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Utilization of Digital Twins for Bridge Inspection, Monitoring and Maintenance
https://orcid.org/http://orcid.org/0000-0002-4969-3085
https://orcid.org/http://orcid.org/0000-0001-6523-2687
https://orcid.org/http://orcid.org/0000-0002-3799-2248
New communication and information systems and technologies (ICT - Information and Communication Technologies) have great potential to aggregate new functionalities and services to inspect, monitor, and manage bridges and other infrastructure assets. Digital Transformation can reduce maintenance costs (avoiding unnecessary maintenance events) and improve system availability, reducing operational losses. The use of Big Data Analytics, incorporating Artificial Intelligence and Machine Learning, are innovative solutions that can be introduced. The adoption of Digital Twins, which incorporate all these elements, can lead to a reduction in the total cost, allowing predictive and proactive maintenance. The implementation of any digital twin requires the construction of a 3D model with the most efficient representation of geometry, material properties, internal connections, and boundary conditions, as well as ground localization information. In the particular case of a bridge, the digital twin may incorporate and manage drawings, spreadsheets, documents, and technical reports, regarding its design and construction, as well as regulatory provisions utilized, in an easy and comprehensive way. All the data is stored and managed using Cloud Computing. All the information is provided graphically to the users in real-time, providing important subsidies for the decision-making and prioritization processes involved in the bridge maintenance. Risk-based predictive maintenance helps to determine the optimal time and date when repairing activities should be performed, offering cost savings over routine or preventive maintenance. The development of a Digital Twin for a railway bridge (incorporating the described features) is illustrated in this paper.
Utilization of Digital Twins for Bridge Inspection, Monitoring and Maintenance
https://orcid.org/http://orcid.org/0000-0002-4969-3085
https://orcid.org/http://orcid.org/0000-0001-6523-2687
https://orcid.org/http://orcid.org/0000-0002-3799-2248
New communication and information systems and technologies (ICT - Information and Communication Technologies) have great potential to aggregate new functionalities and services to inspect, monitor, and manage bridges and other infrastructure assets. Digital Transformation can reduce maintenance costs (avoiding unnecessary maintenance events) and improve system availability, reducing operational losses. The use of Big Data Analytics, incorporating Artificial Intelligence and Machine Learning, are innovative solutions that can be introduced. The adoption of Digital Twins, which incorporate all these elements, can lead to a reduction in the total cost, allowing predictive and proactive maintenance. The implementation of any digital twin requires the construction of a 3D model with the most efficient representation of geometry, material properties, internal connections, and boundary conditions, as well as ground localization information. In the particular case of a bridge, the digital twin may incorporate and manage drawings, spreadsheets, documents, and technical reports, regarding its design and construction, as well as regulatory provisions utilized, in an easy and comprehensive way. All the data is stored and managed using Cloud Computing. All the information is provided graphically to the users in real-time, providing important subsidies for the decision-making and prioritization processes involved in the bridge maintenance. Risk-based predictive maintenance helps to determine the optimal time and date when repairing activities should be performed, offering cost savings over routine or preventive maintenance. The development of a Digital Twin for a railway bridge (incorporating the described features) is illustrated in this paper.
Utilization of Digital Twins for Bridge Inspection, Monitoring and Maintenance
https://orcid.org/http://orcid.org/0000-0002-4969-3085
https://orcid.org/http://orcid.org/0000-0001-6523-2687
https://orcid.org/http://orcid.org/0000-0002-3799-2248
New communication and information systems and technologies (ICT - Information and Communication Technologies) have great potential to aggregate new functionalities and services to inspect, monitor, and manage bridges and other infrastructure assets. Digital Transformation can reduce maintenance costs (avoiding unnecessary maintenance events) and improve system availability, reducing operational losses. The use of Big Data Analytics, incorporating Artificial Intelligence and Machine Learning, are innovative solutions that can be introduced. The adoption of Digital Twins, which incorporate all these elements, can lead to a reduction in the total cost, allowing predictive and proactive maintenance. The implementation of any digital twin requires the construction of a 3D model with the most efficient representation of geometry, material properties, internal connections, and boundary conditions, as well as ground localization information. In the particular case of a bridge, the digital twin may incorporate and manage drawings, spreadsheets, documents, and technical reports, regarding its design and construction, as well as regulatory provisions utilized, in an easy and comprehensive way. All the data is stored and managed using Cloud Computing. All the information is provided graphically to the users in real-time, providing important subsidies for the decision-making and prioritization processes involved in the bridge maintenance. Risk-based predictive maintenance helps to determine the optimal time and date when repairing activities should be performed, offering cost savings over routine or preventive maintenance. The development of a Digital Twin for a railway bridge (incorporating the described features) is illustrated in this paper.
Utilization of Digital Twins for Bridge Inspection, Monitoring and Maintenance
Lecture Notes in Civil Engineering
Pellegrino, Carlo (editor) / Faleschini, Flora (editor) / Zanini, Mariano Angelo (editor) / Matos, José C. (editor) / Casas, Joan R. (editor) / Strauss, Alfred (editor) / Futai, M. M. (author) / Bittencourt, T. N. (author) / Santos, R. R. (author) / Araújo, C. R. R. (author)
International Conference of the European Association on Quality Control of Bridges and Structures ; 2021 ; Padua, Italy
2021-12-12
8 pages
Article/Chapter (Book)
Electronic Resource
English
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