Intelligent Risk Prognosis and Control of Foundation Pit Excavation Based on Digital Twin
Timely risk information acquisition and diagnosis during foundation pit excavation (FPE) processes are vital for ensuring the safe and effective construction of underground urban infrastructures. Unfortunately, diverse geological and hydrogeological conditions and complex shapes of the foundation pi...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-01-01
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| Series: | Buildings |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2075-5309/13/1/247 |
| _version_ | 1797444932424695808 |
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| author | Zhe Sun Haoyang Li Yan Bao Xiaolin Meng Dongliang Zhang |
| author_facet | Zhe Sun Haoyang Li Yan Bao Xiaolin Meng Dongliang Zhang |
| author_sort | Zhe Sun |
| collection | DOAJ |
| description | Timely risk information acquisition and diagnosis during foundation pit excavation (FPE) processes are vital for ensuring the safe and effective construction of underground urban infrastructures. Unfortunately, diverse geological and hydrogeological conditions and complex shapes of the foundation pit create barriers for reliable FPE risk prognosis and control. Furthermore, typical support systems during FPE use temporary measures, which have limited capacity to confront excessive loads, large deformations, and seepage. This study aims to establish an intelligent risk prognosis and control framework based on digital twin (DT) for ensuring safe and effective FPE processes. Previous studies have conducted extensive experimental and numerical analyses for examining unsafe conditions during FPE. How to enable intelligent risk prognosis and control of tedious FPE processes by integrating physics-based models and sensory data collected in the field is still challenging. DT could help to establish the interaction and feedback mechanisms between the physical and virtual space. In this study, the authors have established a DT model that consists of a physical space model and a high-fidelity physics-based model of a foundation pit in virtual space. As a result, a mechanism for effective acquisition and fusion of heterogeneous information from both physical and virtual space is established. Then, the authors proposed an integrated model and data-driven approach for examining safety risks during FPE. In the end, the authors have validated the proposed method through a case study of the FPE of the Wuhan Metro Line. The results show that the proposed method could provide theoretical and practical support for future intelligent FPE. |
| first_indexed | 2024-03-09T13:19:34Z |
| format | Article |
| id | doaj.art-87be3490bea2425da31e564b50ef96eb |
| institution | Directory Open Access Journal |
| issn | 2075-5309 |
| language | English |
| last_indexed | 2024-03-09T13:19:34Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Buildings |
| spelling | doaj.art-87be3490bea2425da31e564b50ef96eb2023-11-30T21:32:00ZengMDPI AGBuildings2075-53092023-01-0113124710.3390/buildings13010247Intelligent Risk Prognosis and Control of Foundation Pit Excavation Based on Digital TwinZhe Sun0Haoyang Li1Yan Bao2Xiaolin Meng3Dongliang Zhang4Faculty of Architecture, Civil and Transportation Engineering, Beijing University of Technology, Beijing 100124, ChinaSchool of Mechanics and Civil Engineering, China University of Mining and Technology-Beijing, Beijing 100083, ChinaFaculty of Architecture, Civil and Transportation Engineering, Beijing University of Technology, Beijing 100124, ChinaFaculty of Architecture, Civil and Transportation Engineering, Beijing University of Technology, Beijing 100124, ChinaFaculty of Architecture, Civil and Transportation Engineering, Beijing University of Technology, Beijing 100124, ChinaTimely risk information acquisition and diagnosis during foundation pit excavation (FPE) processes are vital for ensuring the safe and effective construction of underground urban infrastructures. Unfortunately, diverse geological and hydrogeological conditions and complex shapes of the foundation pit create barriers for reliable FPE risk prognosis and control. Furthermore, typical support systems during FPE use temporary measures, which have limited capacity to confront excessive loads, large deformations, and seepage. This study aims to establish an intelligent risk prognosis and control framework based on digital twin (DT) for ensuring safe and effective FPE processes. Previous studies have conducted extensive experimental and numerical analyses for examining unsafe conditions during FPE. How to enable intelligent risk prognosis and control of tedious FPE processes by integrating physics-based models and sensory data collected in the field is still challenging. DT could help to establish the interaction and feedback mechanisms between the physical and virtual space. In this study, the authors have established a DT model that consists of a physical space model and a high-fidelity physics-based model of a foundation pit in virtual space. As a result, a mechanism for effective acquisition and fusion of heterogeneous information from both physical and virtual space is established. Then, the authors proposed an integrated model and data-driven approach for examining safety risks during FPE. In the end, the authors have validated the proposed method through a case study of the FPE of the Wuhan Metro Line. The results show that the proposed method could provide theoretical and practical support for future intelligent FPE.https://www.mdpi.com/2075-5309/13/1/247digital twinfoundation pit excavationrisk prognosis and controlconstruction safety |
| spellingShingle | Zhe Sun Haoyang Li Yan Bao Xiaolin Meng Dongliang Zhang Intelligent Risk Prognosis and Control of Foundation Pit Excavation Based on Digital Twin Buildings digital twin foundation pit excavation risk prognosis and control construction safety |
| title | Intelligent Risk Prognosis and Control of Foundation Pit Excavation Based on Digital Twin |
| title_full | Intelligent Risk Prognosis and Control of Foundation Pit Excavation Based on Digital Twin |
| title_fullStr | Intelligent Risk Prognosis and Control of Foundation Pit Excavation Based on Digital Twin |
| title_full_unstemmed | Intelligent Risk Prognosis and Control of Foundation Pit Excavation Based on Digital Twin |
| title_short | Intelligent Risk Prognosis and Control of Foundation Pit Excavation Based on Digital Twin |
| title_sort | intelligent risk prognosis and control of foundation pit excavation based on digital twin |
| topic | digital twin foundation pit excavation risk prognosis and control construction safety |
| url | https://www.mdpi.com/2075-5309/13/1/247 |
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