Raw point clouds of build structures do not provide semantic nor component level information. Automatic bridge information model generation from point cloud data would remedy this issue. This paper describes, applies, and evaluates a strategy for top-down partitioning of reinforced concrete bridges into structurally distinct component regions for girder, box girder, and slab bridges. The first phase is a user-guided denoising and coordinate frame specification process. The second phase utilizes the reference frame and geometric heuristics to identify the individual spans and whether the bridge contains AASHTO girders or not. It identifies cutting surfaces to apply for partitioning the bridge. The third phase identifies the substructure, superstructure, and deck components. This process either merges partitioned regions or further partitions regions to isolate bridge components with different functions. Isolated components include the girders/boxes/slabs, the piers, the abutments, the diaphragms, the road, and the parapets. The final coarse bridge model has a level of detail from 100 to 200. Application to four bridges demonstrates the low processing time and high partitioning accuracy, and provides visualizations of the IFC bridge model output.
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