Node Demand Reverse Deduction (DRD) Technology for Water Supply Networks

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Abstract

The node demand driven analytical technique is the currently accepted method of hydraulic calculation for water distribution networks. Since the node demands are derived from the user's monthly or bimonthly meter reading data and water usage patterns, there are usually deviations between the real and the estimated data. The results obtained from this method are limited in its application of hydraulic modeling for daily operation and management for the water supply network. Based on theoretical analysis and practical example tests, this paper proposes a new method of calculation for node hydraulic grades (HG) through SCADA discrete point pressure monitorings and the triangulated irregular network (TIN) interpolation algorithm. Using the physical information of the connected pipes, such as pipe friction coefficients, and the HG data, the node demands can be calculated. Based on node demands and the HG data, the pipe network pressures can be stabilized, the leakage amounts can be estimated, and the leakage locations can be identified. This method can bring network hydraulic modeling into a new era. © Springer International Publishing Switzerland 2015.

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Wang, R., Wang, Z., Ping, J., Sun, J., & Xiao, C. (2015). Node Demand Reverse Deduction (DRD) Technology for Water Supply Networks. In Advances in Intelligent Systems and Computing (Vol. 1089, pp. 825–830). Springer Verlag. https://doi.org/10.1007/978-3-319-08422-0_120

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