BIM technology plays a crucial role during the bridge scheme demonstration stage, especially in the early phases of bridge engineering projects, where a progressively detailed demonstration process is essential.
The project’s feasibility study report forms the foundation for project approval. This report is based on gathering relevant data and considering the project’s long-term planning. It involves a systematic analysis of the project’s role within the road network and the broader transportation system, as well as its social and economic impact. At this stage, a preliminary construction plan is developed, outlining the project’s scale and main technical standards to demonstrate its necessity and feasibility.
Here, BIM concepts are applied to build a detailed 3D information model that validates the need for transportation engineering projects. This comprehensive model integrates traffic network data, including existing roads and alternative transportation modes in the area, along with social factors such as population, ethnicity, economic development, and political influences affecting the project route. It also incorporates critical geological and geographic information about natural features along the path.
Because the model is parametric and computational, it enables traffic flow predictions through calculations and analyses. This helps determine the project’s functional positioning and necessity more accurately. Compared to traditional evaluation methods, this approach allows project owners and planners to assess projects more intuitively and scientifically using information models.
BIM technology is also invaluable during the bridge design phase. Unlike architectural structural engineers, bridge professionals often act as both the “architects” and “structural engineers” of the bridge. In this phase, designers are responsible not only for creating cost-effective designs but also for performing modeling calculations—an extensive workload.
Currently, the modeling and calculation process often requires repeated adjustments and optimizations to be manually reflected in the drawings, leading to inefficiencies. However, if the modeling and computational models can be interconnected or unified under the same data model, this interactive approach can significantly improve efficiency and resolve many design-phase challenges.
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