carefully designed and well constructed, damage may occur in them due to unexpected causes. Currently, many different techniques have been proposed and investigated in bridge condition assessment. However, evaluation efficiency of condition assessment has not been paid much attention by the researchers. A fast evaluation of the urban railway bridge condition based on the cloud computing is presented. In this paper dynamic FE model and Artificial neural networks technique is applied to model updating. The cloud computing model provides the basis for fast analyses. It was found that when applied to the actually railway bridges, the proposed method provided results similar to those obtained by experts, but can improve efficiency of bridge

scholarly journals Research on Dynamic Response Characteristics for Basement Structure of Heavy Haul Railway Tunnel with Defects

Mathematics ◽  
2021 ◽  
Vol 9 (22) ◽  
pp. 2893
Author(s):  
Jinfei Chai
Keyword(s):  
Constitutive Model ◽  
Dynamic Response ◽  
Principal Stress ◽  
Surrounding Rock ◽  
Railway Tunnel ◽  
Basement Structure ◽  
Measuring Point ◽  
Heavy Haul ◽  
Damage Constitutive Model ◽  
Heavy Haul Railway

Based on the basic principle of thermodynamics, an elastoplastic damage constitutive model of concrete is constructed in this paper. The model is realized and verified in FLAC3D, which provides a solid foundation for the study of dynamic response and fatigue damage to the base structure of a heavy haul railway tunnel. The dynamic response and damage distribution of the base structure of a heavy-duty railway tunnel with defects were numerically simulated by the concrete elastic-plastic damage constitutive model. Then, by analyzing the response characteristics of the tunnel basement structure under different surrounding rock softening degrees, different foundation suspension range and different foundation structure damage degree are determined. The results show the following: (1) The elastoplastic damage constitutive model of concrete can well describe the stress–strain relationship of materials, especially with the simulation results of post peak softening being in good agreement with the test results, and the simulation effect of the unloading–reloading process of the cyclic loading and unloading test also meet the requirements. (2) The initial stress field and dynamic response of the tunnel basement structure under the action of train vibration load are very different from the ideal state of the structure design when the surrounding rock of the base is softened, the base is suspended, or the basement structure is damaged. With the surrounding rock softening, basement hanging, or basement structure damage developing to a certain extent, the basement structure will be damaged. (3) The horizontal dynamic stress amplitude increases with the increase in the softening degree of the basement surrounding rock. The horizontal dynamic stress of the measuring point increases with the increase in the width of the hanging out area when the hanging out area is located directly below the loading line. When the degree of damage to the basement structure is aggravated, the horizontal dynamic tensile stress of each measuring point gradually decreases. (4) The maximum principal stress increment increases with the increase in the fracture degree of the basement structure, while the minimum principal stress increment decreases with the increase in the fracture degree of the basement structure, but the variation range of the large and minimum principal stress increments is small. The research results have important theoretical and practical significance for further analysis of the damage mechanism and control technology of the foundation structure of a heavy haul railway tunnel with defects.

Experimental research on the dynamic response characteristics of the transition subgrade induced by heavy-haul train passage

2019 ◽  
Vol 233 (9) ◽  
pp. 974-987 ◽  
Author(s):  
Huihao Mei ◽  
Wuming Leng ◽  
Rusong Nie ◽  
Renpan Tu ◽  
Yafeng Li ◽  
...  
Keyword(s):  
Dynamic Response ◽  
Repeated Loading ◽  
Moving Loads ◽  
Response Characteristics ◽  
Heavy Haul Train ◽  
Condition Evaluation ◽  
Heavy Haul ◽  
Variation Characteristics ◽  
Heavy Haul Railway ◽  
Moving Train

The dynamic response of the subgrade under moving train loads provides information on subgrade settlement prediction, condition evaluation, and so forth. This paper presents the field dynamics tests on the transition subgrade in the Shuo-Huang heavy-haul railway in China. The variation characteristics of the peak dynamic displacements along the track and subgrade slope were analyzed, and the random distribution characteristics of the peak dynamic displacements at the subgrade shoulder were studied. The response characteristics of the subgrade during the train passage were investigated, and the attenuation regularities of vibration along the subgrade slope were identified. The results indicated that the action of the train moving loads on the subgrade has obvious periodicity, and two bogies in the adjacent wagons should be considered as one loading unit. The peak dynamic displacements at the subgrade shoulder obey normal distribution under the repeated loading of the loading unit. The subgrade bed is dramatically influenced by the dynamic loadings of the trains, and the moving train loads have little influence on the part below the subgrade bed. The results of the research provide the basis for the evaluation of instantaneous and long-term dynamic stability of the subgrade and offer guidance for simulating train moving loads in the model test and numerical analysis to study the dynamic response of the subgrade.

scholarly journals Evaluation of Performance Indicator of Railway Bridges Using Updated Finite Element Model

2019 ◽  
Vol 69 (2) ◽  
pp. 89-96
Author(s):  
Sokol Milan ◽  
Márföldi Monika ◽  
Venglár Michal ◽  
Lamperová Katarína
Keyword(s):  
Health Monitoring ◽  
Performance Indicator ◽  
Element Model ◽  
Fe Model ◽  
Railway Bridge ◽  
Railway Bridges ◽  
Evaluation Of Performance ◽  
Bridge Structures ◽  
Steel Railway Bridge

AbstractStructural health monitoring (SHM) can provide information needed to make important decisions regarding the maintenance of bridge structures. However, the data collected from monitoring needs to be first translated into actionable, quantitative or qualitative based characteristics, that indicate the condition of a bridge. This paper presents a process of evaluation of such performance indicator in case of a steel railway bridge using the updated FE model and in-situ measurements of strains on selected stringers and floorbeams.

scholarly journals The Influence of Track Structure Parameters on the Dynamic Response Sensitivity of Heavy Haul Train-LVT System

2021 ◽  
Vol 11 (24) ◽  
pp. 11830
Author(s):  
Zhi-Ping Zeng ◽  
Yan-Cai Xiao ◽  
Wei-Dong Wang ◽  
Xu-Dong Huang ◽  
Xiang-Gang Du ◽  
...  
Keyword(s):  
Dynamic Response ◽  
Track Structure ◽  
Lateral Stiffness ◽  
Structure Parameters ◽  
Response Sensitivity ◽  
Vertical Stiffness ◽  
Rail System ◽  
Heavy Haul Train ◽  
Heavy Haul ◽  
Heavy Haul Railway

Background: In order to study the applicability of Low Vibration Track (LVT) in heavy-haul railway tunnels, this paper carried out research on the dynamic effects of LVT heavy-haul railway wheels and rails and provided a technical reference for the structural design of heavy-haul railway track structures. Methods: Based on system dynamics response sensitivity and vehicle-track coupling dynamics, the stability of the upper heavy-haul train, the track deformation tendency, and the dynamic response sensitivity of the vehicle-track system under the influence of random track irregularity and different track structure parameters were calculated, compared and analyzed. Results: Larger under-rail lateral and vertical structural stiffness can reduce the dynamic response of the rail system. The vertical and lateral stiffness under the block should be set within a reasonable range to achieve the purpose of reducing the dynamic response of the system, and beyond a certain range, the dynamic response of the rail system will increase significantly, which will affect the safety and stability of train operation. Conclusions: Considering the changes of track vehicle body stability coefficients, the change of deformation control coefficients, and the sensitivity indexes of dynamic performance coefficients to track structure stiffness change, the recommended values of the vertical stiffness under rail, the lateral stiffness under rail, the vertical stiffness under block, and the lateral stiffness under block are, respectively 160 kN/mm, 200 kN/mm, 100 kN/mm, and 200 kN/mm.

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

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Zhiwu Yu ◽  
Zhi Shan ◽  
Ju Yuan ◽  
Xiao Li
Keyword(s):  
Fatigue Life ◽  
Fatigue Loading ◽  
Load Level ◽  
Polymer Optical Fiber ◽  
Railway Bridges ◽  
Multisensor System ◽  
Linear Variable Displacement Transducer ◽  
Heavy Haul ◽  
Performance Deterioration ◽  
Heavy Haul Railway

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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