Automated Sub-Zoning of Water Distribution Systems
Name
Sela et al EM&S(2015).pdf
Size
3.57 MB
Format
Adobe PDF
Checksum (MD5)
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Author(s)
Allen, Michael
Preis, Ami
Iqbal, Mudasser
Perelman, Lina Sela
Whittle, Andrew
Date Issued
December 2014
Journal
Environmental Modelling and Software
Publisher
Elsevier
Citation
Sela Perelman, Lina et al. “Automated Sub-Zoning of Water Distribution Systems.” Environmental Modelling & Software 65 (2015): 1–14.
Version
Author's final manuscript
Abstract
Water distribution systems (WDS) are complex pipe networks with looped and branching topologies that often comprise thousands to tens of thousands of links and nodes. This work presents a generic framework for improved analysis and management of WDS by partitioning the system into smaller (almost) independent sub-systems with balanced loads and minimal number of interconnections. This paper compares the performance of three classes of unsupervised learning algorithms from graph theory for practical sub-zoning of WDS: (1) Global clustering – a bottom-up algorithm for clustering n objects with respect to a similarity function, (2) Community structure – a bottom-up algorithm based on the property of network modularity, which is a measure of the quality of network partition to clusters versus randomly generated graph with respect to the same nodal degree, and (3) Graph partitioning – a flat partitioning algorithm for dividing a network with n nodes into k clusters, such that the total weight of edges crossing between clusters is minimized and the loads of all the clusters are balanced. The algorithms are adapted to WDS to provide a practical decision support tool for water utilities. Visual qualitative and quantitative measures are proposed to evaluate models' performance. The three methods are applied for two large-scale water distribution systems serving heavily populated areas in Singapore.
MIT Department
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
Terms of Use
Creative Commons Attribution-NonCommercial-NoDerivs License
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1016/j.envsoft.2014.11.025
