Inspection-informed finite element model updating of a steel bridge using BIM-based damage mapping and modal correlation

Abstract

The calibration of structural models using field data is essential for improving the reliability of bridge assessment and the consistency of numerical simulations. This study presents an inspection-informed model updating approach for a real-world steel pedestrian bridge by integrating experimental modal data, BIM-based damage information, and finite element analysis results. The post-calibration consistency assessment is carried out using natural frequency comparison and the Modal Assurance Criterion (MAC). The proposed framework introduces a semi-automated workflow in which inspection-based damage grades stored in a BIM model are transferred to the finite element model via element identifiers. Damage is represented through inspection-based stiffness modifiers, while a global calibration parameter accounts for modelling uncertainties. This formulation enables a structured combination of inspection-based local stiffness modifiers and global model correction, improving the interpretability of the updated parameters. Field measurements were obtained using accelerometers under ambient excitation, and operational modal analysis was applied to identify natural frequencies and mode shapes. These results were compared with a finite element model, in which damage information from a Revit-based inspection dataset was semi-automatically mapped and incorporated into the numerical model. A constrained optimisation process was used to calibrate the damage coefficients and global stiffness factor by minimising the difference between numerical and experimental natural frequencies. The results show a reduction in frequency discrepancies and an improvement in modal correlation after calibration. The results show that the proposed approach enables a transparent and repeatable integration of inspection data into finite element model updating, particularly at the global level. Although the level of improvement remains moderate, the calibration process is constrained by inspection data and modelling assumptions, supporting a consistent interpretation of the calibrated parameters. The framework, therefore, prioritises consistency and transparency over purely numerical fitting, supporting more reliable structural assessment.