Monitoring and Evaluation of Overturning Resistance of Box Girder Bridges Based on Time-Varying Reliability Analysis

Dan, Danhui; Yu, Xuewen; Yan, Xiangqiao; Zhang, Kailong

doi:10.1061/(asce)cf.1943-5509.0001375

Cited by 13 publications

(9 citation statements)

References 13 publications

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“…The author of this paper has proposed identification methods of full-bridge traffic load distribution based on computer vision in 2019 and 2020 [22], [23], which have preliminarily solved the problem of bridge traffic load measurement. On this basis, anti-overturning monitoring method of box girder bridges based on measured traffic load is established [24], [27], as well as simulation method of traffic load model based on machine vision [28]. These studies have shown a good prospect of applying DT to bridges group health monitoring.…”

Section: Digital Twin System Of Bridges Group Based On Machine Vision Fusion Monitoring Of Bridge Traffic Loadmentioning

confidence: 99%

Digital Twin System of Bridges Group Based on Machine Vision Fusion Monitoring of Bridge Traffic Load

Dan

Ying

2022

IEEE Trans. Intell. Transport. Syst.

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Bridges play an important role in transportation infrastructure systems. Intelligent and digital management of bridges group is an essential part of the future intelligent transportation infrastructure system. This paper proposes a digital twin system for bridges group in the regional transportation infrastructure network, which is interconnected by measured traffic loads. In physical space, a full-bridge traffic load monitoring system based on information fusion of weigh-in-motion (WIM) and multi-source heterogeneous machine vision is set up on the target bridge to measure traffic loads, also lightweight sensors are employed on the bridges group for structural response information. Furthermore, by establishing mechanical analysis models in the corresponding digital space and using the measured traffic loads as links, the working condition perception and safety warning of all bridges in the regional transportation network is achieved, forming an important support for further intelligent transportation infrastructure system. The proposed digital twin system has been preliminarily implemented in a bridges group around Shanghai, China, demonstrating the feasibility of the technical framework proposed in this paper and the bright prospects.

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Section: Digital Twin System Of Bridges Group Based On Machine Vision Fusion Monitoring Of Bridge Traffic Loadmentioning

confidence: 99%

Digital Twin System of Bridges Group Based on Machine Vision Fusion Monitoring of Bridge Traffic Load

Dan

Ying

2022

IEEE Trans. Intell. Transport. Syst.

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“…Therefore, the pier top section size can be minimalized during the design of pier top girder to reduce the consumption of bridge materials. Double-limb thin-walled piers are adopted in the construction of long-span bridges to ensure the strength and stability of the bridge, as well as a small thrust stiffness to solve the displacement problem of the bridge pier top [27]. Like the single-limb thin-walled pier, the cross section of the double-limb thin-walled pier also contains hollow piers and solid piers.…”

Section: Types Of Pier Structure Of the Continuous Rigid-framementioning

confidence: 99%

The Influence of Buckling Mode and Buckling Stability Coefficient of Rigid-Frame Bridge during Construction in Cold Region

Zhang²,

Wang

2022

Geofluids

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The study aims to further standardize the construction process, improve the construction quality, and ensure the stability of infrastructure construction. The continuous rigid-frame bridge is taken as the research object, the finite element model of the bridge body is established by using the beam element, and the overall stability of the rigid-frame bridge is analyzed in the construction and completion stages. Moreover, the stability coefficient and buckling mode are established under different working conditions in each stage, the linear stability variation law is summarized, and the geometric nonlinear stability analysis method is established through the specific data. The nonlinear stability safety factor and buckling mode are obtained, and the influence of wind load and initial defects on the stability of continuous rigid-frame bridge is further explored. The results show that with the increase of the bridge height, the overall stability factor of the bridge is decreasing, and the safety factor of the single-limb thin-walled hollow pier is relatively larger than that of the double-limb thin-walled hollow pier. During the construction, the asymmetric self-weight load caused by the asynchronous load and cantilever pouring has the greatest impact on the stability of the bridge. The stability safety factor of the geometric nonlinear stability analysis method constructed is 0.3% and 1.27% lower than the ideal state, respectively. The stability safety factor of the wind load and the initial defect is 12.65% lower than the ideal state, and the stability safety factor is greatly reduced. The results have important reference significance to ensure the construction safety and overall stability of the bridge.

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“…Many scholars have studied the probability of failure models of bridges concerning time. [1][2][3][4][5][6] Cornell proposed a second-order moment model for computing structural safety. 7 Ang and Cornell proposed a First Order Reliability Method (FORM) for reliability calculation, which quickly gained wide applications in various fields.…”

Section: Introductionmentioning

confidence: 99%

A method for time‐varying reliability calculation of RC bridges considering random deterioration process

Yang

Huang

2023

Quality & Reliability Eng

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This paper proposes a new method based on dual neural networks to improve the efficiency of time‐varying reliability calculation of bridge structures. Based on the basic theory of structural time‐varying reliability analysis, this method uses the dyadic neural network integration method to convert the time‐varying reliability calculation of bridges from the traditional Monte Carlo simulation to the direct integration operation, which improves operation efficiency and retains high working accuracy. In addition, considering the randomness of the decay process of different bridge resistances, the variation law of time‐varying reliability of bridges in the process of uncertain resistance reduction is studied, and an explicit formula for time‐varying reliability of bridges is given and solved by using the proposed dual neural network method. Finally, the effectiveness of the proposed method is verified by an engineering arithmetic example. The result indicates that the bridge has a greater probability of failure under random conditions.

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Monitoring and Evaluation of Overturning Resistance of Box Girder Bridges Based on Time-Varying Reliability Analysis

Cited by 13 publications

References 13 publications

Digital Twin System of Bridges Group Based on Machine Vision Fusion Monitoring of Bridge Traffic Load

Digital Twin System of Bridges Group Based on Machine Vision Fusion Monitoring of Bridge Traffic Load

The Influence of Buckling Mode and Buckling Stability Coefficient of Rigid-Frame Bridge during Construction in Cold Region

A method for time‐varying reliability calculation of RC bridges considering random deterioration process

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