The Risk Analysis of Dam Gate Based on Bayesian Network and Hydraulic Mechanics

Abstract:

Risk analysis is an important part of the dam safety risk management. The uncertain factors causing the failure of the gate is very complex, including the gate design and manufacturing, management operation, some man-made factors, etc. The traditional risk analysis method has certain limitation. Bayesian networks can quickly and effectively solve the failure probability of the system and for a direct analysis on the effects of every system component by a two-side inference, so as to locate the system weakness and adopt effective measures. This paper based on Bayesian network, through the example of Bayesian network in the application of dam gate risk analysis.

• Periodical: Advanced Materials Research (Volume 848)
• Pages: 112-116
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.848.112
• Online since: November 2013
• Authors: Guo Dong Ma, Hui Peng, Qiang Qiang Jiang, Mi Li, Jin Lai Zhang, Sheng Liang Wu
• Keywords: Bayesian Network (BN), Dam Safety, Failure Probability, Gate, Risk Analysis

References

[1] Langseth H, Portinale L . Bayesian networks in reliability [J]. Reliability Engineering and System Safety, 2007 , 92 ( 1) : 92-108.

DOI: 10.1016/j.ress.2005.11.037

[2] Jang Shu-hai , Fan Zi-wu, WU Shi-qiang . Flood risk assessment and control flood safety decision [M]. Beijing: China Water Resources and Hydropower Press, 2005, 86～87. ( in Chinese).

[3] Cooper, G. Computational complexity of probabilistic inference using Bayesian belief networks (Research note). Artificial Intelligence. 42: 393-405, (1990).

DOI: 10.1016/0004-3702(90)90060-d

[4] LI Dian-qing, YAN Li-li , SHAO Dong-guo. Reliability evaluation of earth -rock dams using Bayesian network [J]. Engineering Journal of Wuhan University, 2007, 40 (16) : 24-29 . ( in Chinese).

[5] ZHOU Jian-fang, TANG Chun-yan, XU Zhi-yong. Application of Bayesian networks to dam's risk analysis [J] . Journal of Hydroelectric Engineering. 2010, 29(1) : 192-196. ( in Chinese).

[6] JENSEN F V, NIELSEN T D. Bayesian networks and decision graphs [M]. New York: Springer, (2007).

[7] BROMLEY J, JACKSON N A, CLYMER O J, et al. The use of Hugin to develop Bayesian networks as an aid to integrated water resource planning [J]. Environmental Modelling & Software, 2005. 20: 231-242.

DOI: 10.1016/j.envsoft.2003.12.021

[8] STRAUB D, KIUREGHI AN A D. Combining Bayesian networks with structural reliability methods: methodology [J]. Journal of Engineering Mechanics, 2010. 136(10) : 1248-1258.

DOI: 10.1061/(asce)em.1943-7889.0000173

[9] Wang Guangyan , Ma Zhijun , Hu Qiwei . The fault tree analysis based on Bayesian networks [J]. Systems Engineering-Theory&Practice, 2004, 24(6): 76-83.

[10] Jang Shu-hai , Fan Zi-wu. Application of Bayesian method to the analysis of accident rate in the hydraulic water gate. [J] Journal of hydraulic engineering. 2006, 37(8): 945-949.

[11] Friis-Hansen A . Bayesian networks as a decision support tool in marine applications [ D ] . PhD thesis , Technical University of Denmark , 2001.

[12] Hartford D N D , Baecher G B. Risk and uncertainty in dam safety [ M ] . Thomas Telford , (2004).

[13] Li Jianchuan , Hu Niaoqing , Qin Guojun , et al. Application and construction of bayesian networks based on fault trees [J] . Computer Engineering and Applications, 2003, 24 : 225 – 228.