BIM and SHM Unite on a Massive Scale: Is This the Future of Bridge Safety?

A recent project in southwest China has demonstrated how building information modeling (BIM) can be effectively integrated with structural health monitoring (SHM) in a large-scale, real-world setting. Using a lightweight BIM model embedded into the web-client of an SHM system—via the skeleton-template method, CATIA platform, and sensor data—researchers explored the practical benefits of this combined approach on a butterfly arch bridge.

Study: Implementation of a BIM-Based Collaboration System for Structural Damage Condition Assessment in an Asymmetric Butterfly Arch Bridge. Image Credit: GaluhSekar/Shutterstock.com

Background

Ensuring the operational safety of in-service bridges is a global priority. Long-span bridges, in particular, face complex service conditions: continuous heavy traffic, environmental wear, and occasional extreme events like typhoons, earthquakes, or vehicle collisions. These factors make regular inspection and real-time structural monitoring essential.

While traditional SHM systems are widely used, they have notable limitations. Monitoring results often lag behind real-time conditions, they don’t clearly indicate damage location or severity, and they lack strong indicators for structural health evaluation. In contrast, BIM has been gaining traction in the construction industry for its strengths in visualization, coordination, and interdisciplinary integration.

Still, BIM’s use in SHM for large-scale bridges remains limited—mostly applied in smaller or more contained projects. This study aimed to address that gap by exploring how 3D modeling and sensor-based monitoring can work together to support SHM in complex infrastructure.

Methods

For this research, the Fu River butterfly arch bridge in Chengdu, China—constructed between 2012 and 2015—served as the case study. Engineers began by using the midas Civil software to analyze the bridge’s spatial mechanical characteristics and determine key structural monitoring points based on the original construction blueprints.

An SHM system was then designed to monitor several aspects of the bridge’s performance, including:

  • Bridge deflection
  • Stress in the arch rib and main girder
  • Vibration acceleration of the arch rib
  • Structural temperature
  • Cable force variation in suspenders and tied bars
  • Traffic load patterns

Sensor data was collected and transmitted wirelessly, enabling real-time evaluation of the bridge’s safety and performance.

To support data collaboration and visualization, BIM was integrated into the SHM system. CATIA was selected as the modeling platform, and the skeleton-template method was used to construct both primary bridge components and localized, parameterized elements of the butterfly arch structure.

Results and Discussion

Based on the structural analysis and monitoring requirements, a fully functional SHM system was developed. It included core modules for data acquisition, transmission, processing, control, analysis, and evaluation.

To improve performance and usability, lightweight modeling strategies were applied—such as simplifying model properties, reducing resolution, and compressing normal vector data. These adjustments resolved common issues like slow data access, poor display quality, and inefficient information sharing, ultimately improving the overall management experience of the BIM-SHM integration.

Monitoring data from the sensors was stored and updated in a SQL Server database. Within the BIM model, user-defined virtual sensor parameters were linked to this database, allowing real-time values to update automatically. In the event of a safety alert, the damage location could be instantly visualized within the BIM interface.

The system was tested when an overweight or oversized vehicle crossed the bridge. No irreversible damage was observed. The bridge's structural responses remained within design thresholds, and no fatigue damage was found in the tied bars or suspenders. These findings validated the effectiveness of the integrated BIM-SHM system for both visual assessment and early warning.

Conclusion and Future Prospects

This study offered a comprehensive look at how BIM and SHM technologies can be combined for long-span bridges, using the Fu River butterfly arch bridge as a real-world example. The resulting system provided an efficient way to monitor structural health in real time with visual feedback and early alerts.

However, there are still hurdles to wider adoption. Challenges include immature BIM tools for SHM use, the large volume of data produced, uncertain return on investment, and the lack of standardized procedures or legal frameworks. As bridge designs become more complex and infrastructure continues to grow, optimizing BIM-SHM integration will become even more important.

Looking ahead, the integration of cloud-based BIM, computational modeling, and advanced technologies like artificial intelligence, machine learning, digital reality capture, and big data analytics could further enhance system performance and address many of the current limitations.

Journal Reference

Qin, H. et al. (2025). Implementation of a BIM-Based Collaboration System for Structural Damage Condition Assessment in an Asymmetric Butterfly Arch Bridge. Buildings15(8), 1211. DOI: 10.3390/buildings15081211, https://www.mdpi.com/2075-5309/15/8/1211

Disclaimer: The views expressed here are those of the author expressed in their private capacity and do not necessarily represent the views of AZoM.com Limited T/A AZoNetwork the owner and operator of this website. This disclaimer forms part of the Terms and conditions of use of this website.

Nidhi Dhull

Written by

Nidhi Dhull

Nidhi Dhull is a freelance scientific writer, editor, and reviewer with a PhD in Physics. Nidhi has an extensive research experience in material sciences. Her research has been mainly focused on biosensing applications of thin films. During her Ph.D., she developed a noninvasive immunosensor for cortisol hormone and a paper-based biosensor for E. coli bacteria. Her works have been published in reputed journals of publishers like Elsevier and Taylor & Francis. She has also made a significant contribution to some pending patents.  

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