Structural Health Monitoring of Engineering Structures Using Digital Twins: A Digital Twin Platform Approach

Research output: Contribution to book/anthology/report/proceedingArticle in proceedingsResearchpeer-review

Abstract

Engineering structures such as bridges and wind farms need to have a long useful lifetime. Structural Health Monitoring (SHM) via predictive simulations may be valuable towards lifetime extension. Digital Twins (DTs) are a suitable technology for such SHM, automated interventions, and providing analytical insights. In this paper, we present the Digital Twin as a Service (DTaaS), which is a collaborative online platform for management of DTs. This platform eases the task of building, using, and sharing DTs in a collaborative environment. The DTaaS provides real-time communication capabilities to link DTs with engineering structures, which helps with updating the models used in the DTs and thereby improving the prediction accuracy offered by SHM systems. The capabilities of the DTaaS are exemplified in the context of a wind turbine case study, in which a DT of the jacket-pile foundation is developed based on experimental data.

Original languageEnglish
Title of host publicationExperimental Vibration Analysis for Civil Engineering Structures, EVACES 2025 - Volume 1
EditorsÁlvaro Cunha, Elsa Caetano
Number of pages11
PublisherSpringer Science and Business Media Deutschland GmbH
Publication date2025
Pages986-996
ISBN (Print)9783031961090
DOIs
Publication statusPublished - 2025
Event11th International Conference on Experimental Vibration Analysis for Civil Engineering Structures, EVACES 2025 - Porto, Portugal
Duration: 2 Jul 20254 Jul 2025

Conference

Conference11th International Conference on Experimental Vibration Analysis for Civil Engineering Structures, EVACES 2025
Country/TerritoryPortugal
CityPorto
Period02/07/202504/07/2025
Series Lecture Notes in Civil Engineering
Volume674 LNCE
ISSN2366-2557

Keywords

  • Digital Twin Platform
  • Jacket-Pile Foundation
  • Offshore Wind Turbine
  • Structural Health Monitoring

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