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A Superposed Model for the Pipe Failure Assessment of Water Distribution Networks and Uncertainty Analysis: A Case Study

机译:给水管网失效评估与不确定性分析的叠加模型

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Pipe failure often occurs in water distribution networks (WDNs) and results in high levels of water loss and socio-economic damage. Physical-based, statistical and data-driven models have been developed to estimate pipe failure rates (failures per km of pipe per year) to efficiently manage water losses from WDNs and to ensure safe operations. Due to the complexities of pipe failure patterns, we develop a superposed statistical model to depict the relationship between pipe failure rate and pipe age. The model's level of uncertainty was then quantified by simulating pipe failures as Poisson numbers. Part of Beijing's WDN is taken as a study case, and pipe failure data for a 4-year period, as well as pipe properties, are collected to develop the pipe failure model. The case study results show that the pipe failure rates vary with time in a non-monotonic manner and that the proposed model captures pipe failure behaviour with an R-2 value of 0.95. A 95% confidence interval of modelled pipe failures for each pipe age group is used to describe the uncertainty level of the model. We find that 88% of the observations fall under the 95% confidence interval. The established model could be applied to prioritize pipes with higher failure rates to optimize pipe replacement/rehabilitation strategies. Our uncertainty analysis of this model can help utility managers understand the model's reliability and formulate reasonable WDN management plans.
机译:管道故障经常发生在配水网络(WDN)中,并导致大量的水流失和社会经济损失。已经开发了基于物理,统计和数据驱动的模型来估计管道故障率(每年每公里管道的故障),以有效管理WDN造成的水损失并确保安全运行。由于管道故障模式的复杂性,我们开发了一个叠加统计模型来描述管道故障率与管道寿命之间的关系。然后通过将管道故障模拟为泊松数来量化模型的不确定性水平。以北京WDN的一部分为研究案例,收集了4年期间的管道故障数据以及管道性能,以开发管道故障模型。案例研究结果表明,管道故障率以非单调方式随时间变化,并且该模型捕获的管道故障行为的R-2值为0.95。每个管道使用年限的建模管道故障的95%置信区间用于描述模型的不确定性水平。我们发现88%的观察值落在95%的置信区间内。建立的模型可以用于对故障率较高的管道进行优先排序,以优化管道更换/修复策略。我们对该模型的不确定性分析可以帮助公用事业管理人员了解该模型的可靠性并制定合理的WDN管理计划。

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