On the digital twinning of load tests in railway bridges. Case study: High speed railway network, Extremadura, Spain

Chacón, R.; Posada, Hector; Ramonell, C.; Sierra, Pablo; Rodríguez, A.; Koulalis, Ilias; Ioannidis, K.; Vrochidis, S.; Tomar, Rahul; Freitag, S.; Wagmeister, Stefan; Teodorovic, Mirko

doi:10.1201/9781003322641-98

Cited by 5 publications

(3 citation statements)

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“…Moreover, researchers have introduced various mixed definitions of bridge DT, which makes it difficult to establish an evolved digital platform with seamless integration of technologies [12,27]. 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].…”

Section: Introductionmentioning

confidence: 99%

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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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Section: Introductionmentioning

confidence: 99%

“…As the bridge undergoes changes or natural deterioration happens with its operational life, the as-is model updating replicates these modifications. The synchronization supports better decision-making for maintenance and repairs, as the DT provides an up-to-date and detailed understanding of the bridge's current state [29][30][31][32].…”

mentioning

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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“…Demonstrative case studies of various structures, such as buildings, bridges, footbridges, airports, ports, and stadiums, make up the project's test beds. These test beds have been detailed in reports available in [12], providing an expansive outlook for exploring asset twinning opportunities [13][14][15][16][17][18].…”

mentioning

confidence: 99%

I‐Twin. Computational twin connectors for I‐profiles. Towards unforeseen interoperability of digital tools

Posada,

Chacón,

Ramonell

2023

ce papers

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Standard BIM data‐exchange format requirements are permeating Building Construction. This is due to the increasing digital communication between Stakeholders of complex projects. All steps of development (conception, design, procurement, construction and operation) are pushing towards integration of data schemas. Desirably, knowledge and value generated by one stakeholder may then be leveraged by other stakeholders. 3D models, simulations, measurements, logbooks, schedules, as‐built conditions and other information constructs are on the verge of interoperable communication. Structural Analysis must play a significant role within those more digitized data exchanges. This paper presents recent developments of frameworks, connectors and tools for the integration of structural I‐shaped beam entities into Digital Twins. The information construct I‐Twin encompasses information loads for geometries (IFC‐Based), sensors (IoT) and simulations (FEM).

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A Framework for 3D Modeling of Construction Sites Using Aerial Imagery and Semantic NeRFs

Vrachnos,

Krestenitis,

Koulalis

et al. 2024

Lecture Notes in Computer Science

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On the digital twinning of load tests in railway bridges. Case study: High speed railway network, Extremadura, Spain

Cited by 5 publications

References 0 publications

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

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

I‐Twin. Computational twin connectors for I‐profiles. Towards unforeseen interoperability of digital tools

A Framework for 3D Modeling of Construction Sites Using Aerial Imagery and Semantic NeRFs

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