Rintaro IKUMA

Construction of external environment digital twin for social infrastructure structures

Fuminori NAKAMURA

With the recent development of numerical simulation technology, it is becoming possible to predict the deterioration of structures. On the other hand, information engineering technologies such as ICT and IoT technologies are becoming available in various fields. Therefore, by combining numerical simulation technology developed in the civil engineering field with information engineering technology, it is possible to perform deterioration prediction analysis of concrete structures. In this research, we constructed an external environment prediction system for real structures that combines numerical simulation and virtual space technology.
The virtual space was constructed by combining photogrammetry using a drone and models in Unity. The numerical simulation incorporated models for solar radiation, wind distribution, and airborne salt distribution. We also demonstrated how to automatically acquire and save external environment information on the Web and synchronize it with the system. By combining these methods, it was shown that the external environmental effects of a real structure can be reproduced in virtual space.
Although the constructed virtual space has some rough parts, it is clear that the structure and its surrounding topography can be sufficiently reproduced using the virtual space. It was confirmed that the numerical simulation results were appropriately reflected in the solar radiation effect on the surface of the concrete structure, the spatial distribution of wind conditions around the target structure, and the spatial distribution of airborne salt.
From the above results, it is believed that by combining virtual space technology and numerical simulation, it is possible to easily confirm wind conditions and the distribution of airborne salt, which are difficult to visualize in real space, and is effective in managing structures. It was also shown that by combining numerical simulations calculated in advance, prediction time can be shortened and real-time predictions can be made.