TY - JOUR
T1 - Development and validation of graphics-based digital twin framework for UAV-aided post-earthquake inspection of high-rise buildings
AU - Wang, Jingjing
AU - Wu, Yongjingbang
AU - Wang, Shuo
AU - Narazaki, Yasutaka
AU - Liu, Hai
AU - Spencer, Billie F.
N1 - This work is supported by the National Natural Science Foundation of China (Nos. 51978182, 52020105002). The third author acknowledges the partial support of this research by the China Scholarship Council (No. 201706320312). The authors would like to acknowledge the efforts of Amirali Najafi, Nate Levine, Koji Tsuchimoto, Vedhus Hoskere, Casey Rodgers, Ziluo Yao, Sheng Jiang, Guanghao Zhai, Lixing Ma, and Jianying Lin for this research.
PY - 2024/9
Y1 - 2024/9
N2 - Traditional post-earthquake inspection of civil infrastructure is conducted manually, taking a considerable amount of time and often putting inspectors in harm's way. This problem is exacerbated in modern cities, where millions of people can be left homeless until their residences are deemed safe to reinhabit. Image collection enabled by commercial unmanned aerial vehicles (UAVs) combined with computer vision-based techniques has provided an alternative with high potential for rapid post-earthquake inspection. However, the extracted images of the damage alone are inadequate to evaluate the system-level safety condition of a structure. The quality of the visual information also heavily relies on the effectiveness of the UAV inspection scheme which is susceptible to environmental uncertainties. To this end, a graphics-based digital twin (GBDT) framework is developed for UAV-aided post-earthquake inspection of high-rise buildings and validated using a high-rise building in Guangzhou, China. The GBDT is comprised of a finite element (FE) model and a photorealistic computer graphics (CG) model, with the latter being informed by the former, jointly providing as a comprehensive virtual representation of the structure so that every step of the post-earthquake inspection procedure can be planned and evaluated virtually. First, to avoid the cumbersome nature of constructing the graphical representation of the numerous components in high-rise buildings, the CG model in the GBDT is created by automatically importing structural components from the FE model and adding nonstructural components according to the dimensions of the as-built structure. This fast modeling process as well as the accuracy of the virtual presentation are validated by point cloud comparisons between the CG model and the as-built structure. Subsequently, the GBDT is used to showcase the evaluation of UAV flight schemes for post-earthquake inspection of high-rise buildings. To shorten flight time and place more emphasis on potential damage, FE analysis is conducted to determine the earthquake-induced damage locations. Consistent damage hotspots are then marked on the CG model, along with restrictions from the real environment such as obstacles, weak satellite signal, wind speed, and lighting conditions considered in the synthetic environment. Finally, applying the synthetic environment as the testbed, three UAV-aided inspection schemes are implemented virtually and the best UAV flight scheme is determined for the assumed field inspection. This example demonstrates the flexibility of the GBDT in representing the real-world structure and environmental conditions and its efficacy in assisting decision making for rapid and effective structural inspection in the aftermath of an earthquake.
AB - Traditional post-earthquake inspection of civil infrastructure is conducted manually, taking a considerable amount of time and often putting inspectors in harm's way. This problem is exacerbated in modern cities, where millions of people can be left homeless until their residences are deemed safe to reinhabit. Image collection enabled by commercial unmanned aerial vehicles (UAVs) combined with computer vision-based techniques has provided an alternative with high potential for rapid post-earthquake inspection. However, the extracted images of the damage alone are inadequate to evaluate the system-level safety condition of a structure. The quality of the visual information also heavily relies on the effectiveness of the UAV inspection scheme which is susceptible to environmental uncertainties. To this end, a graphics-based digital twin (GBDT) framework is developed for UAV-aided post-earthquake inspection of high-rise buildings and validated using a high-rise building in Guangzhou, China. The GBDT is comprised of a finite element (FE) model and a photorealistic computer graphics (CG) model, with the latter being informed by the former, jointly providing as a comprehensive virtual representation of the structure so that every step of the post-earthquake inspection procedure can be planned and evaluated virtually. First, to avoid the cumbersome nature of constructing the graphical representation of the numerous components in high-rise buildings, the CG model in the GBDT is created by automatically importing structural components from the FE model and adding nonstructural components according to the dimensions of the as-built structure. This fast modeling process as well as the accuracy of the virtual presentation are validated by point cloud comparisons between the CG model and the as-built structure. Subsequently, the GBDT is used to showcase the evaluation of UAV flight schemes for post-earthquake inspection of high-rise buildings. To shorten flight time and place more emphasis on potential damage, FE analysis is conducted to determine the earthquake-induced damage locations. Consistent damage hotspots are then marked on the CG model, along with restrictions from the real environment such as obstacles, weak satellite signal, wind speed, and lighting conditions considered in the synthetic environment. Finally, applying the synthetic environment as the testbed, three UAV-aided inspection schemes are implemented virtually and the best UAV flight scheme is determined for the assumed field inspection. This example demonstrates the flexibility of the GBDT in representing the real-world structure and environmental conditions and its efficacy in assisting decision making for rapid and effective structural inspection in the aftermath of an earthquake.
KW - 3D synthetic environment
KW - UAV-aided inspection
KW - earthquake engineering
KW - graphics-based digital twin (GBDT)
KW - high-rise buildings
KW - post-earthquake inspection
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U2 - 10.1002/tal.2127
DO - 10.1002/tal.2127
M3 - Article
AN - SCOPUS:85192456948
SN - 1541-7794
VL - 33
JO - Structural Design of Tall and Special Buildings
JF - Structural Design of Tall and Special Buildings
IS - 13
M1 - e2127
ER -