Digital twin-based structural health monitoring and measurements of dynamic characteristics in balanced cantilever bridge

Abstract

This study developed a digital twin (DT) and structural health monitoring (SHM) system for a balanced cantilever bridge, utilizing advanced measurement techniques to enhance accuracy. Vibration and dynamic strain measurements were obtained using accelerometers and piezo-resistive strain gauges, capturing low-magnitude dynamic strains during operational vibrations. 3D-LiDAR scanning and Ultrasonic Pulse Velocity (UPV) tests captured the bridge's as-is geometry and modulus of elasticity. The resulting detailed 3D point cloud model revealed the structure's true state and highlighted discrepancies between the as-designed and as-built conditions. Dynamic properties, including modal frequencies and shapes, were extracted from the strain and acceleration measurements, providing critical insights into the bridge's structural behavior. The neutral axis depth, indicating stress distribution and potential damage, was accurately determined. Good agreement between vibration measurement data and the as-is model results validated the reliability of the digital twin model. Dynamic strain patterns and neutral axis parameters showed strong correlation with model predictions, serving as sensitive indicators of local damage. The baseline digital twin model and measurement results establish a foundation for future bridge inspections and investigations. This study demonstrates the effectiveness of combining digital twin technology with field measurements for real-time monitoring and predictive maintenance, ensuring the sustainability and safety of the bridge infrastructure, thereby enhancing its overall resilience to operational and environmental stressors.

Keywords

Digital twin / Structural health monitoring / Balanced cantilever bridge / 3D-LiDAR / Dynamic strain measurement

Relevance to resilience

This study advances infrastructure resilience through the integration of DT technology with SHM for a balanced cantilever bridge. This synergy facilitates real-time condition assessment and predictive maintenance, enabling proactive structural management. By leveraging 3D-LiDAR scanning, UPV tests, and dynamic strain measurements, the developed DT model accurately mirrors the bridge’s as-is conditions. This accurate representation is fundamental for the early detection of potential structural vulnerabilities and for enabling timely, informed interventions.

The validated DT-SHM framework contributes significantly to resilience-based management by enhancing preparedness and facilitating a more effective response to potential structural issues. It aims to minimize downtime and support rapid functional recovery following disruptive events, extend the bridge’s effective service life, and offers a scalable approach applicable to other critical urban infrastructure. Consequently, this research aids in maintaining the operational continuity of vital transportation assets, thereby reinforcing the overall resilience of urban networks.

CRediT authorship contribution statement

Tidarut Jirawattanasomkul: Writing - original draft, Visualization, Validation, Resources, Project administration, Funding acquisition, Conceptualization. Le Hang: Writing - original draft, Software, Methodology, Investigation, Formal analysis, Data curation. Supasit Srivaranun: Writing - review & editing, Validation, Project administration, Conceptualization. Suched Likitlersuang: Writing - review & editing, Supervision, Funding acquisition, Conceptualization. Pitcha Jongvivatsakul: Writing - review & editing, Validation. Wanchai Yodsudjai: Funding acquisition, Conceptualization. Punchet Thammarak: Software, Project administration, Methodology, Investigation, Data curation, Conceptualization.

Declaration of interests

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgement

This research is funded by the Thailand Science Research and Innovation Fund, Chulalongkorn University (BCG_FF_68_165_2100_027). The first author (Tidarut Jirawattanasomkul) also gratefully acknowledges support from the Grants for Development of New Faculty Staff, Ratchadaphiseksomphot Fund, Chulalongkorn University. The corresponding author (Supasit Srivaranun) acknowledges the Research and Innovation Funding from National Research Council of Thailand (No. N84A680208) and the Research Grant from Faculty of Engineering, Kasetsart University (No. 67/05/CE). The fourth author (Suched Likitlersuang) acknowledges Thailand Science Research and Innovation Fund Chulalongkorn University (DISF68210001) and the National Research Council of Thailand (NRCT): Grant No. N42A670572.

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