scholarly journals Evaluating Probabilistic Traffic Load Effects on Large Bridges Using Long-Term Traffic Monitoring Data

Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 5056 ◽  
Author(s):  
Lu ◽  
Ma ◽  
Liu
Keyword(s):  
Control Measure ◽  
Heavy Traffic ◽  
Suspension Bridge ◽  
Traffic Monitoring ◽  
Traffic Load ◽  
Monitoring Data ◽  
Traffic Density ◽  
Maximum Deflection ◽  
Load Effects ◽  
Crossing Theory

With the steadily growing of global transportation market, the traffic load has increased dramatically over the past decades, which may develop into a risk source for existing bridges. The simultaneous presence of heavy trucks that are random in nature governs the serviceability limit for large bridges. This study investigated probabilistic traffic load effects on large bridges under actual heavy traffic load. Initially, critical stochastic traffic loading scenarios were simulated based on millions of traffic monitoring data in a highway bridge in China. A methodology of extrapolating maximum traffic load effects was presented based on the level-crossing theory. The effectiveness of the proposed method was demonstrated by probabilistic deflection investigation of a suspension bridge. Influence of traffic density variation and overloading control on the maximum deflection was investigated as recommendations for designers and managers. The numerical results show that the congested traffic mostly governs the critical traffic load effects on large bridges. Traffic growth results in higher maximum deformations and probabilities of failure of the bridge in its lifetime. Since the critical loading scenario contains multi-types of overloaded trucks, an effective overloading control measure has a remarkable influence on the lifetime maximum deflection. The stochastic traffic model and corresponding computational framework is expected to be developed to more types of bridges.

Probabilistic evaluation of maximum dynamic traffic load effects on cable-supported bridges under actual heavy traffic loads

2020 ◽  
pp. 1748006X2093849
Author(s):  
Yang Liu ◽  
Qinyong Wang ◽  
Naiwei Lu
Keyword(s):  
Heavy Traffic ◽  
Suspension Bridge ◽  
Traffic Monitoring ◽  
Traffic Load ◽  
Dynamic Traffic ◽  
Type Distribution ◽  
Cable Stayed Bridge ◽  
Weigh In Motion ◽  
Load Effects ◽  
Motion Measurements

The traffic load has grown significantly in recent years, which might be a threat for the service safety of existing bridges. Thus, it is an urgent task to assess the actual traffic load effects on bridges, considering actual heavy traffic load instead of design traffic load. This study presents a framework for extrapolating maximum dynamic traffic load effects on large bridges using site-specific traffic monitoring data. The framework involves vehicle–bridge interaction analysis and probabilistic modelling of extreme values. The weigh-in-motion measurements of a busy highway in China were collected for stochastic traffic load modelling. Case studies of two long-span cable-supported bridge based on the weigh-in-motion measurements were conducted to demonstrate the effectiveness of the proposed framework. It is demonstrated that Rice’s level-crossing approach can capture both dynamic and probabilistic characteristics of the traffic load effects. The root-mean-square displacement of the cable-stayed bridge follows a C-type distribution, and the one for the suspension bridge follows an M-type distribution, which is associated with the first-order mode shapes of the two types of bridges. The amplification factors for the cable-stayed bridge and the suspension bridge are 5.9% and 3.6%, respectively. The numerical analysis indicates that the dynamic effect for extrapolation is weaker with the increase in bridge span length, but the effect of traffic volume growth will be more significant.

scholarly journals Image Processing in Intelligent Traffic Management

2019 ◽  
Vol 8 (2S4) ◽  
pp. 213-218
Keyword(s):  
Image Processing ◽  
Traffic Management ◽  
Heavy Traffic ◽  
Traffic Monitoring ◽  
Transportation Systems ◽  
Traffic Density ◽  
Control Mechanisms ◽  
Image Processing Techniques ◽  
Wide Range ◽  
Processing Techniques

Traffic monitoring and traffic control have always been challenging tasks. Intelligent Transportation Systems (ITS) based on wide range of technologies have certain practical challenges in their application and implementation. Video surveillance has proven advantageous over traditional systems based on inductive loops sensors and detectors for traffic monitoring. Accurate traffic density estimation which is basic to tackling traffic congestions requires detection of vehicles, assessing their speed, and tracking vehicles passing through surveillance zones. Image processing techniques require processing of large number of image frames for real-time applications in traffic management. More efficient and less costly image processing techniques for accurate vehicle detection and density determination are required for developing more effective traffic management systems. There is a need for developing algorithms with robust performance under heavy traffic loads and varied environmental conditions. Developments in artificial intelligence offer new vistas in image processing for regulation and management of traffic by signal control mechanisms and creation of neural networks for unhindered traffic flow.

scholarly journals Bayesian structural identification of a long suspension bridge considering temperature and traffic load effects

2018 ◽  
Vol 18 (4) ◽  
pp. 1310-1323 ◽  
Author(s):  
Andre Jesus ◽  
Peter Brommer ◽  
Robert Westgate ◽  
Ki Koo ◽  
James Brownjohn ◽  
...  
Keyword(s):  
Suspension Bridge ◽  
Structural Identification ◽  
Traffic Load ◽  
Load Effects

scholarly journals Fatigue Assessment on Suspenders under Stochastic Wind and Traffic Loads Based on In-Situ Monitoring Data

2019 ◽  
Vol 9 (16) ◽  
pp. 3405 ◽  
Author(s):  
Mengxue Wu ◽  
Jin Zhu ◽  
Junlin Heng ◽  
Sakdirat Kaewunruen
Keyword(s):  
Fatigue Damage ◽  
Life Time ◽  
Suspension Bridge ◽  
In Situ Monitoring ◽  
Traffic Load ◽  
Monitoring Data ◽  
Fatigue Reliability ◽  
Fatigue Assessment ◽  
Traffic Loads

As a critical component of a suspension bridge, the integrity of the suspenders plays a critical role in the serviceability and reliability of the bridge during its life time. Despite the wide recognition of the importance of the suspenders, very few studies have been devoted to the condition evaluation of suspenders in operation. The present study performs the fatigue assessment on the suspenders accounting for the stochastic wind and traffic loads using the in-situ monitoring data. To this end, a probabilistic numerical framework is proposed to predict the time-dependent fatigue reliability of the suspenders under stochastic wind and traffic loads during the bridge’s life time, based on the linear fatigue damage rule. As a demonstration, the proposed numerical framework is applied to a long-span suspension bridge located in a mountainous canyon. The results indicate that it is of paramount importance to consider both the wind and traffic load effects in the fatigue reliability evaluation of the suspenders. In addition, it was also found that among the suspenders under investigation, the short suspender at the bridge mid-span (S36) is more prone to the fatigue damage, while the long suspender at the end of the bridge girder (S2) is less prone to the fatigue damage. Finally, provided with a target reliability index of 3.0, the fatigue life of the suspenders S36 and S2, considering the life time wind and traffic load, is estimated as 53 years and 167 years, respectively. The present research could provide essential guidelines for the optimization of inspection and replacement in maintenance practices for suspenders.

scholarly journals System Reliability Assessment of Cable-Supported Bridges under Stochastic Traffic Loads Based on Deep Belief Networks

2020 ◽  
Vol 10 (22) ◽  
pp. 8049
Author(s):  
Naiwei Lu ◽  
Yang Liu ◽  
Mohammad Noori ◽  
Xinhui Xiao
Keyword(s):  
Mechanical Behavior ◽  
System Reliability ◽  
Suspension Bridge ◽  
Reliability Evaluation ◽  
Traffic Monitoring ◽  
Numerical Results ◽  
Traffic Load ◽  
Belief Networks ◽  
Deep Belief Networks ◽  
Structural Nonlinearities

A cable-supported bridge is usually a key junction of a highway or a railway that demands a higher safety margin, especially when it is subjected to harsh environmental and complex loading conditions. In comparison to short-span girder bridges, long-span flexible structures have unique characteristics that increase the complexity of the structural mechanical behavior. Therefore, the system safety of cable-supported bridges is critical but difficult to evaluate. This study proposes a novel and intelligent approach for system reliability evaluation of cable-supported bridges under stochastic traffic load by utilizing deep belief networks (DBNs). The related mathematical models were derived taking into consideration the structural nonlinearities and high-order statically indeterminate characteristics. A computational framework is presented to illustrate the steps followed for system reliability evaluation using DBNs. In a case study, a prototype suspension bridge is selected to investigate the system reliability under stochastic traffic loading based on site-specific traffic monitoring data. The numerical results indicated that DBNs provide an accurate approximation for the mechanical behavior accounting for structural nonlinearities and different system behaviors, which can be treated as a meta-model to estimate the structural failure probability. The dominant failure modes of the suspension bridge are the fracture of suspenders followed by the bending failure of girders. The degradation of suspenders due to fatigue-corrosion damage has a significant effect on the system reliability of a suspension bridge. The numerical results provide a theoretical basis for the design on cable replacement strategies.

scholarly journals Characteristic dynamic traffic load effects in bridges

2009 ◽  
Vol 31 (7) ◽  
pp. 1607-1612 ◽  
Author(s):  
Eugene J. OBrien ◽  
Paraic Rattigan ◽  
Arturo González ◽  
Jason Dowling ◽  
Aleš Žnidarič
Keyword(s):  
Traffic Load ◽  
Dynamic Traffic ◽  
Load Effects ◽  
Characteristic Dynamic

Proposed evaluation methods for vibration serviceability of long span cable bridges

2021 ◽  
Author(s):  
E.-S. Hwang ◽  
M. T. Hwang ◽  
D. Y. Kim ◽  
K. J. Park
Keyword(s):  
Heavy Traffic ◽  
Damping Ratio ◽  
Flexible Structures ◽  
Evaluation Methods ◽  
Monitoring Data ◽  
Long Span ◽  
Vibration Serviceability ◽  
Long Term Monitoring ◽  
Term Monitoring

<p>Vibration serviceability becomes more important considerations in design and maintenance, especially for slender and flexible structures such as long span cable bridges. In this study, various evaluation methods for vibration serviceability for long span cable bridges are proposed. These methods are based on short and long-term monitoring data such as accelerations and displacements of bridges. Proposed methods include (1) method of evaluating vibration amplitude based on Reiher-Meister curves, (2) method of evaluating variations in natural frequencies and damping ratio,</p><p>(3) method of weighted rms(root-mean-square) acceleration based on ISO 2631-1, and (4) probabilistic analysis using long-term monitoring data. These methods are applied to example cable bridge and cases of normal traffic, heavy traffic, windy condition and sudden abnormal vibration are considered. The results of this study are expected to be implemented to real bridge monitoring system for real-time and periodic evaluation of vibration serviceability.</p>

Measuring heavy traffic with WIM-ROAD and WIM-BRIDGE systems in an urban environment

2021 ◽  
Author(s):  
Maarten Soudijn ◽  
Sebastiaan van Rossum ◽  
Ane de Boer
Keyword(s):  
Heavy Traffic ◽  
Pressure Sensors ◽  
Strain Sensors ◽  
Traffic Load ◽  
Structural Safety ◽  
Special Focus ◽  
The Road ◽  
Weigh In Motion ◽  
Set Up ◽  
Calibration Program

<p>In this paper we present weight measurements of urban heavy traffic comparing two different Weigh In Motion (WIM) systems. One is a WIM-ROAD system using Lineas quartz pressure sensors in the road surface. The other is a WIM-BRIDGE system using optical fibre-based strain sensors which are applied under the bridge to the bottom fibre of a single span of the bridge deck. We have designed our tests to determine which system is most suited to Amsterdam. We put special focus on the accuracy that each system can achieve and have set up an extensive calibration program to determine this. Our ultimate goal is to draw up a realistic traffic load model for Amsterdam. This model would lead to a recommendation that can be used to re- examine the structural safety of existing historic bridges and quay walls, in addition to the current traffic load recommendations.</p>

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