PSI - Issue 64

Lucas Martins Barreto et al. / Procedia Structural Integrity 64 (2024) 1168–1175 Author name / Structural Integrity Procedia 00 (2019) 000 – 000

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those not directly related to reinforced or prestressed concrete bridges or not addressing design conception or structural health monitoring. We prioritized articles published between 2019 and 2023 that significantly contributed to addressing the question of how Digital Twins can be effectively employed in monitoring the structural health of reinforced and prestressed concrete bridges. Selected articles were categorized to align with the study's scope, and relevant information was extracted for the literature review. Additionally, two case studies were selected using the same criteria. One case study focused on a project utilizing Digital Twins in bridge construction, while the other examined real-time continuous monitoring of a bridge's structural health. These case studies provided practical understandings into the application of Digital Twins in reinforced and prestressed concrete bridge engineering. 3. Digital Twin Workflow The process of creating and maintaining a Digital Twin involves several key stages, including data acquisition, storage, transfer, analysis, and visualization. The accuracy and effectiveness of the Digital Twin depends on each stage, ultimately leading to better decision-making and asset management practices Wenner et al. (2022) outline the main steps of a Digital Twin workflow, which include the development of the digital model, data collection, storage, transfer, analysis and categorization, as well as Digital Twin updating, graphical interface building, and planning and implementation actions. Below in the table 1, is presented a summary of the key stages involved in the creation and management of a Digital Twin for bridges, along with references to relevant studies that have explored these stages in detail.

Table 1: Key stages involved in the creation and management of a Digital Twin for bridges. Stage Description

References

Creation of the digital model

Defines the entire volume of the bridge to be analyzed in a virtual way. Can be created from BIM software or photogrammetry with methodologies like laser sensors, LiDAR, and Point Cloud system. Obtains data to be monitored using sensors or drones. Data can be used directly in updating the Digital Twin or require prior processing. Uses database technology with hardware and/or software support to store the large volume of data obtained over time. Sends data obtained and stored in the field via the internet (MQTT or http) to the digital model for synchronization. Analyzes the synchronized data, which can be done manually or in an automated way with artificial intelligence. Classifies data by type and urgency, using software like SIB-Bauwerke and following methodologies like FMECA. Updates the digital model to match the physical model, following methodologies like Data-Centric Engineering (DCE) framework. Visualizes the digital model in a 3D model using software like WebGL, HTML5, and virtual reality devices (VR). Plans maintenance and preventive inspections based on real-time monitoring data, ensuring bridge safety and maintenance.

Kaewunruen et al. (2021), Khemlani (2022), Sofia, Anas, Faiz (2020)

Data acquisition

Dong et al. (2021)

Data storage

Wenner et al. (2022)

Data transfer

Sofia, Anas, Faiz (2020)

Data analysis

Kaewunruen et al. (2021)

Data classification

Wenner et al. (2022)

Digital Twin Update

Ye et al. (2019)

Graphical interface

Ye et al. (2019), Wenner et al. (2022)

Planning and execution

Wenner et al. (2022)

The table 1 highlights the multidisciplinary nature of Digital Twin development, encompassing aspects of data acquisition, storage, transfer, analysis, and visualization. It underscores the importance of advanced technologies such as sensors, drones, and artificial intelligence in ensuring the accuracy and effectiveness of the Digital Twin. By following these stages and methodologies, infrastructure managers could make informed decisions regarding maintenance and inspection, ultimately enhancing the safety and efficiency of bridge assets.