Identifying Critical Links in Water Supply Systems Subject to Various Earthquakes to Support Inspection and Renewal Decision Making
Identifying Critical Links in Water Supply Systems Subject to Various Earthquakes to Support Inspection and Renewal Decision Making
复制标题
识别遭受各种地震影响的供水系统的关键环节，以支持检查和更新决策
DOI：
10.1061/9780784480847.029
复制
发表时间：
2017
期刊：
影响因子：
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通讯作者：
M. Razavi
中科院分区：
文献类型：
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作者：
B. Pudasaini;S. M. Shahandashti;M. Razavi
在最近的地震中，供水系统受到了广泛的破坏，这清楚地表明了进行地震规划的必要性。然而，供水地震规划受制于地震的位置、震级和造成的破坏的不确定性。供水系统的复杂拓扑结构以及不同材料的使用、接头特性、管径和土壤腐蚀性使问题进一步复杂化。本文的目的是确定受各种地震影响的供水网络的关键环节，并在给定资源约束的情况下找到最优更新决策。该方法由四个相互关联的部分组成：(1)修理率概率建模；(2)蒙特卡罗模拟；(3)水力损伤建模；(4)资源配置优化。第一部分根据经验脆性曲线计算网络中每条管道的修复率。经验脆性曲线与管道的位置、材料、直径、接缝性质和土壤腐蚀性有关。蒙特卡罗模拟在管网中产生概率损伤（即泄漏和断裂）。水力模型计算了考虑模拟损伤的可用性指标。资源分配优化模型在给定资源约束条件下，采用遗传算法寻找最优续订决策，以使可服务性指标最大化。利用供水网络对模型进行了验证。该网络由117个管道和92个连接点组成。结果表明，提出的方法优于文献中最新提出的方法，以确定水网络中的关键环节。使用网络可服务性指数作为度量，将结果与文献中最新提出的方法进行比较。
Widespread damage of water supply systems during recent earthquakes clearly shows the need for seismic planning. However, water supply seismic planning is subject to uncertainties in location, magnitude, and resulting damage of earthquakes. This problem is further complicated by complex topology of water supply systems along with the use of different materials, joint characteristics, pipe diameters and soil corrosivities. The objective of this paper is to identify critical links of water supply networks subject to various earthquakes and find optimum renewal decision given resource constraints. The methodology comprises of four interconnected components: (1) repair rate probabilistic modeling; (2) Monte Carlo simulation; (3) hydraulic damage modelling; and (4) resource allocation optimization. The first component calculates repair rate for each pipe in the network based on empirical fragility curves. Empirical fragility curves depend on the pipes’ location, material, diameter, joint property and soil corrosivity. Monte Carlo simulation generates probabilistic damages (i.e., leaks and breaks) in the pipe network. The hydraulic model calculates serviceability index considering simulated damages. Resource allocation optimization model uses genetic algorithm to find the optimum renewal decision to maximize serviceability index given resource constraints. The proposed model was validated using a water supply network. The network consists of 117 pipes and 92 junctions. The results show that the proposed methodology outperforms the latest proposed methodology in the literature to identify critical links in a water network. The network serviceability index is used as the measure to compare the results with the latest proposed methodology in the literature.