Seismic fragility analysis of deteriorated bridge structures employing a UAV inspection-based updated digital twin

Yoon, Sung-Sik; Lee, Sangmok; Kye, Seungkyung; Kim, Inho; Jung, Hyung‐Jo; Spencer, Billie F.

doi:10.1007/s00158-022-03445-0

Cited by 13 publications

(6 citation statements)

References 39 publications

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“…However, their approach lacks dealing with the integration of FE and structural analysis tools. Yoon et al (2022) assess bridge condition based on images captured with a UAV from which damage is automatically detected through a mask Region-based Convolutional Neural Network (R-CNN) algorithm. The methodology proposed by these authors also included a FE model updating module based on a linear stiffness reduction corresponding to the level of bridge condition assessment, as per the damage grades defined in South Korean accepted codes.…”

Section: Uavs Satellite Monitoring and Other Dtrelated Emerging Techn...mentioning

confidence: 99%

Bridge management through digital twin-based anomaly detection systems: A systematic review

Rios

Plevris

Nogal

2023

Front. Built Environ.

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Bridge infrastructure has great economic, social, and cultural value. Nevertheless, many of the infrastructural assets are in poor conservation condition as has been recently evidenced by the collapse of several bridges worldwide. The objective of this systematic review is to collect and synthesize state-of-the-art knowledge and information about how bridge information modeling, finite element modeling, and bridge health monitoring are combined and used in the creation of digital twins (DT) of bridges, and how these models could generate damage scenarios to be used by anomaly detection algorithms for damage detection on bridges, especially in bridges with cultural heritage value. A total of 76 relevant studies from 2017 up to 2022 have been taken into account in this review. The synthesis results show a consensus toward the future adoption of DT for bridge design, management, and operation among the scientific community and bridge practitioners. The main gaps identified are related to the lack of software interoperability, the required improvement of the performance of anomaly-detection algorithms, and the approach definition to be adopted for the integration of DT at the macro scale. Other potential developments are related to the implementation of Industry 5.0 concepts and ideas within DT frameworks.

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Section: Uavs Satellite Monitoring and Other Dtrelated Emerging Techn...mentioning

confidence: 99%

Bridge management through digital twin-based anomaly detection systems: A systematic review

Rios

Plevris

Nogal

2023

Front. Built Environ.

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“…Journal of civil structural health monitoring O&M (Dang and Shim, 2020) 14 Lecture notes in civil engineering O&M (Bello et al, 2022) 3 Lecture notes in civil engineering F, O&M (Zhou et al, 2022) -Lecture notes in civil engineering F, O&M (Kang et al, 2021) 27 Multimedia tools and applications F, O&M (Mohammadi et al, 2021) 37 Remote sensing E (Marra et al, 2021) 3 SCIRES-IT E (Shao et al, 2020) 19 Sensors E (Ghahari et al, 2022) 6 Sensors O&M (Yu et al, 2022) 5 Structural control and health monitoring O&M (Yoon et al, 2022) 2 Structural and multidisciplinary optimization O&M (Ye et al, 2019) 40 Proceedings of the 12th international workshop on structural health monitoring O&M (Shu et al, 2019) 3 Proceedings of the 12th international workshop on structural health monitoring E, O&M (Jiang et al, 2021a) 4 Structural monitoring and maintenance O&M (Shim et al, 2019a) 99 Structure and infrastructure engineering F, O&M (Omer et al, 2019) 45 Structure and infrastructure engineering E, O&M (Ye et al, 2020a) 7 Structure and infrastructure engineering O&M (Jiang et al, 2022a) 1 Structure and infrastructure engineering F, O&M (Futai et al, 2022) 3 Structure and infrastructure engineering F, O&M Note: The number of citations in the table is based on the Scopus data as of June 2023. The meaning of the symbols in the table is defined in the following section.…”

Section: Definition and Development Of Digital Twinmentioning

confidence: 99%

“…Applications References Perception Virtual inspection (Marra et al, 2021;Omer et al, 2019Omer et al, , 2021) Real-time monitoring (Dang et al, 2022;Zhou et al, 2022;Ye et al, 2019;Shao et al, 2020;Lai et al, 2022) Evaluation Analysis diagnosis (Ye et al, 2020b;Ghahari et al, 2022;Yu et al, 2022;Dan et al, 2021;Shu et al, 2019;Yoon et al, 2022;Lai et al, 2022) Performance prediction (Yu et al, 2022;Jiang et al, 2021aJiang et al, , 2021bZhao et al, 2022) Scenario simulation (Baisthakur and Chakraborty, 2021;Van Nimmen et al, 2021;Jiang et al, 2022a)…”

Section: Categoriesmentioning

confidence: 99%

“…However, The point cloud focuses more on the appearance of the bridge structure and does not consider the degradation of material properties over time. Yoon et al (2022) used a UAV to check the material property degradation of bridge structural members to update the FEM for seismic fragility analysis. Lai et al (2022) combined computer vision 3D reconstruction and vibration measurements to assess bridge structural condition using heterogeneous information sources.…”

Section: Analysis Diagnosis the Condition Analysis And Diagnosismentioning

confidence: 99%

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Research progress and prospect of digital twin in bridge engineering

Yang,

Zhu,

Cai

2023

Advances in Structural Engineering

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The concept of digital twins in bridge engineering is still vague and even confused with the Bridge Information Model (BrIM). Therefore, this study provides a detailed review of 42 papers related to digital twins in bridge engineering, focusing on a proper definition, key features and creation techniques for bridge digital twin (BDT). The paper also compares BDT and BrIM from the perspectives of their elements, features, fidelity, services provided, and degree of development. The applications of BDT at different life cycle stages are identified, and the related technologies are analyzed in detail. The results show that the research clusters of BDT are divided into geometric model generation, finite element model updating, and management and are focused on the operation and maintenance phase while lacking attention in the design and construction phase. Besides, a reference framework of BDT based on the life cycle of bridges is proposed, and directions for future research are suggested.

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“…Many methods in the literature define bridge DT as a FEM updating approach that collects data from different sensors, explores potential relationships between different datasets, considers uncertainties, and makes predictions for bridge safety and reliability in specific situations [28][29][30][31][32]. Other methods consider DTs as an as-is BrIM updating approach to generate a DT-enhanced BrIM framework with the latest inspection damage information [33][34][35][36]. These research studies can help in tackling the dilemma of changing from static and enclosed information with recurring compatibility difficulties to a connected data model, where the physical asset can be completely represented as a DT.…”

Section: Introductionmentioning

confidence: 99%

Evolution of Digital Twin Frameworks in Bridge Management: Review and Future Directions

Mousavi,

Rashidi,

Mohammadi

et al. 2024

Remote Sensing

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Over the last decade, the digital twin (DT) concept has effectively revolutionized conventional bridge monitoring and management. Despite their overall success, current bridge DTs encounter conceptual ambiguities, hindering their inherent potential for practical implementation. Moreover, intelligent decision support models have not been properly considered as a component of the bridge DTs framework to enhance the reliability of decisions for asset maintenance. Therefore, this paper conducts a scientometric analysis and a comprehensive state-of-the-art review, exploring current bridge DT research trends and architectures and introducing an enhanced conceptual framework for bridge DTs. To this end, more than 480 research publications have been reviewed, compared, and analyzed. The research result encompasses the redevelopment of a multilayer DT framework, fostering its implementation in the full lifecycle of bridge infrastructure while exploring the potential integration of decision support systems and data fusion from advanced technologies to improve the overall efficiency of implementing DT technology in bridges.

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Seismic fragility analysis of deteriorated bridge structures employing a UAV inspection-based updated digital twin

Cited by 13 publications

References 39 publications

Bridge management through digital twin-based anomaly detection systems: A systematic review

Bridge management through digital twin-based anomaly detection systems: A systematic review

Research progress and prospect of digital twin in bridge engineering

Evolution of Digital Twin Frameworks in Bridge Management: Review and Future Directions

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