Rapid seismic risk assessment of bridges using UAV aerial photogrammetry

This paper proposes a framework for rapid seismic risk assessment of bridges using aerial photogrammetric surveys conducted by Unmanned Aerial Vehicles (UAVs). First, the data acquisition process for the photogrammetric 3D reconstruction of an asset and the subsequent procedure for computer-vision-based automatic extraction of visible geometric features are presented. Then, the extracted features are combined in the structural models to perform a seismic risk assessment in terms of capacity-to-demand ratios. Uncertainties are related to the material and geometric hidden variables. Monte Carlo simulation is performed, assuming uniform (uninformed) distributions for the input variables affected by epistemic uncertainty. The ranges of such distributions are estimated based on engineering judgment and knowledge of construction practices. The analysis provides an estimate of the epistemic uncertainties of the capacity-to-demand ratios, with limited available information obtained from UAV aerial photogrammetry. The feasibility and applicability of the proposed framework are demonstrated through a case study of a simply supported bridge in the Italian highway network. The 3D reconstruction process is validated by comparing the aerial survey with a laser scanner survey. The seismic risk of the selected bridge is assessed using the geometric information obtained from the UAV aerial photogrammetric survey. Finally, the paper discusses the applicability of the proposed methodology for bridge management purposes in an automated framework and at network scale.