Computational BIM and Intelligent Operations

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

P. Talasila, D. Tcherniak, A.M.D. Jensen, S. Mahato, A. Schörghofer-Queiroz, M.D. Ulriksen, G. Abbiati, P.G. Larsen, L. Damkilde

Published 2025

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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.

Topics

BIMPredictive Analytics and Performance Optimizationanomaly detectiondamage detectiondigital twinspredictive analyticspredictive maintenancestructural health monitoring

Cite this paper

@InProceedings{58b21833,
author="Talasila, P.
and Tcherniak, D.
and Jensen, A.M.D.
and Mahato, S.
and Sch{\"o}rghofer-Queiroz, A.
and Ulriksen, M.D.
and Abbiati, G.
and Larsen, P.G.
and Damkilde, L.",
editor="Caetano, Elsa
and Cunha, {\'A}lvaro",
title="Structural Health Monitoring of Engineering Structures Using Digital Twins: A Digital Twin Platform Approach",
booktitle="Experimental Vibration Analysis for Civil Engineering Structures",
year="2025",
publisher="Springer Nature Switzerland",
address="Cham",
pages="986--996",
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.",
isbn="978-3-031-96110-6",
url={https://doi.org/10.1007/978-3-031-96110-6_98},
}