An evidence-based risk decision support approach for metro tunnel construction
The risk-informed decision-making of metro tunnel project is often faced with the problem of inadequate utilization of available information. In order to address the epistemic uncertainty problem caused by insufficient utilization of information in decision-making, this paper proposes a risk decisi...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Vilnius Gediminas Technical University
2022-05-01
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| Series: | Journal of Civil Engineering and Management |
| Subjects: | |
| Online Access: | https://mla.vgtu.lt/index.php/JCEM/article/view/16807 |
| _version_ | 1828263909514018816 |
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| author | Yifan Guo Junjie Zheng Rongjun Zhang Youbin Yang |
| author_facet | Yifan Guo Junjie Zheng Rongjun Zhang Youbin Yang |
| author_sort | Yifan Guo |
| collection | DOAJ |
| description |
The risk-informed decision-making of metro tunnel project is often faced with the problem of inadequate utilization of available information. In order to address the epistemic uncertainty problem caused by insufficient utilization of information in decision-making, this paper proposes a risk decision support approach for metro tunnel construction based on Continuous Time Bayesian Network (CTBN) technique. CTBN can factor the state space of variables in tunnel projects and perform evidence-based reasoning, which enables the diverse information of expert opinions, project-specific parameters, historical data and engineering anomalies to be the evidence to support decision-making. A concise CTBN model development method based on Dynamic Fault Trees is presented to replace the cumbersome model learning process. The proposed approach can utilize multi-source information as evidence to provide multi-form decision support both in the pre-construction stage and construction stage of the tunnel construction project, and the results can support the decisions on judging the acceptability of the risk, developing response strategies for risk factors and diagnosing the causes of the hazardous event. A case study on the water leakage risk of tunnel construction in China is presented to illustrate the feasibility of the approach. The case study shows that the approach can assist in making informed decisions, so as to improve the engineering safety.
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| first_indexed | 2024-04-13T04:17:26Z |
| format | Article |
| id | doaj.art-503fd70c8e8d46c7b1a7a2a12710450f |
| institution | Directory Open Access Journal |
| issn | 1392-3730 1822-3605 |
| language | English |
| last_indexed | 2024-04-13T04:17:26Z |
| publishDate | 2022-05-01 |
| publisher | Vilnius Gediminas Technical University |
| record_format | Article |
| series | Journal of Civil Engineering and Management |
| spelling | doaj.art-503fd70c8e8d46c7b1a7a2a12710450f2022-12-22T03:02:56ZengVilnius Gediminas Technical UniversityJournal of Civil Engineering and Management1392-37301822-36052022-05-0128510.3846/jcem.2022.16807An evidence-based risk decision support approach for metro tunnel constructionYifan Guo0Junjie Zheng1Rongjun Zhang2Youbin Yang3School of Civil Engineering & Mechanics, Huazhong University of Science and Technology, Wuhan, ChinaSchool of Civil Engineering & Mechanics, Huazhong University of Science and Technology, Wuhan, ChinaSchool of Civil Engineering & Mechanics, Huazhong University of Science and Technology, Wuhan, ChinaChina Railway Siyuan Survey and Design Group Co., LTD, Kunming, China The risk-informed decision-making of metro tunnel project is often faced with the problem of inadequate utilization of available information. In order to address the epistemic uncertainty problem caused by insufficient utilization of information in decision-making, this paper proposes a risk decision support approach for metro tunnel construction based on Continuous Time Bayesian Network (CTBN) technique. CTBN can factor the state space of variables in tunnel projects and perform evidence-based reasoning, which enables the diverse information of expert opinions, project-specific parameters, historical data and engineering anomalies to be the evidence to support decision-making. A concise CTBN model development method based on Dynamic Fault Trees is presented to replace the cumbersome model learning process. The proposed approach can utilize multi-source information as evidence to provide multi-form decision support both in the pre-construction stage and construction stage of the tunnel construction project, and the results can support the decisions on judging the acceptability of the risk, developing response strategies for risk factors and diagnosing the causes of the hazardous event. A case study on the water leakage risk of tunnel construction in China is presented to illustrate the feasibility of the approach. The case study shows that the approach can assist in making informed decisions, so as to improve the engineering safety. https://mla.vgtu.lt/index.php/JCEM/article/view/16807Continuous Time Bayesian Networkevidencerisk-informed decision-makingtunnel constructionknowledgemulti-source information |
| spellingShingle | Yifan Guo Junjie Zheng Rongjun Zhang Youbin Yang An evidence-based risk decision support approach for metro tunnel construction Journal of Civil Engineering and Management Continuous Time Bayesian Network evidence risk-informed decision-making tunnel construction knowledge multi-source information |
| title | An evidence-based risk decision support approach for metro tunnel construction |
| title_full | An evidence-based risk decision support approach for metro tunnel construction |
| title_fullStr | An evidence-based risk decision support approach for metro tunnel construction |
| title_full_unstemmed | An evidence-based risk decision support approach for metro tunnel construction |
| title_short | An evidence-based risk decision support approach for metro tunnel construction |
| title_sort | evidence based risk decision support approach for metro tunnel construction |
| topic | Continuous Time Bayesian Network evidence risk-informed decision-making tunnel construction knowledge multi-source information |
| url | https://mla.vgtu.lt/index.php/JCEM/article/view/16807 |
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