Latest Advances in Finite Element Modelling and Model Updating of Cable-Stayed Bridges

Sharry, Thomas; Guan, Hong; Nguyễn, Andy; Oh, Erwin

doi:10.3390/infrastructures7010008

Cited by 18 publications

(9 citation statements)

References 132 publications

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“…Maintenance and repair costs also go down. In the area of SHM, various new methods have been developed in recent years, the vast majority of which are based on finite element modeling or the use of modal features [102]. Because of the extensive number of computations required and the inherent unpredictability of the models, these approaches are relatively incompatible with real-world scenarios and cannot achieve the desired results.…”

Section: Shm Of Bridge and Aimentioning

confidence: 99%

The State of the Art of Artificial Intelligence Approaches and New Technologies in Structural Health Monitoring of Bridges

et al. 2022

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The challenges of urban administration are growing, as the population, automobiles, and cities rise. Making cities smarter is thus one of the most effective solutions to urban issues. A key feature of the “smart cities” of today is that they use cutting-edge technology in their infrastructure and services. With strategic planning, the smart city utilizes its resources in the most efficient manner. With reduced expenses and enhanced infrastructure, smart cities provide their residents with more and better services. One of these important urban services that can be very helpful in managing cities is structural health monitoring (SHM). By combining leading new technologies like the Internet of Things (IoT) with structural health monitoring, important urban infrastructure can last longer and work better. A thorough examination of recent advances in SHM for infrastructure is thus warranted. Bridges are one of the most important parts of a city’s infrastructure, and their building, development, and proper maintenance are some of the most important aspects of managing a city. The main goal of this study is to look at how artificial intelligence (AI) and some technologies, like drone technology and 3D printers, could be used to improve the current state of the art in SHM systems for bridges, including conceptual frameworks, benefits and problems, and existing methods. An outline of the role AI and other technologies will play in SHM systems of bridges in the future was provided in this study. Some novel technology-aided research opportunities are also highlighted, explained, and discussed.

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Section: Shm Of Bridge and Aimentioning

confidence: 99%

The State of the Art of Artificial Intelligence Approaches and New Technologies in Structural Health Monitoring of Bridges

et al. 2022

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“…Cable-supported bridges, mainly consisting of cable-stayed bridges and suspension bridges, only account for about 1.5% of the total number of bridges while being employed as an effective structural form for large-span requirements and complex environments [3][4][5]. By optimizing the material properties of cables [6] and increasing the accuracy of numerically simulating their behavior [7,8], the introduction of cables in bridges significantly improves their applicable span.…”

Section: Introductionmentioning

confidence: 99%

“…Furthermore, the previous studies also provided design suggestions for tower shapes, anchor locations, and deck cross-sections [10]. The mechanical performance, including vibration modes and natural frequencies of the complicated cable-supported bridges, was mainly obtained using nonlinear finite element (FE) analysis based on the cable element and its stiffness matrix [7,[11][12][13][14][15]. With expressive FE models, a great deal of analyses were conducted for the cable-stayed and suspension bridges under statistical vehicle loads [16], earthquakes [17], typhoons [18,19], and even fire risks [20].…”

Section: Introductionmentioning

confidence: 99%

Safety–Function–Environment Evaluation System for Large-Span Cable-Supported Bridges: Theory and Case Studies

Zhang,

Tan,

et al. 2024

Sustainability

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Compared with common bridges, large-span cable-supported bridges contain more components, are located in a more complex environment, and play a more important role in traffic system sustainability. Throughout the service life, it is more necessary to evaluate their safety, functionality, and environmental status. In this study, a comprehensive evaluation system is proposed to fill the gap using advanced sensor-guided structural health monitoring data and probability-based digital twins. Safety evaluation is the basis of the system and can be divided into overall and component levels. The former includes an over-limit analysis of main structural responses and degradation identification of dynamic characteristics. The abnormal areas discovered in this phase and the hot spots prompted by prior information during the design process will be checked in the latter. The functional assessment of this system is mainly based on checklist-type inspection and is often carried out together with appearance inspection and non-main structural component detection. Environmental assessment includes the monitoring and analysis of wind fields, temperature, humidity, foundation scour, and traffic flow and is the source of external information in the aforementioned two modules. The temperature and humidity of the example bridges are basically uniformly distributed along the spatial dimension, fluctuating over a period of one day.

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“…Finite element (FE) model updating is a well-recognized approach for SHM purposes, as an accurate model serves as a baseline reference for damage detection and long-term monitoring efforts. The latest advances in finite element modeling and model updating of cable-stayed bridges were presented by Sharry et al [ 14 ]. In addition, influence lines or static methods are also used for damage identification of cable-stayed bridges.…”

Section: Introductionmentioning

confidence: 99%

Multiple Damaged Cables Identification in Cable-Stayed Bridges Using Basis Vector Matrix Method

Ren

Zhu

2023

Sensors

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A new damaged cable identification method using the basis vector matrix (BVM) is proposed to identify multiple damaged cables in cable-stayed bridges. The relationships between the cable tension stiffness and the girder bending strain of the cable-stayed bridge are established using a force method. The difference between the maximum bending strains of the bridges with intact and damaged cables is used to obtain the damage index vectors (DIXVs). Then, BVM is obtained by the normalized DIXV. Finally, the damage indicator vector (DIV) is obtained by DIXV and BVM to identify the damaged cables. The damage indicator is substituted into the damage severity function to identify the corresponding damage severity. A field cable-stayed bridge is used to verify the proposed method. The three-dimensional finite element model is established using ANSYS, and the model is validated using the field measurements. The validated model is used to simulate the strain response of the bridge with different damage scenarios subject to a moving vehicle load, including one, two, three, and four damaged cables with damage severity of 10%, 20%, and 30%, respectively. The noise effect is also discussed. The results show that the BVM method has good anti-noise capability and robustness.

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Latest Advances in Finite Element Modelling and Model Updating of Cable-Stayed Bridges

Cited by 18 publications

References 132 publications

The State of the Art of Artificial Intelligence Approaches and New Technologies in Structural Health Monitoring of Bridges

The State of the Art of Artificial Intelligence Approaches and New Technologies in Structural Health Monitoring of Bridges

Safety–Function–Environment Evaluation System for Large-Span Cable-Supported Bridges: Theory and Case Studies

Multiple Damaged Cables Identification in Cable-Stayed Bridges Using Basis Vector Matrix Method

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