ABSTRACT
As the significant number of European bridge stock comprises more than 100 years old masonry arch bridges, restrictions to the operation of these bridges or their closure due to increased traffic load can result in network disruptions with subsequent economic losses. Apparently, most of these bridges are carrying loads above those envisaged by their original designs. This paper presents the development of a framework for the digital twinning of masonry arch bridges to enhance their management and provide informed decisions for their repair and maintenance schemes. As a case study, a full-scale masonry arch bridge with a 3.0m span is considered here. The framework starts with the development of a 3D geometry using an innovative photogrammetry approach, which accurately captured the overall geometry and local irregularities of the masonry bridge. Afterwards, dynamic characteristics i.e., natural frequency and modal shape of the masonry arch bridge can be obtained from ambient vibration tests by instrumenting the bridge with accelerometers. A Bayesian approach is then implemented to identify structural modal properties under different time windows as a comparison for further assessments. Data from the developed 3D geometry (via photogrammetry) and modal properties are combined to develop a high-fidelity numerical model for structural analysis. This numerical model can be continuously calibrated using monitoring data from the testing of the masonry arch bridges under service loadings. The framework presented in this study has the potential to conduct an autonomous condition-based assessment of ageing masonry arch bridges, characterised by advanced real-time monitoring, and data-informed decisions to understand damage accumulation.
