长江科学院院报 ›› 2021, Vol. 38 ›› Issue (5): 137-143.DOI: 10.11988/ckyyb.20200137

• 水工结构与材料 • 上一篇    下一篇

基于动态贝叶斯网络的混凝土坝失事风险分析

李宗坤1,2, 王特1, 葛巍1,3, 郑艳1   

  1. 1.郑州大学 水利科学与工程学院, 郑州 450001;
    2.郑州大学 软件学院, 郑州 450002;
    3.代尔夫特理工大学 技术、政策和管理学院,荷兰 代尔夫特 2628 BX
  • 收稿日期:2020-02-24 修回日期:2020-06-15 出版日期:2021-05-01 发布日期:2021-05-17
  • 通讯作者: 王 特(1996-),男,河南新野人,博士研究生,主要从事大坝风险评价与管理研究。E-mail: 2433405642@qq.com
  • 作者简介:李宗坤(1961-),男,河南邓州人,教授,博士,博士生导师,主要从事水利工程风险评价与管理研究。E-mail: lizongkun@zzu.edu.cn
  • 基金资助:
    国家自然科学基金项目(51709239,51679222,51379192);中国博士后科学基金项目(2018M632809);河南省科技攻关项目(182102311070);河南省高等学校重点科研项目(18A570007)

Risk Analysis of Concrete Dam Breach Based on Dynamic Bayesian Network

LI Zong-kun1,2, WANG Te1, GE Wei1,3, ZHENG Yan1   

  1. 1. School of Water Conservancy Engineering, Zhengzhou University, Zhengzhou 450001, China;
    2. School of Software, Zhengzhou University, Zhengzhou 450002, China;
    3. Faculty of Technology, Policy and Management, Delft University of Technology, Delft 2628 BX, The Netherlands
  • Received:2020-02-24 Revised:2020-06-15 Online:2021-05-01 Published:2021-05-17

摘要: 针对混凝土坝运行期风险因素多、不确定性大,且风险因素状态随时间呈动态变化的问题,分析并归纳了导致混凝土坝失事的主要风险源,引入时间因素建立了动态贝叶斯网络模型,研究混凝土坝失事概率随时间变化的动态特性。结合Leaky Noisy-or gate扩展模型,阐述了条件概率的确定方法。由实例分析得到了某混凝土坝失事概率和各风险因素发生概率的时序变化曲线。结果表明该动态贝叶斯网络评估模型合理可行且优于静态贝叶斯网络模型。研究成果可为类似工程的动态风险分析及评价体系的构建提供借鉴和参考。

关键词: 混凝土坝, 失事风险, 动态贝叶斯网络, 条件概率, 风险管理

Abstract: There are many dynamic risk factors and uncertainties in the operation period of concrete dam. In this paper, a dynamic Bayesian network model is constructed to study the dynamic characteristics of dam breach probability by introducing time factors. In association with the Leaky Noisy-or gate extended model, the method of determining conditional probability is described. The time series curves of occurrence probability of dam breach against each risk factor are obtained for a practical project as a case study. The present model is proved to be prior to the static Bayesian network as the result is more rational. The research finding offers reference for the dynamic risk analysis and evaluation system construction of similar projects.

Key words: concrete dam, breach risk, dynamic Bayesian network, conditional probability, risk management

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