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A Framework of Identifying Critical Water Distribution Pipelines from Recovery Resilience

机译:从恢复弹性中识别关键配水管道的框架

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Identifying critical facilities in a water distribution system (WDS) from the standpoint of recovery resilience is significant for emergency inspection and restoration when a large-scale system disruption occurs. Taking a damaged pipeline into account, this paper proposes a framework for realizing criticality identification. The priority with which a damaged pipeline needs to be restored to minimize WDS service loss and the impact of delaying such priority on the loss of service are taken as criticality metrics. To acquire two metric values for each pipeline, a WDS recovery optimization problem, which integrates mechanical repair measures with hydraulic simulation, aimed at minimizing system service loss, is proposed and then solved by a genetic algorithm. Given the stochasticity of disruptions on a WDS, critical pipelines are identified by a stochastic scoring method, based on the statistical distribution of the two metrics obtained by stochastic sampling. An application of the framework to a case study of a WDS with simulated disruption scenarios distinguished pipelines critical to effective infrastructure restoration. Compared with models using network centrality and vulnerability-based metrics, the framework proposes a more reasonable way to measure facility criticality in terms of recovery resilience.
机译:从恢复弹性的角度识别供水系统(WDS)中的关键设施对于发生大规模系统中断的紧急检查和恢复至关重要。考虑到受损的管道,本文提出了一种实现临界识别的框架。需要恢复损坏的管道以最小化WDS服务损失的优先级以及延迟此类优先级对服务丢失的影响被视为关键性指标。为了获得每条管道的两个度量值,提出了WDS恢复优化问题,该问题将机械维修措施与水力仿真相结合,旨在最大程度地减少系统服务损失,然后通过遗传算法解决。给定WDS上的随机性,基于随机抽样获得的两个指标的统计分布,可以通过随机评分方法确定关键管道。该框架在具有模拟中断场景的WDS案例研究中的应用,区分了对有效基础架构恢复至关重要的管道。与使用网络中心性和基于漏洞的指标的模型相比,该框架提出了一种更合理的方法来根据恢复弹性来衡量设施的关键性。

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