基于动态贝叶斯网络的混凝土坝失事风险分析

李宗坤, 王特, 葛巍, 郑艳

raybet体育在线 院报 ›› 2021, Vol. 38 ›› Issue (5) : 137-143.

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raybet体育在线 院报 ›› 2021, Vol. 38 ›› Issue (5) : 137-143. DOI: 10.11988/ckyyb.20200137
水工结构与材料

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
作者信息 +

Risk Analysis of Concrete Dam Breach Based on Dynamic Bayesian Network

  • LI Zong-kun1,2, WANG Te1, GE Wei1,3, ZHENG Yan1
Author information +
文章历史 +

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。

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.

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

Key words

concrete dam / breach risk / dynamic Bayesian network / conditional probability / risk management

引用本文

导出引用
李宗坤, 王特, 葛巍, 郑艳. 基于动态贝叶斯网络的混凝土坝失事风险分析[J]. raybet体育在线 院报. 2021, 38(5): 137-143 https://doi.org/10.11988/ckyyb.20200137
LI Zong-kun, WANG Te, GE Wei, ZHENG Yan. Risk Analysis of Concrete Dam Breach Based on Dynamic Bayesian Network[J]. Journal of Changjiang River Scientific Research Institute. 2021, 38(5): 137-143 https://doi.org/10.11988/ckyyb.20200137
中图分类号: TV64   

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基金

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)

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