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Algorithm for Automatic Detection of Topological Changes in Water Distribution Networks
Authors:Orazio Giustolisi  Zoran Kapelan  Dragan Savic
Affiliation:1Professor, Dept. of Civil and Environmental Engineering, Technical Univ. of Bari, via E. Orabona 4, 70125 Bari, Italy (corresponding author). E-mail: o.giustolisi@poliba.it
2Senior Lecturer, Centre for Water Systems, Univ. of Exeter, Harrison Building, North Park Rd., EX4 4QF Exeter, U.K. E-mail: z.kapelan@ex.ac.uk
3Professor, Centre for Water Systems, Univ. of Exeter, Harrison Building, North Park Rd., EX4 4QF Exeter, U.K. E-mail: d.savic@ex.ac.uk
Abstract:Topological and pressure-driven analyses are an integral part of reliability/risk considerations for a water distribution system. For example, it is often necessary to identify which parts of the distribution network are isolated from water sources after the valves have been closed in response to a mechanical pipe failure. Pressure-driven analysis is then necessary to ascertain the consequences of pipe failures in terms of the performance of the functioning subsystem while pipe breaks are being fixed in the isolated area. Therefore, it is extremely useful to have an algorithm for the automatic identification of nodes/pipes disconnected from the water source(s). However, this is a complex problem because valves sometimes significantly modify the network topology. Furthermore, the use of isolation valves can cause a demand shortage to some customers (due to pressure reduction) during the abnormal operating conditions in the system. Thus, pressure-driven simulation of the network behavior is required. For these reasons, a novel algorithm capable of automatic detection of topological network changes is coupled with a robust pressure-driven simulation model. This algorithm is tested on two case studies involving a small artificial water distribution system and a larger, real-life network. The results obtained clearly demonstrate the robustness of the algorithm developed.
Keywords:Water distribution systems  Network analysis  System reliability  Simulation  Algorithms  Risk management  
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