PSI - Issue 84

Alessandro Pucci et al. / Procedia Structural Integrity 84 (2026) 433–440

435

Defect identification is performed by analyzing the structured image dataset to detect visual anomalies, revealing surface deterioration. These anomalies are recognized either automatically by AI or, when necessary, by human assisted identification. Defect positioning exploits the spatial information derived from the image acquisition and photogrammetric processing stages. This approach ensures a consistent placement relative to the surrounding geometry; furthermore, allows defects on images to be accurately transferred to the 3D digital representation of the structure. Then, detected defects can be associated with the corresponding BIM elements (e.g., piers, girders, or abutments) and visualized both in the reconstructed 3D model and within the BIM environment (Fig. 1).

Fig. 1. (Left) crack detection in the image, (center) crack positioning onto the 3D textured model, (right) crack assignment to the pier BIM model (CEA).

The resulting defect dataset is thus both deeply descriptive and spatially explicit, establishing a robust link between image-based inspection findings and component-level digital models. This provides a reliable foundation for subsequent evaluation and assessment. The proposed analysis framework adopts a hierarchical, multi-level approach for the systematic evaluation of structural degradation and risk on bridge assets. The procedure is articulated into three main analytical levels — defect level, element level, and structure level — with an additional intermediate aggregation stage between the element and structure levels to ensure a coherent transfer of information across scales. At the defect level, each individual defect is characterized by a priority index: = 1 ⋅ 2 ⋅ (1) where k 1  [0.2, 0.5, 1] is the extent index, k 2  [0.2, 0.5, 1] is the intensity index, and G  [1, 2, …, 5] is the severity index, which depends on the defect category, material and element; thus, it is an indicator of the relevance to structural risk. At this level, the priority index p provides a localized and preliminary indication of defect criticality, as interactions among defects and their collective effects on the structural element are not yet considered. By contrast, at the element level, geometric information from individual defects is aggregated to evaluate the combined impact of multiple defects with varying spatial concentrations on a given structural element. To further clarify this point, the process is based on three main categories: (i) the defect category, (ii) the associated structural