Locating Inadvertently Partially Closed Valves in Water Distribution Systems

灵敏度(控制系统) 遗传算法 可靠性(半导体) 计算 管道(软件) 管道运输 计算机科学 控制阀 工程类 可靠性工程 数学优化 算法 控制工程 数学 机械工程 物理 功率(物理) 量子力学 电子工程
作者
Nhu Cuong,Angus R. Simpson,Jochen Deuerlein,Olivier Piller
出处
期刊:Journal of Water Resources Planning and Management [American Society of Civil Engineers]
卷期号:144 (8) 被引量:16
标识
DOI:10.1061/(asce)wr.1943-5452.0000958
摘要

The reliability of a water distribution system is highly dependent on the management of its pipeline network. A pipe or a portion of the network can be isolated for inspection, maintenance, and replacement by the installation of isolation valves along the pipelines. However, the presence of isolation valves may cause a large discrepancy in the hydraulic behavior between the real system and results from a simulation model if the statuses of some of the valves in the system are unknown. Possible problems related to these valves are missing valves in the model due to poor or nonexistent documentation, errors in data transfer, or valve mechanical failure. This paper introduces an innovative methodology for the identification of unknown partially/fully closed valves in a water distribution network. An optimization problem is formulated for the unknown valve issue and solved by application of three sequentially applied methods, which include a local sensitivity analysis, an application of genetic algorithms (GAs), and an application of the Levenberg-Marquardt algorithm. In the first method, the sensitivity of the flow rates and nodal heads at measurement locations with respect to the change in the minor losses of the valves is computed. This computation is used to identify the valves that are unable to be localized by the measurement data. The second method applies a genetic algorithm combined with an extended period simulation in order to preliminarily identify the locations of the partially/fully closed valves and their setting values, i.e., the degree of opening of the valve. Finally, the application of the Levenberg-Marquardt (LM) algorithm was implemented to correct the results from the GA model. Results and discussions from two case studies show that the proposed methodologies can solve real-world problems.
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