Colin Caprani

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Research theme

Structural Health Monitoring

Sensors turn a bridge from a drawing into a measured object. Monitoring reveals how a structure actually behaves under load, which is often less conservative than the assessment assumes, and it can catch problems an occasional inspection would miss. The harder question is when monitoring is worth its cost, and what to do with what it tells you.

Our contributions

We design and install monitoring systems in the field, frequently to clear the safe passage of 600-tonne superloads across ageing bridges, and develop the value-of-information methods that decide when monitoring pays. The work combines sensing, probabilistic model updating and reliability.

People

Samadhi Loku Hettiarachchilage
PhD candidate · Bridge structural health monitoring under moving loads using real-time sensor data
Zaid Mir Rangrez
Postdoc · Machine learning for value of information in monitoring
Shihab Khan
Alumnus · A comprehensive value-of-information framework for quantifying SHM benefits
Yordanos Lemma
PhD candidate · Self-diagnosing monitoring: Bayesian fault detection & outlier categorisation in SHM systems
Amirhossein Eslamikhouzani
Alumnus · Drive-by bridge inspection: instrumented wagons for SHM of rail bridges
Ziyi Zhou
Postdoc · Automation & robotics for civil structures

Selected publications · 18 in this area

  1. Z. Y. M. Rangreza, J. Ghosh, C. Caprani, S. Ghosh (2025). Integrating risk perceptions in a value of information framework using cumulative prospect theory. Structural Safety doi ↗
  2. F. Shaker, C. C. Caprani (2023). A Modern Bayesian Approach to Model Updating of Bridges Considering Measurement Uncertainty. Proceedings of the 14th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP14
  3. M. S. Khan, C. C. Caprani (2023). A value of information framework for quantifying the value of reliability assessment for a steel railway truss bridge. Proceedings of the 14th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP14
  4. Z. Y. Mir Rangrez, J. Ghosh, C. Caprani, S. Ghosh (2023). Value of information under random decision, model, and measurement errors. Proceedings of the International Association for Life-Cycle Civil Engineering (IALCCE)
  5. M. S. Khan, C. Caprani, S. Ghosh, J. Ghosh (2022). Value of strain-based structural health monitoring as decision support for heavy load access to bridges. Structure and Infrastructure Engineering doi ↗
  6. S. Zhang, C. Caprani, M. Melhem, A. Ng, N. Hodgins (2021). Use of structural health monitoring for assessing historical bridges under heavy loads. 10th International Conference on Bridge Maintenance, Safety and Management, Sapporo, Japan doi ↗
  7. M. S. Khan, C. Caprani, S. Ghosh, J. Ghosh (2021). Value of structural health monitoring for bridges subjected to severe loads. Bridge Maintenance, Safety, Management, Life-Cycle Sustainability and Innovations - Proceedings of the 10th International Conference on Bridge Maintenaince, Safety and Management, IABMAS 2020 doi ↗
  8. M. S. Khan, S. Ghosh, C. Caprani, J. Ghosh (2020). Sensitivity of Value of Information to Model and Measurement Errors. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering doi ↗
  9. N. Powers, D. M. Frangopol, R. Al-Mahaidi, C. Caprani, Y. Tsompanakis (2020). Maintenance, monitoring, risk and life-cycle performance of bridges. Structure and Infrastructure Engineering doi ↗
  10. J. W. Ngan, C. C. Caprani, Y. Bai (2020). Numerical validation framework of GFRP floor models using structural health monitoring. ACMSM25 doi ↗

All publications →