3D model data of digital twin in seismic emergency inspection of road bridges

After an earthquake, it is crucial to judge the necessity of traffic regulation and implement emergency measures based on load-bearing capacity and drivability to facilitate early road clearance. The diagnose on road bridges has traditionally relied on past earthquake damage and recovery response record as a reference, however, inconsistencies in diagnostic results have become an issue. Additionally, considering the shortage of engineers during disasters and the need of lightening their workload, it is urgent to develop emergency inspection methods that enable them to diagnose remotely. Therefore, we examined a remote diagnostic system using digital twins as a new emergency inspection method. 

Totally 5 bridges were scanned after earthquake, the 2024 Noto Peninsula Earthquake 1st January, by portable LiDAR Scanner Matterport Pro3. This dataset includes the 3d data of the 5 Bridges (A~E). The 3d data of the bridges were saved separately as e57 file, named as Bridge A~E. The E57 file is data format of LiDAR Point Cloud data file.