Fatigue reliability assessment for bridge welded details using long-term monitoring data

Deng, Yang; Ding, Youliang; Li, Aiqun; Zhou, Guangdong

doi:10.1007/s11431-011-4526-6

Cited by 38 publications

(17 citation statements)

References 18 publications

(22 reference statements)

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“…In order to ensure the service life and security of constructional works, it is necessary to monitor the constructional work systematically during its building and operating. Due to the diversity, complexity and non-deterministic characters of inducing factors of the building subsidence deformation, the mechanical behavior and deformation trend of building subsidence also reflect non-linear characteristics with the coexistence of the uncertainty and randomness [17][18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34]. Existing methods for building subsidence deformation prediction usually establish the time series analysis model by utilizing monitored data [35][36][37][38][39][40].…”

mentioning

confidence: 99%

Dynamic prediction of building subsidence deformation with data-based mechanistic self-memory model

Wang

Hou

et al. 2012

Chin. Sci. Bull.

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This paper describes a building subsidence deformation prediction model with the self-memorization principle. According to the non-linear specificity and monotonic growth characteristics of the time series of building subsidence deformation, a data-based mechanistic self-memory model considering randomness and dynamic features of building subsidence deformation is established based on the dynamic data retrieved method and the self-memorization equation. This model first deduces the differential equation of the building subsidence deformation system using the dynamic retrieved method, which treats the monitored time series data as particular solutions of the nonlinear dynamic system. Then, the differential equation is evolved into a difference-integral equation by the self-memory function to establish the self-memory model of dynamic system for predicting nonlinear building subsidence deformation. As the memory coefficients of the proposed model are calculated with historical data, which contain useful information for the prediction and overcome the shortcomings of the average prediction, the model can predict extreme values of a system and provide higher fitting precision and prediction accuracy than deterministic or random statistical prediction methods. The model was applied to subsidence deformation prediction of a building in Xi'an. It was shown that the model is valid and feasible in predicting building subsidence deformation with good accuracy. The fast development of economics promotes the urbanization of China. More and more high-rises appear in our cities [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16]. In order to ensure the service life and security of constructional works, it is necessary to monitor the constructional work systematically during its building and operating. Due to the diversity, complexity and non-deterministic characters of inducing factors of the building subsidence deformation, the mechanical behavior and deformation trend of building subsidence also reflect non-linear characteristics with the coexistence of the uncertainty and randomness [17][18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34]. Existing methods for building subsidence deformation prediction usually establish the time series analysis model by utilizing monitored data [35][36][37][38][39][40]. However, most of these models are of the "parameter model" class which may not have clear physical meaning of parameters and discard effective parts of monitoring data. On the basis of the retrieved modeling, self-memorization principle has been recently developed based on the mechanism of time series data. As a mathematic realization on integration of deterministic and random theory, the self-memory model is a statistical-dynamical method to solve problems in nonlinear dynamic systems [41][42][43]. The core method of the model is to transform differential equations into difference-integral equations by introduction of the self-memory function. For dynamic systems described by differential equations, pre...

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mentioning

confidence: 99%

Dynamic prediction of building subsidence deformation with data-based mechanistic self-memory model

Wang

Hou

et al. 2012

Chin. Sci. Bull.

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“…The width and height of RSB's steel box girder are 36.3 and 3.0 m, respectively, and the width and height of RCB's steel box girder are 37.4 and 3.0 m, respectively. The SHMS of the Runyang Bridges has been established for real-time monitoring of structural responses, geometric deformations, environmental conditions, and traffic loadings by using modern techniques in sensing, testing, and network communication [20,23]. During the construction period, three types of strain sensors, namely, the optical fiber strain sensor, vibration chord strain sensor, and strain gauge, were installed at certain key positions in order to evaluate the fatigue performances of the welded details.…”

Section: Bridge Description and Instrumentationmentioning

confidence: 99%

“…One of the traffic growth patterns is to assume that over a certain period, growth takes place in a linear fashion. Deng et al [20] directly adopted the linear growing pattern of number of cycles to consider the traffic growth. In this work, the traffic flow growth is also simulated with a linear increase of number of cycles.…”

Section: Fatigue Life Prediction Based On 4-year Datamentioning

confidence: 99%

“…In recent years, however, it is proved that structural monitoring is essential in the fatigue performance assessment of steel bridges [11,12]. Consequently, a more accurate method to measure the fatigue stress is introduced with the development of structural health monitoring system (SHMS) [13][14][15][16][17][18][19][20][21][22]. SHMS provides opportunities to observe more realistic stress distributions and fatigue behaviors under operational excitations.…”

Section: Introductionmentioning

confidence: 99%

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Investigation of fatigue performance of welded details in long-span steel bridges using long-term monitoring strain data

Deng

Liu

Feng

et al. 2015

Struct. Control Health Monit.

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SUMMARYMonitoring strain data provides possibilities for the fatigue assessment of the critical components in real structures under the operational conditions. This paper presents a case study on the investigation of fatigue performance of welded details. Long-term monitoring strain data of 4 years between 2006 and 2009 collected by the structural health monitoring system mounted on the Runyang Suspension Bridge and Runyang Cable-stayed Bridge are utilized. The study focuses on two aspects: (i) the effects of different strain components in the raw strain data on the fatigue damage assessment and (ii) the necessity of long-term strain measurement for fatigue evaluation. The results indicate that temperature effect on the stress range spectrum is negligible. The enormous low-level stress cycles caused by random interference would result in erroneous equivalent stress ranges and number of cycles, and thus should be eliminated from the stress range spectrum. Through in-depth analysis of monitoring strain data in three special months and in 3 years, respectively, it is revealed that short-term data monitored in a few days and medium-term data monitored in a few months are not adequate enough to reveal the actual fatigue behaviors of steel bridges and would give inaccurate fatigue life prediction. Finally, the fatigue life predictions of two types of welded details by considering traffic flow growth are carried out. Lessons learned from the long-term monitoring are expected to enhance our understanding in fatigue performances of steel bridges.

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“…However, the stable and exact measurement of the stress values of structure details may then only be obtained by the durable and sensitive strain gauges embedded in the structure during the construction phase [27][28][29]. In addition, the influences on the bridge safety brought by the vehicle loads [30,31], seismic loads [32,33], environmental corrosions [34,35], and thermal effects [36] had be investigated widely, and the concrete shrinkage & creep (S&C) effects of the laboratory specimens [37] and simple bridge types [38,39] were also widely reported. However, the field measurement for the complicated self-anchored suspension bridge, including the detailed stress and geometry evolution associated with time-dependent effects were rarely reported, especially for the one having such an extra-wide concrete girder [40,41].…”

Section: Introductionmentioning

confidence: 99%

Structural Health Monitoring and Time-Dependent Effects Analysis of Self-Anchored Suspension Bridge with Extra-Wide Concrete Girder

Zhou

et al. 2018

Applied Sciences

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Abstract:The present work is aimed at studying the structural health status of Hunan Road Bridge, which is currently the widest concrete self-anchored suspension bridge in China. The monitoring data included the structural deformations, internal forces, and vibration characteristics from April 2015 to April 2016 were analyzed to evaluate the structural changes and safety. The influences brought by the ambient temperature changes and the dual effects composed of concrete shrinkage & creep (S&C) and seasonal temperature changes were analyzed based on the measured data. The long-time effects of concrete S&C were predicted using the CEB-FIP 90 model and the age-adjusted effective modulus method based on the ANSYS beam finite element model. The measured data showed that the transverse displacements of towers were more significant than the longitudinal ones. The spatial effect of the extra-wide girder is significant, which performs as the longitudinal stresses change unevenly along the transverse direction. The seasonal ambient warming caused overall increases in girder compressive stresses, and the cooling resulted in decreases along with significant temperature gradient effects. The prediction results show that the cable anchoring positions at girder ends and tower tops will move towards the mid-span affected by concrete S&C. In terms of the middle region of mid-span girder, significant increases in longitudinal stresses of top plate and decreases in the ones of bottom plate will be caused by the significant deflection. Comprehensively, the increases in the girder compressive stresses of side-span bottom plate and mid-span top plate are worthy of attention when confronted with extreme high temperature during the bridge service life cycle.

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Fatigue reliability assessment for bridge welded details using long-term monitoring data

Cited by 38 publications

References 18 publications

Dynamic prediction of building subsidence deformation with data-based mechanistic self-memory model

Dynamic prediction of building subsidence deformation with data-based mechanistic self-memory model

Investigation of fatigue performance of welded details in long-span steel bridges using long-term monitoring strain data

Structural Health Monitoring and Time-Dependent Effects Analysis of Self-Anchored Suspension Bridge with Extra-Wide Concrete Girder

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