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Systematic Surge Protection For Worst-case Transient Loadings In Water Distribution Systems

机译:供水系统中最坏情况下的瞬时负载的系统电涌保护

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Estimating appropriate water demands for the design of a distribution system is itself difficult, but the continuously fluctuating nature of these demands has the added potential of creating water hammer problems that might result in catastrophic pipeline or system failure. To first identify and then avoid these eventualities, this paper searches a predefined set of possible water hammer events in water distribution systems to identify the most severe transient loadings and then conducts a search for suitable surge protection strategies. Genetic algorithms and particle swarm optimization are combined with transient analysis first to identify a set of worst-case loads and then to seek an optimal protection strategy to cope with them. Case studies show that the worst case is not always obvious and cannot always be assumed a priori to correspond with high or low demand scenarios. Both the search for the worst-case loading and its associated optimal protection strategies are strongly sensitive to the characteristics of both the pipe system and the candidate transient events.
机译:为分配系统的设计估算合适的用水需求本身是困难的,但是这些需求的不断波动性质具有产生水锤问题的额外潜力,这可能会导致灾难性的管道或系统故障。为了首先识别并避免这些可能,本文在供水系统中搜索了一组预定义的可能的水锤事件,以识别最严重的瞬态负荷,然后进行搜索以寻找合适的电涌保护策略。遗传算法和粒子群优化与瞬态分析相结合,首先确定一组最坏情况的负荷,然后寻求最佳的保护策略来应对它们。案例研究表明,最坏的情况并不总是很明显,也不能总是先验地假定它与高需求或低需求情景相对应。寻找最坏情况的负载及其相关的最佳保护策略都对管道系统的特性和候选瞬态事件都非常敏感。

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