| description abstract | Building information modeling (BIM) has been widely accepted in the industry and extensively used in supporting many construction tasks. In the government sector, the USDOT Federal Highway Administration (FHWA) has implemented building information modeling (BIM) for bridge construction. Hence, state DOTs are now faced with heightened pressure in complying with the FHWA’s Bridge Information Modeling (BrIM) standardization. Although BIM can provide many benefits to DOTs, current BIM-based platforms for bridges are not fully developed to process traditional two-dimensional (2D) bridge drawings for BIM-based computational tasks involving existing bridges, for example cost estimation. Bridges are a critical infrastructure in any nation’s economy, and by law the DOTs are tasked with ensuring that they remain safe for use. To maintain bridges, engineers currently perform periodic inspections, assessing each part of the bridge to identify areas that require maintenance. Maintenance work items are then generated for these areas; these are usually computed traditionally or by systems that still rely heavily on manual inputs. Such processes are time-consuming and cumbersome, and depend on years of bridge technical expertise. To overcome these limitations and improve the accuracy of processes such as generating maintenance work items for bridges, we propose a framework for automatically (1) processing existing 2D bridge drawings for bridges built pre-BIM adoption in the architecture, engineering, and construction (AEC) industry; (2) converting these record drawings into three-dimensional (3D) information models; and (3) converting 3D information models into industry foundation class (IFC) files. The developed 3D models using the proposed framework were compared against developed 3D models using the state-of-the-art method. Experimental results show that the developed framework can be used in developing algorithms that generate 3D models and IFC output files from portable document format (PDF) bridge drawings in a semiautomated fashion. The proposed method uses 3.33% of the time it takes the current state-of-the-art method to generate a 3D model, and the generated models are of comparative quality. | |
