It is shown that water distribution systems can be damaged by earthquakes, and the seismic damages cannot easily be located, especially immediately after the events. Earthquake experiences show that accurate and quick location of seismic damage is critical to emergency response of water distribution systems. This paper develops a methodology to locate seismic damage -- multiple breaks in a water distribution system by monitoring water pressure online at limited positions in the water distribution system. For the purpose of online monitoring, supervisory control and data acquisition (SCADA) technology can well be used. A neural network-based inverse analysis method is constructed for locating the seismic damage based on the variation of water pressure. The neural network is trained by using analytically simulated data from the water distribution system, and validated by using a set of data that have never been used in the training. It is found that the methodology provides an effective and practical way in which seismic damage in a water distribution system can be accurately and quickly located.
The supervisory control and data acquisition (SCADA) technology has been used in water distribution systems in recently years, in which, waterhead at some nodes and/or flowrate in some links in the water distribution systems are monitored by radio or internet, and the waterhead and flowrate monitoring stations are usually determined by experience or simply evenly distributed. For the purpose of more efficient monitoring, optimal monitoring of waterhead in a water distribution system was developed by the authors, and as the second part of the study, this paper has proposed a method for optimal monitoring of flowrate in a water distribution system. A perturbation analysis is conducted to determine the sensitivity matrix, and the sensitivity equation is solved by a least square method, and the optimal monitoring of flowrate is then decided. The optimal monitoring solution is compared with the evenly distributed case, and it is found the optimal monitoring provides a more efficient and practical scheme if the number of monitoring stations is specified.
The supervisory control and data acquisition (SCADA) technology is commonly used in water distribution systems in recently years. Monitoring is one of the most important steps in SCADA's implementation, and in reality monitoring stations used for water pressure are usually decided by experience or simply evenly distributed. For the purpose of more efficient monitoring, a method for optimal monitoring of water pressure in a water distribution system is proposed in this paper, in which, a sensitivity analysis is conducted for determining the sensitivity equation, and the sensitivity equation is then solved by a least-square method. It is found from examples that the method provides an efficient and practical way in which optimal monitoring scheme of water distribution system may be decided.
Breaks often occur to urban water distribution systems under severely cold weather, or due to corrosion of pipes, deformation of ground, etc., and the breaks cannot easily be located, especially immediately after the events. This paper develops a methodology to locate a break in a water distribution system by monitoring water pressure online at some nodes in the water distribution system. For the purpose of online monitoring, supervisory control and data acquisition (SCADA) technology can well be used. A neural network-based inverse analysis method is constructed for locating the break based on the variation of water pressure. The neural network is trained by using analytically simulated data from the water distribution system, and validated by using a set of data that have never been used in the training. It is found that the methodology provides a quick, effective, and practical way in which a break in a water distribution system can be located.
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