Digital Twin-Based Investigation of a Building Collapse Accident
Autor(en): |
Zhe Zheng
Wenjie Liao Jiarui Lin Yucheng Zhou Chi Zhang Xinzheng Lu |
---|---|
Medium: | Fachartikel |
Sprache(n): | Englisch |
Veröffentlicht in: | Advances in Civil Engineering, Januar 2022, v. 2022 |
Seite(n): | 1-13 |
DOI: | 10.1155/2022/9568967 |
Abstrakt: |
The collapse of engineering structures can cause significant casualties and have negative social effects. Collapse accident investigation can elucidate the potential causes and mechanisms of the collapse accident, thus remediating future structural collapse and enhancing the resilience. However, there are some obstacles to investigating complicated collapse accidents using conventional methods. For example, the out-syncs between on-site investigation and simulation analysis are intractable and can make discovering the cause of collapse accidents difficult. Hence, a digital twin-based investigation method for collapse accidents was proposed. First, basic virtual digital building models are established using real-world information. Then, after mapping the data from the real world into the virtual space, the corresponding highly realistic multistage models before and after the building collapse accident are constructed and synchronized. Using the digital twin method, investigators with multidisciplinary knowledge can efficiently integrate, update, and check the models. Finally, the potential collapse mechanism was revealed with the assistance of the corresponding models. To demonstrate the effectiveness of the proposed digital twin-based investigation method, a real collapse accident investigation is utilized as an example. These results validated our method. |
Copyright: | © 2022 Zhe Zheng et al. et al. |
Lizenz: | Dieses Werk wurde unter der Creative-Commons-Lizenz Namensnennung 4.0 International (CC-BY 4.0) veröffentlicht und darf unter den Lizenzbedinungen vervielfältigt, verbreitet, öffentlich zugänglich gemacht, sowie abgewandelt und bearbeitet werden. Dabei muss der Urheber bzw. Rechteinhaber genannt und die Lizenzbedingungen eingehalten werden. |
8.57 MB
- Über diese
Datenseite - Reference-ID
10660749 - Veröffentlicht am:
28.03.2022 - Geändert am:
01.06.2022