Fatigue analysis of long-span suspension bridges under multiple loading: Case study

Chen, Z.W.; Xu, You Lin; Xia, Yong; Li, Q.; Wong, K. Y. Michael

doi:10.1016/j.engstruct.2011.08.027

Cited by 69 publications

(34 citation statements)

References 14 publications

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“…21 That is, the weight of a long-span suspension bridge is signi¯cantly larger than the weight of a train and/or a series of road vehicles. Moreover, through the analysis of three resonance conditions, we observed that the impact factor of a long-span cable-supported bridge under a series of moving forces is often small.…”

Section: Brief Introduction Of the Existing Sil Identi¯cation Methodsmentioning

confidence: 99%

“…However, with consideration of stress response, railway loading serves a dominant function in most bridge components of TMB when compared with highway and wind loadings. 21 Peak stress is induced by trains that move close to the location of the concerned components. Two fundamental types of information required for SIL identi¯cation are measured stress (or strain) time history and the corresponding train information.…”

Section: Selection and Preprocessing Of Relevant Monitoring Datamentioning

confidence: 99%

See 1 more Smart Citation

Stress Influence Line Identification of Long Suspension Bridges Installed with Structural Health Monitoring Systems

Chen

Cai

2016

Int. J. Str. Stab. Dyn.

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Numerous long-span suspension bridges have been built worldwide over the past few decades. To ensure the safety of such bridges and their users during the bridge service life, several bridges have been equipped with Structural Health Monitoring Systems (SHMSs), which measure dynamic bridge responses and various loading types on-site. Integrating SHMS and damage detection technology for condition assessment of these bridges has become a new development trend. Recent studies have proven that stress in°uence line (SIL)-based damage indices achieve excellent damage detection performance for a long suspension bridge. However, an accurate and prompt manner of identifying the SIL of a long suspension bridge is important to facilitate the development of the SIL for an e®ective damage index. Identifying the SIL from eld measurement data under in-service conditions has several advantages over the traditional static loading test. This study proposes and develops a new SIL identi¯cation method by integrating the least squares solution and Weighted Moving Average (WMA) based on the measured train information and the corresponding train-induced stress time history. The efcacy of the proposed method is validated through its application to Tsing Ma Bridge (TMB). The good agreement between the identi¯ed and baseline SILs for a typical diagonal truss member veri¯es the e®ectiveness of the proposed method. Furthermore, robustness testing is performed by identifying SIL on the basis of information on di®erent trains and train-induced stress responses and by identifying the SIL of di®erent types of bridge components. Results indicate the feasibility of the application of the proposed approach to SIL identi¯cation for long-span bridges.

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Section: Brief Introduction Of the Existing Sil Identi¯cation Methodsmentioning

confidence: 99%

Section: Selection and Preprocessing Of Relevant Monitoring Datamentioning

confidence: 99%

Stress Influence Line Identification of Long Suspension Bridges Installed with Structural Health Monitoring Systems

Chen

Cai

2016

Int. J. Str. Stab. Dyn.

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“…Virlogeux [1992] and Gu et al [1999], by neglecting the vehicle effects, conducted buffeting induced fatigue analysis on two cable-stayed bridges and the fatigue life was found to be much longer than the design life of the bridges. In addition, many works have been carried out on the vehicle-bridge dynamic analysis or dynamic analysis of long-span bridges under wind, railway and highway loadings [Byers et al, 1997;Guo and Xu, 2001;Cai and Chen, 2004a;Xu et al, 2009;Chen and Wu, 2010;Chen et al, 2011aChen et al, , 2011b. However, most of these studies focus on dynamic displacements and accelerations by using a simple finite element model of the bridge without including structural details [Chen et al, 2011a].…”

Section: Performance Evaluation Of Vehicle and Wind-induced Bridge Famentioning

confidence: 99%

Framework of Wind–vehicle–bridge Interaction Analysis and Its Applications

Cai

Zhang

Liu

et al. 2013

J. Earthquake and Tsunami

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Under strong winds, bridges may exhibit large dynamic responses. Wind may also endanger the safety of moving vehicles on the roadways as well as on bridges. For regular aerodynamic study of long-span bridges, traffic loads are not typically considered, assuming that bridges will be closed to traffic at high wind speeds. Therefore, bridges are usually tested in wind tunnels or analyzed numerically without considering moving vehicles on them. However, there are numerous possible scenarios under which vehicles may still be on the bridge when higher wind speeds occur. These scenarios include unexpected increase in hurricane forward speed or intensity, evacuation traffic gridlock, accidents/stalled vehicles or rainfall flooding blocking the road ahead, etc. Wind, together with vehicles, will also cause serviceability and bridge fatigue damage issues. The present study will present the framework of wind-vehicle-bridge interaction analysis and its applications, developed in the last decade by the authors' group, focused on the vehicle and bridge safety issues. It consists of the following five parts: (1) A three dimensional finite element analysis framework considering the interaction of wind, bridge and vehicles; (2) experimental facilities development and studies for both static and aerodynamic tests of bridge section models and vehicles; (3) Computation fluid dynamic (CFD) prediction of loading on vehicles; (4) performance evaluation of vehicle safety and bridge fatigue; and (5) bridge vibration mitigations. Case study will also be presented and future research needs are discussed.

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“…Xu et al [24] studied the Continuum Damage Mechanics (CDM) based method for fatigue estimation. Statistical analysis [25] of stress and monitoring [26] has also been carried out. Ko and Kim [27] investigated the wide band nature of the stress process and the rain flow method of stress cycle counting.…”

Section: Introduction and Past Researchmentioning

confidence: 99%

“…They assume that these functions are error-free and provide a single estimated damage value. The error in the distributions may be due to short-term data that are commonly used in these analysis [1,15,[23][24][25]28] to determine the parameters. The sampling error due to the use of short-term data in parameter estimation can propagate into significant errors in the predicted fatigue damage.…”

Section: Introduction and Past Researchmentioning

confidence: 99%

Effect of uncertainties in wind speed and direction on the fatigue damage of long-span bridges

Alduse

Jung

Vanli

et al. 2015

Engineering Structures

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Fatigue analysis of long-span suspension bridges under multiple loading: Case study

Cited by 69 publications

References 14 publications

Stress Influence Line Identification of Long Suspension Bridges Installed with Structural Health Monitoring Systems

Stress Influence Line Identification of Long Suspension Bridges Installed with Structural Health Monitoring Systems

Framework of Wind–vehicle–bridge Interaction Analysis and Its Applications

Effect of uncertainties in wind speed and direction on the fatigue damage of long-span bridges

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