## 6 Experimental Verification  
### System Performance  
Figure 12 shows the main interface of the developed BIM system. To verify the function and performance of the system, three case models extracted from Tekla software were used. As shown in Figure 13, model 1 is a medium-scale steel structural workshop, model 2 is a multi-story steel structural building, and model 3 is a large-scale steel structural workshop. The model parameters are listed in Table 1.  
Figure 11: Dynamic loading and switching of LODs. Figure 12: The main interface of the developed BIM system. Figure 13: Three test models: (**a**) model 1 medium-scale steel structural workshop; (**b**) model 2: multi-story steel structural building; and (**c**) model 3: large-scale steel structural workshop. As for the user interface, the developed system provided some interactive functions, such as displaying the component attribute information saved in the IFC file at the user's click position, as shown in Figure 14.  
The redundancy eliminate rate \(r\) is defined to evaluate the effect of redundancy removal function:  
\[r=1-\frac{s}{m} \tag{9}\]  
where \(m\) and \(s\) are the numbers of instances with geometric information before and after redundancy elimination, respectively. The redundancy elimination rate denotes the proportion of components identified as redundant in all components of the project, thus verifying the effectiveness of the redundancy removal approach. Table 2 lists the test results of the system performance by using the proposed approach of component redundancy removal. As indicated in Tables 2 and 3, the size of the created geometry file is almost the same as that of the original IFC file, which guarantees efficient network transmission and small space occupation. In addition, geometric information extraction takes less than 30 s, which can meet the requirement of the quasi-real-time visualization. It can also be seen in Table 3 that the average frame per second (FPS) is over 30 when rendering with low memory consumption. As for the redundancy elimination rate, more than 90% of the model components are identified as redundancy, especially in model 1 and model 3, where the redundancy elimination rates are more than 97%. Therefore, the redundancy elimination approach dramatically improves the performance of the system. For non-redundant instances, each of them is merged into a single drawcall when rendering, significantly reducing the overhead of hardware resources. Above all, the test results show that the proposed algorithms and techniques can greatly improve the system's performance and can support the quasi-real-time geometric information extraction and efficient display for large steel structural models. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Model Category** & **IFC File Size** & **Number of Instances in IFC File** & **Number of Properties** & **Number of Relationships** \\ \hline Model 1 & 15.4 MB & 29,178 & 8777 & 13,483 \\ Model 2 & 46.4 MB & 39,335 & 9649 & 13,941 \\ Model 3 & 61.8 MB & 112,897 & 24,460 & 44,668 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Test model parameters. Figure 14: Interactive interface and component information display. Taking the above three models as examples, LOD technology was also carried out to simplify their geometric information, and the shortest lengths of the folded edge were 0 mm (without mesh simplification), 10 mm, and 50 mm, respectively. The test results are listed in Table 3, which shows that the number of geometric instances is significantly reduced after simplification, and unnecessary details are omitted when observing from a long distance. It can also be suggested that with the increase in collapsed edge length, the number of instances is still primarily reserved, but the number of vertices and patches to be rendered is greatly reduced. Taking model 1 as an example, when the minimum edge length is 10 mm, 60.67% of vertices and 80.94% of triangular patches are omitted, indicating that some small instances are removed and the rest are simplified.