Author(s): Yu Chen; Peng-Zhi Lin
Linked Author(s):
Keywords: Bayesian networks; Non-additivity; Dam break risk
Abstract: The dam break often brings catastrophic damages and enormous impacts to human, society, economy and environment, and becomes a world-wide problem. Therefore, the dam break risk is highly important for dam safety management authorities. There are many causes, such as earthquake, landslide, extreme rainfall, etc are involved in dam breach formation and eventual dam failure, which means the risk analysis for dam break, especially for that under the composite action of multi-causes, is a complex system problem. In view of the situation, this paper regards earthquake and extreme flood as prominent causes and takes dams in Dadu river basin as a study case, combines Bayesian networks with non-additivity principle to analyze their dam break risks. During the research process, literature analysis, historical data and expert knowledge have been taken firstly to identify the related factors affecting the dam break risk. Furthermore, determine variable nodes of the dam break risk, build Bayesian network directed acyclic topology model about the dam break risk according to the causal relationship between risk factors, and construct the priori probabilities and conditional probabilities of corresponding nodes. Finally, calculate the risk probabilities under the condition of the same input variables and different variables by using based on Bayesian network reasoning. The study can be expected to more intuitively and clearly reflect the relationship between risk factors and the impact way of each factor to the total risk, help to make account of the changing conditions of nodes induced by the variation of any other nodes of networks, lay the foundation for risk management decisionmaking, and provide theories and technological supports for the development of dam break risk analysis.
Year: 2016