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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1. Introduction Digital Twins represent the connection between the physical and information worlds, enabling an efficient flow of data between them. This technological approach has a wide range of applications, from analyzing the behavior of structural elements to understanding urban dynamics. Also, it allows the planning, monitoring, inspecting, and decision making for present and future smart cities. Sensors that send real-time data to the system, combined with artificial intelligence, enable the analysis and diagnosis of structures, aiding decision-making, and disaster prevention (JIANG et al., 2021). Wenner et al. (2022) emphasize that a Digital Twin should be seen not as a technology, but as a process. It is a virtual representation of the real world, composed of synchronized processes at different levels of periodicity and fidelity. Unlike Building Information Modeling (BIM), Digital Twins are dynamic, connectable, and grounded, even though BIM serves as the basis for Digital Twins creating. These models integrate physical models, sensor updates, and historical information to simulate processes across disciplines, scales, and probabilities, mapping a virtual space that mirrors the corresponding element's life cycle (DONG et al., 2021). Kritzinger et al. (2018) classify Digital Twins into three categories: Digital Model, Digital Shadow, and Digital Twin. A Digital Model involves manual information exchange between the real and virtual worlds, without direct connection. In a Digital Shadow, information is automatically transferred from the physical to the digital model, but the reverse is manual. Digital Twins, however, feature automatic bidirectional information exchange. Digital Twins find extensive application in monitoring the life cycle of structures, construction stages, maintenance, and recovery works (OPOKU et al., 2021). They can also predictively analyze physical models, simulating how structures like bridges would behave under different circumstances. Sofia, Anas, and Faiz (2020) demonstrate the use of urban traffic data to estimate the load a bridge will endure over time, aiding in predicting its limitations and planning preventive measures to extend its useful life. Dong et al. (2021) predicts the useful life of an overhead crane using the Digital Twin, based on fatigue calculations. They employ various methods such as structural hot spot stress, local stress-strain, equivalent structural stress, and nominal stress. By extracting data from pressure, traction, laser distance measurement, and thermal expansion sensors, they create a model that detects defects, analyzes resistance, and predicts the crane's operating service time and residual time until the end of its operation. Web-based construction management hub software integrates Digital Twins with construction stages, enabling the anticipation of different scenarios at the construction site. This integration with project schedules enables simulations of different procedures, early fail detection, cost reduction, and more accurate planning (BENTLEY SYSTEMS, 2022b). Given the challenges of constructing and maintaining bridges, this work was held at the Research and Innovation Centre for Smart and Sustainable Cities (CEPIN-CIS) at IFSP Campus Caraguatatuba, aiming to evaluate the current state of Digital Twins for monitoring the structural health of reinforced and prestressed concrete bridges. It also aims to explore, through two case studies, how this technology can analyse and monitor key factors contributing to structural issues, thereby improving the longevity of bridges. This approach seeks to understand the Digital Twin's role in maintenance actions, thereby preventing closures and, in severe cases, bridge collapses. Despite the considerable resources required for their construction, including materials, time, and labour, bridges play a crucial role in enabling the freedom of movement for citizens. The application of Digital Twins in monitoring the structural health of bridges is a promising area, as evidenced by their projected market value of $63.5 billion in 2027 (PORTES, 2022). 2. Methods A thorough review of recent literature was conducted to explore the application of Digital Twins in the construction, maintenance, and monitoring of reinforced and prestressed concrete bridges. Given the limited availability of data on this topic, we rigorously conducted a systematic literature review to consolidate existing knowledge specifically related to Digital Twins in these bridge types. Our focus was to investigate how Digital Twins can be effectively utilized for monitoring the structural health of such bridges. To ensure relevance, we established strict inclusion and exclusion criteria for article selection, excluding