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System reliability of a gravity dam-foundation system using Bayesian networks

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  • Pei, Liang
  • Chen, Chen
  • He, Kun
  • Lu, Xiang

Abstract

Traditionally, the reliability of a gravity dam-foundation system is evaluated using several typical dam sections. However, the performance of different dam sections may vary greatly even under the same environment and loading conditions due to the different dam structures and geological conditions. Therefore, an improved method was proposed in this study to assess the system reliability of a gravity dam-foundation system more reasonably. Based on the synchronous load increment in the whole dam and the response surface method (RSM), the critical failure modes were determined, and the RSM agent models for the strength failure and instability failure performance functions were constructed. Through the Monte Carlo simulation and the Bayesian progressive deduction, the method of system reliability was proposed. The application results of a gravity dam showed that the reliability in different dam sections was different for the same loading and environment conditions, and the system safety assessment was unreasonable using several typical dam sections. The proposed method overcame the defects of excessively searching the failure path, distorting the failure probability assessment, and incompletely describing the characteristics of the system using the traditional methods. It provides a new method for the system reliability evaluation of large-scale and complex structural systems.

Suggested Citation

  • Pei, Liang & Chen, Chen & He, Kun & Lu, Xiang, 2022. "System reliability of a gravity dam-foundation system using Bayesian networks," Reliability Engineering and System Safety, Elsevier, vol. 218(PB).
    • Handle: RePEc:eee:reensy:v:218:y:2022:i:pb:s0951832021006621
    DOI: 10.1016/j.ress.2021.108178
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    1. Fluixá-Sanmartín, Javier & Escuder-Bueno, Ignacio & Morales-Torres, Adrián & Castillo-Rodríguez, Jesica Tamara, 2020. "Comprehensive decision-making approach for managing time dependent dam risks," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
    2. Morales-Torres, Adrián & Escuder-Bueno, Ignacio & Serrano-Lombillo, Armando & Castillo Rodríguez, Jesica T., 2019. "Dealing with epistemic uncertainty in risk-informed decision making for dam safety management," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    3. Eldosouky, AbdelRahman & Saad, Walid & Mandayam, Narayan, 2021. "Resilient critical infrastructure: Bayesian network analysis and contract-Based optimization," Reliability Engineering and System Safety, Elsevier, vol. 205(C).
    4. Yantao Zhu & Xinqiang Niu & Jimin Wang & Chongshi Gu & Qiang Sun & Bo Li & Lixian Huang, 2020. "A Risk Assessment Model for Dam Combining the Probabilistic and the Nonprobabilistic Methods," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-12, April.
    5. Liu, Xintian & Yu, Xueguang & Tong, Jiachi & Wang, Xu & Wang, Xiaolan, 2021. "Mixed uncertainty analysis for dynamic reliability of mechanical structures considering residual strength," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    6. Andreini, Marco & Gardoni, Paolo & Pagliara, Stefano & Sassu, Mauro, 2019. "Probabilistic models for the erosion rate in embankments and reliability analysis of earth dams," Reliability Engineering and System Safety, Elsevier, vol. 181(C), pages 142-155.
    7. Kun He & Liang Pei & Xiang Lu & Jiankang Chen & Zhenyu Wu, 2020. "Research and Application of Critical Failure Paths Identification Method for Dam Risk Analysis," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-10, September.
    8. Gang Wang & Zhenyue Ma, 2016. "Application of Probabilistic Method to Stability Analysis of Gravity Dam Foundation over Multiple Sliding Planes," Mathematical Problems in Engineering, Hindawi, vol. 2016, pages 1-12, June.
    9. Zhao, Wei & Fan, Feng & Wang, Wei, 2017. "Non-linear partial least squares response surface method for structural reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 161(C), pages 69-77.
    10. M. Peng & L. Zhang, 2012. "Analysis of human risks due to dam-break floods—part 1: a new model based on Bayesian networks," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 64(1), pages 903-933, October.
    11. Ching, Jianye & Leu, Sou-Sen, 2009. "Bayesian updating of reliability of civil infrastructure facilities based on condition-state data and fault-tree model," Reliability Engineering and System Safety, Elsevier, vol. 94(12), pages 1962-1974.
    12. Liu, Wenli & Chen, Elton J. & Yao, Erlei & Wang, Yanyu & Chen, Yangyang, 2021. "Reliability analysis of face stability for tunnel excavation in a dependent system," Reliability Engineering and System Safety, Elsevier, vol. 206(C).
    13. Khakzad, Nima & Khan, Faisal & Paltrinieri, Nicola, 2014. "On the application of near accident data to risk analysis of major accidents," Reliability Engineering and System Safety, Elsevier, vol. 126(C), pages 116-125.
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