Reliability Estimation for the Joint Waterproof Facilities of Utility Tunnels Based on an Improved Bayesian Weibull Model
Safety issues are a major concern for the long-term maintenance and operation of utility tunnels, of which the focal point lies in the reliability of critical facilities. Conventional evaluation methods have failed to reflect the time-dependency and objectivity of the reliability of critical facilit...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-01-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/13/1/611 |
| _version_ | 1797626205523935232 |
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| author | Fang-Le Peng Yong-Kang Qiao Chao Yang |
| author_facet | Fang-Le Peng Yong-Kang Qiao Chao Yang |
| author_sort | Fang-Le Peng |
| collection | DOAJ |
| description | Safety issues are a major concern for the long-term maintenance and operation of utility tunnels, of which the focal point lies in the reliability of critical facilities. Conventional evaluation methods have failed to reflect the time-dependency and objectivity of the reliability of critical facilities, hence reducing the credibility of the analysis results and posing serious risks to the safety of utility tunnels. Taking joint waterproof facilities as an example, this paper focuses on the scientific problem of how to achieve a dynamic estimation of the reliability of critical facilities throughout the project life cycle of utility tunnels. To this end, an improved Weibull distribution model is proposed to incorporate the actual field conditions that affect the reliability of joint waterproof facilities of utility tunnels. Bayesian methods and Hamiltonian Monte Carlo methods are used to realize the posterior estimation of the model parameters via the observed failure data. The case study shows that the posterior prediction results fit well with the actual observation data. The proposed model can be used to estimate in real time such key reliability indicators as failure rate, failure warning time and expected failure time, which facilitate the safe operation and targeted maintenance of utility tunnels. |
| first_indexed | 2024-03-11T10:07:09Z |
| format | Article |
| id | doaj.art-b847b7b05b4649fbba77229059910943 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-11T10:07:09Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-b847b7b05b4649fbba772290599109432023-11-16T14:59:22ZengMDPI AGApplied Sciences2076-34172023-01-0113161110.3390/app13010611Reliability Estimation for the Joint Waterproof Facilities of Utility Tunnels Based on an Improved Bayesian Weibull ModelFang-Le Peng0Yong-Kang Qiao1Chao Yang2Research Center for Underground Space & Department of Geotechnical Engineering, Tongji University, Shanghai 200092, ChinaResearch Center for Underground Space & Department of Geotechnical Engineering, Tongji University, Shanghai 200092, ChinaResearch Center for Underground Space & Department of Geotechnical Engineering, Tongji University, Shanghai 200092, ChinaSafety issues are a major concern for the long-term maintenance and operation of utility tunnels, of which the focal point lies in the reliability of critical facilities. Conventional evaluation methods have failed to reflect the time-dependency and objectivity of the reliability of critical facilities, hence reducing the credibility of the analysis results and posing serious risks to the safety of utility tunnels. Taking joint waterproof facilities as an example, this paper focuses on the scientific problem of how to achieve a dynamic estimation of the reliability of critical facilities throughout the project life cycle of utility tunnels. To this end, an improved Weibull distribution model is proposed to incorporate the actual field conditions that affect the reliability of joint waterproof facilities of utility tunnels. Bayesian methods and Hamiltonian Monte Carlo methods are used to realize the posterior estimation of the model parameters via the observed failure data. The case study shows that the posterior prediction results fit well with the actual observation data. The proposed model can be used to estimate in real time such key reliability indicators as failure rate, failure warning time and expected failure time, which facilitate the safe operation and targeted maintenance of utility tunnels.https://www.mdpi.com/2076-3417/13/1/611reliability estimationjoint waterproof facilitiesutility tunnelimproved Weibull model |
| spellingShingle | Fang-Le Peng Yong-Kang Qiao Chao Yang Reliability Estimation for the Joint Waterproof Facilities of Utility Tunnels Based on an Improved Bayesian Weibull Model Applied Sciences reliability estimation joint waterproof facilities utility tunnel improved Weibull model |
| title | Reliability Estimation for the Joint Waterproof Facilities of Utility Tunnels Based on an Improved Bayesian Weibull Model |
| title_full | Reliability Estimation for the Joint Waterproof Facilities of Utility Tunnels Based on an Improved Bayesian Weibull Model |
| title_fullStr | Reliability Estimation for the Joint Waterproof Facilities of Utility Tunnels Based on an Improved Bayesian Weibull Model |
| title_full_unstemmed | Reliability Estimation for the Joint Waterproof Facilities of Utility Tunnels Based on an Improved Bayesian Weibull Model |
| title_short | Reliability Estimation for the Joint Waterproof Facilities of Utility Tunnels Based on an Improved Bayesian Weibull Model |
| title_sort | reliability estimation for the joint waterproof facilities of utility tunnels based on an improved bayesian weibull model |
| topic | reliability estimation joint waterproof facilities utility tunnel improved Weibull model |
| url | https://www.mdpi.com/2076-3417/13/1/611 |
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