## 7 Conclusions  
To address the issue of efficient operation of the BIM platform for steel structures, several algorithms and techniques for improving extraction, storage, and visualization of BIM models were presented, and a high-performance BIM platform was developed accordingly. The main work and conclusions of this study are as follows:  
1. Several techniques of information extraction and storage based on IFC files were proposed. Because of the coupled IFC Tree, the complete extraction and lossless storage of building information from the IFC files seriously burden the network transmission. This study proposed several techniques to extract and decouple the geometric and semantic information of components from IFC files. Then, the spatial relationship and geometric information of components were stored in the form of files and cached on the client side, significantly reducing the overhead of database storage and network transmission. 2. An approach for the redundancy removal of component geometry information was proposed. Because of the large number of similar components in BIM models of steel structures, if the components with the same shape are not specially processed, the processing efficiency of geometry information and the performance of model visualization will be greatly affected. This study proposed an approach combining the PCA algorithm and the Hausdorff-based comparison algorithm to extract the geometric information and remove redundancy in the back end. Additionally, the models are cached in the front end, and the redundant instances are merged when rendering. Thus, the lightweight transmission and highly efficient display of BIM models can be reached. 3. A loading mechanism of multi-level LOD models was presented. In the BIM models of steel structures, there are beams and columns with larger geometric dimensions, as well as bolts, gusset plates, and welds with small dimensions. Different applied functions and observed positions require different display accuracy. Based on the edge collapsing algorithm, this study presented a loading mechanism of multi-level LOD models, which can be customized by users, significantly improving the display efficiency of models in coarse-grained visualization. The developed system was tested by using three steel structural models. By adopting the redundancy removal approach, the number of instances is decreased by 96.46% in less than 30 s and over 30 FPS is kept on the test machine when rendering. Adopting the LOD loading mechanism, 95.38% of vertices and 98.46% of patches are eliminated under 50 mm precision. Based on the optimized performance, a BIM platform for the construction management of steel structures was developed and applied to actual projects. The test results showed that the platform has good performance and can support the management of large-scale steel structural projects. Despite some progress made in developing a high-performance BIM platform for steel structures, this study has several limitations. The volume of semantic data extracted from IFC files remains substantial, posing potential network and database performance issues, especially when multiple models are loaded simultaneously. Additionally, the methods tailored specifically to steel structures may not be directly applicable to other types such as concrete structures, limiting broader industry applicability. The multi-level LOD model loading mechanism requires further refinement to handle very large and complex models without compromising visual accuracy or system performance. Furthermore, the current system has limited performance in managing multiple large models, necessitating improvements in caching mechanisms and version control. The inefficiencies in caching and version control can lead to slower data retrieval and potential inconsistencies. Future research should focus on optimizing semantic data management, refining LOD algorithms, and enhancing system architecture to ensure scalability, reliability, and broader applicability across various structural types. Conceptualization, J.W.