Building information modeling supported bridge structural health diagnosis and prognosis

Abstract

This study introduced a framework that facilitates bridge diagnostic and prognostic evaluations and related visualizations, leveraging building information modeling (BIM) techniques and data-driven structural health monitoring. Diagnostic and prognostic algorithms are proposed and able to provide intuitive and accessible structural insights via three-dimensional visualizations supported by the BIM techniques. Through the data communication channel established, virtual model information was successfully embedded into the bridge health evaluations, emphasizing the contribution of BIM techniques for data analysis. The proposed algorithms were applied to a case study of a reinforced concrete bridge. Strain distribution along the bridge deck was mapped in the 3D virtual model, which was able to precisely identify the critical location for potential damage. The residual fatigue life of different parts of the bridge deck was estimated and visualized by considering the main effects of traffic loading, exhibiting good alignments with the diagnostic results. The proposed framework is able to provide understandable and actionable structural information for stakeholders, facilitating the timely identification of structural issues and long-term planning of maintenance schedules.