Digital Twin-based Safety Evaluation of Prestressed Steel Structure
The safety of prestressed steel structures in service has been studied widely. However, traditional safety assessment methods for prestressed steel structures involve few sample points, do not provide accurate predictions, and consume substantial human and material resources. The digital twin techno...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2020-01-01
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| Series: | Advances in Civil Engineering |
| Online Access: | http://dx.doi.org/10.1155/2020/8888876 |
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| _version_ | 1849407608832655360 |
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| author | Zhansheng Liu Wenyan Bai Xiuli Du Anshan Zhang Zezhong Xing Antong Jiang |
| author_facet | Zhansheng Liu Wenyan Bai Xiuli Du Anshan Zhang Zezhong Xing Antong Jiang |
| author_sort | Zhansheng Liu |
| collection | DOAJ |
| description | The safety of prestressed steel structures in service has been studied widely. However, traditional safety assessment methods for prestressed steel structures involve few sample points, do not provide accurate predictions, and consume substantial human and material resources. The digital twin technology can be used to monitor the structural behavior, state, and activity of a steel structure throughout its life cycle, which is equivalent to performing a safety assessment of the structure. The purpose of this study is to establish a digital twin multidimensional model of prestressed steel structures. Based on this model, the support vector machine and prediction model are trained using the relevant structural history data, and the safety risk level of the structure is then predicted based on the measured data. Finally, a proportional reduction model of the wheel-spoke cable truss structure is used to verify the feasibility of the proposed method. The results show that digital twin technology can achieve real-time monitoring of prestressed steel structures in use and can provide timely predictions of the safety level. This represents a new method for the safety risk assessment of prestressed steel structures. |
| format | Article |
| id | doaj-art-4840ac8754f441c2be828945cafc2bf4 |
| institution | Kabale University |
| issn | 1687-8086 1687-8094 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Civil Engineering |
| spelling | doaj-art-4840ac8754f441c2be828945cafc2bf42025-08-20T03:36:01ZengWileyAdvances in Civil Engineering1687-80861687-80942020-01-01202010.1155/2020/88888768888876Digital Twin-based Safety Evaluation of Prestressed Steel StructureZhansheng Liu0Wenyan Bai1Xiuli Du2Anshan Zhang3Zezhong Xing4Antong Jiang5The Key Laboratory of Urban Security and Disaster Engineering of Ministry of Education, Beijing University of Technology, Beijing 100124, ChinaThe Key Laboratory of Urban Security and Disaster Engineering of Ministry of Education, Beijing University of Technology, Beijing 100124, ChinaThe Key Laboratory of Urban Security and Disaster Engineering of Ministry of Education, Beijing University of Technology, Beijing 100124, ChinaThe Key Laboratory of Urban Security and Disaster Engineering of Ministry of Education, Beijing University of Technology, Beijing 100124, ChinaThe Key Laboratory of Urban Security and Disaster Engineering of Ministry of Education, Beijing University of Technology, Beijing 100124, ChinaThe Key Laboratory of Urban Security and Disaster Engineering of Ministry of Education, Beijing University of Technology, Beijing 100124, ChinaThe safety of prestressed steel structures in service has been studied widely. However, traditional safety assessment methods for prestressed steel structures involve few sample points, do not provide accurate predictions, and consume substantial human and material resources. The digital twin technology can be used to monitor the structural behavior, state, and activity of a steel structure throughout its life cycle, which is equivalent to performing a safety assessment of the structure. The purpose of this study is to establish a digital twin multidimensional model of prestressed steel structures. Based on this model, the support vector machine and prediction model are trained using the relevant structural history data, and the safety risk level of the structure is then predicted based on the measured data. Finally, a proportional reduction model of the wheel-spoke cable truss structure is used to verify the feasibility of the proposed method. The results show that digital twin technology can achieve real-time monitoring of prestressed steel structures in use and can provide timely predictions of the safety level. This represents a new method for the safety risk assessment of prestressed steel structures.http://dx.doi.org/10.1155/2020/8888876 |
| spellingShingle | Zhansheng Liu Wenyan Bai Xiuli Du Anshan Zhang Zezhong Xing Antong Jiang Digital Twin-based Safety Evaluation of Prestressed Steel Structure Advances in Civil Engineering |
| title | Digital Twin-based Safety Evaluation of Prestressed Steel Structure |
| title_full | Digital Twin-based Safety Evaluation of Prestressed Steel Structure |
| title_fullStr | Digital Twin-based Safety Evaluation of Prestressed Steel Structure |
| title_full_unstemmed | Digital Twin-based Safety Evaluation of Prestressed Steel Structure |
| title_short | Digital Twin-based Safety Evaluation of Prestressed Steel Structure |
| title_sort | digital twin based safety evaluation of prestressed steel structure |
| url | http://dx.doi.org/10.1155/2020/8888876 |
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