A Comprehensive Probabilistic Model of Traffic Loads based on Weigh-in-Motion Data for Applications to Bridge Structures

Kim, Ji‐Hwan; Song, Junho

doi:10.1007/s12205-019-2432-9

Cited by 27 publications

(14 citation statements)

References 35 publications

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“…is method is helpful to improve the identification accuracy of bridge structural damage location. Considering that the long-term effect of vehicle load is an important cause of fatigue, local damage, aging, reliability reduction, and so on, Jihwan Kim and Lili Li et al proposed a bridge vehicle load model and carrying capacity evaluation method based on dynamic weighing system [3,4]. Xiao-qin Li and Shiqiang Qin et al discussed the strategy and scheme of multiscale finite element simulation of long-span bridge structures with the goal of structural damage diagnosis and safety assessment [5,6].…”

Section: Intoductionmentioning

confidence: 99%

Research on Bridge Structural Damage Identification

Sun

Sheng

et al. 2022

Scientific Programming

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The traditional identification methods have limited ability to identify damage location of bridge structures. Therefore, a bridge structural damage location identification method based on deep learning is proposed. In addition, the sigmoid function is the activation function, and the cross entropy is the cost function. Meanwhile, take the Gaussian noise as the addition method and take the softmax as the classifier. So the constructed SDAE deep learning model can realize damage location identification of the simply supported the continuous beam bridges. Compared with the traditional identification methods of bridge structures, namely BP network and SVM, the proposed method shows higher identification accuracy and antinoise performance. Here, the average identification accuracy of the method for continuous beam bridge is 99.8%. As can be seen that the proposed method is more suitable for practical bridge structure damage location identification.

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Section: Intoductionmentioning

confidence: 99%

Research on Bridge Structural Damage Identification

Sun

Sheng

et al. 2022

Scientific Programming

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“…To estimate the traffic load effects based on the actual traffic environment of Hwayang-Jobal Bridge, this paper uses the WIM-based probabilistic model of bridge traffic loads (Kim and Song 2019) and the Bayesian updating methodology (Kim and Song 2021).…”

Section: Calculation Of Traffic Load Effects Using Traffic Environment Informationmentioning

confidence: 99%

“…Thus, this paper uses the traffic information of roads, which was obtained from the regular traffic investigation on the area around the example bridge, to approximate the actual traffic environment. Because the example bridge has a long span (a total length of 854 m), the maximum traffic load effect occurs under a congested traffic flow, i.e., where many vehicles exist on the bridge (Kim and Song 2019). Hence, the average speed under congestion and the occurrence frequency of the congestion state are necessary when simulating the traffic flow.…”

Section: Calculation Of Traffic Load Effects Using Traffic Environment Informationmentioning

confidence: 99%

Time-Dependent Reliability Assessment and Updating of Post-tensioned Concrete Box Girder Bridges Considering Traffic Environment and Corrosion

Kim

Song

2021

ASCE-ASME J. Risk Uncertainty Eng. Syst., Part A: Civ. Eng.

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In the reliability assessment of a bridge in operation with regards to its ultimate limit state, it should be noted that the strengths of members and effects of traffic load vary continuously over its lifespan due to the structural deterioration and changes of the traffic environment, respectively. Therefore, it is essential to collect relevant data, and incorporate the extracted information into a time-dependent reliability analysis. However, previous studies have not considered both traffic load effects and material deterioration models in timedependent reliability assessment for prestressed concrete (PSC) box girder bridges. To overcome this limitation and assess the reliability efficiently, this paper presents a comprehensive framework for time-dependent reliability assessment of post-tensioned concrete box girder bridges that can consider the traffic environment change and the corrosion in steel strands. The proposed framework employs probabilistic models and methods to estimate the flexural strengths and traffic load effects of a PSC box girder over time based on (1) corrosion-related data collected in the current practice of structure safety inspection, and (2) the traffic environment data obtained through weigh-in-motion (WIM) devices and traffic investigation. The time-dependent reliability is then computed using structural reliability methods based on the estimated strengths and load effects. As a numerical example, the time-dependent reliability of the PSC box girder of an actual cable-stayed bridge, Hwayang-Jobal Bridge in South Korea, is evaluated using the proposed framework. It is demonstrated that the framework can effectively assess the time-dependent reliability of a bridge in operation based on the uncertainties in the traffic environment and corrosion, and update it through data obtained by monitoring and inspection.

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“…Previous studies have done this by means of simple deterministic models, linear correlations, and copulas (see S. et al (2006); Kim and Song (2019) for example). These studies focus only on modeling axle loads (and not inter-axle distances) or provide at best fixed interaxle distances.…”

Section: Introductionmentioning

confidence: 99%

Vehicular Loads Hazard Mapping Through a Bayesian Network in the State of Mexico

Mendoza-Lugo

Morales-Nápoles

2021

Proceedings of the 31st European Safety and Reliability Conference (ESREL 2021)

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Traffic counts collect information that is valuable, for example, in bridge and road design or maintenance processes. The average daily traffic volume is often the most collected measure of vehicular traffic, which is used in the design or assessment of major highways. Permanent control stations, situated in key locations of the highway network, gather data the entire year. However, one of the disadvantages of traffic count data is that most counters used, do not measure total vehicle weight and axle load data. Traffic counts display only the classification of vehicles, traffic volume, average daily traffic, and annual average daily traffic. Axle loads on the other hand are required, for example, as input in the design of pavement and new bridges, and the reliability assessment of existing ones. Weighin-motion (WIM) systems are usually used to collect vehicle load data. The State of Mexico (in central Mexico) has 115 permanent vehicle counting stations with 745 traffic counting points in its federally administered road network. However, due to the lack of WIM stations, it is not possible to obtain axle load data. In this paper, a Bayesian Network (BN) quantified with data from WIM stations in the Netherlands is used to describe the weight and length distribution of heavy vehicles registered in the permanent vehicle counting stations of the State of Mexico federal highways. The Dutch and Mexican vehicle types are matched according to similar characteristics. Later, synthetic WIM observations from the BN model are analysed through extreme value theory and vehicle loads with selected return periods are computed for all study counting points. The outcome is a mapping methodology with a linked database. The traffic volumes and extreme loads can then be easily found and compared with other highways in the network. This work shows that hazard maps can be implemented to provide importantly and summarized information to understand the risks of extreme traffic loads and to help in the reliability assessment and maintenance strategies of pavements and bridges.

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A Comprehensive Probabilistic Model of Traffic Loads based on Weigh-in-Motion Data for Applications to Bridge Structures

Cited by 27 publications

References 35 publications

Research on Bridge Structural Damage Identification

Research on Bridge Structural Damage Identification

Time-Dependent Reliability Assessment and Updating of Post-tensioned Concrete Box Girder Bridges Considering Traffic Environment and Corrosion

Vehicular Loads Hazard Mapping Through a Bayesian Network in the State of Mexico

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