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首页> 外文会议>International Conference on Hydroinformatics >DATA-DRIVEN SURROGATE MODELS FOR FLOOD DEFENCE FAILURE PROBABILITY ESTIMATION: CASE STUDY 'JARILLON DE CALI, COLOMBIA'
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DATA-DRIVEN SURROGATE MODELS FOR FLOOD DEFENCE FAILURE PROBABILITY ESTIMATION: CASE STUDY 'JARILLON DE CALI, COLOMBIA'

机译：防洪失效概率估计的数据驱动替代模型：案例研究“哥伦比亚加里隆·德·卡利”

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Reliability studies for safety assessment of flood defences now days demand a large amount of stochastic calculations. Therefore mathematical simplifications of the models are used to describe the failure state of the flood defence structures. The present study implemented emulation techniques of different flood defence failure mechanisms, in order to assess the impact in the failure probability by the change in operation of an upstream reservoir. It was found that for the assumed conditions, piping is the most probable failure to occur. However is the less sensitive towards an eventual change in the flow regime conditions. The calculation times where significantly reduced, and the influence in the failure probability distributions was assessed proving data driven models to be a powerful tool for flood defence safety assessment.
机译：如今，用于防洪安全评估的可靠性研究需要大量的随机计算。因此，该模型的数学简化用于描述防洪结构的破坏状态。为了评估上游水库运行变化对破坏概率的影响，本研究实施了不同防洪破坏机制的仿真技术。发现在假定的条件下，管道是最有可能发生的故障。然而，对于流动状态条件的最终变化较不敏感。计算时间大大减少，并且评估了故障概率分布中的影响，证明了数据驱动模型是防洪安全评估的有力工具。

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