Journal cover Journal topic
Drinking Water Engineering and Science An interactive open-access journal

Journal metrics

  • CiteScore<br/> value: 0.79 CiteScore
    0.79
  • SNIP value: 0.813 SNIP 0.813
  • SJR value: 0.228 SJR 0.228
  • IPP value: 0.719 IPP 0.719
Drink. Water Eng. Sci., 11, 67-85, 2018
https://doi.org/10.5194/dwes-11-67-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
Research article
15 May 2018
Algorithms for optimization of branching gravity-driven water networks
Ian Dardani and Gerard F. Jones College of Engineering, Villanova University, Villanova, PA 19085, USA
Abstract. The design of a water network involves the selection of pipe diameters that satisfy pressure and flow requirements while considering cost. A variety of design approaches can be used to optimize for hydraulic performance or reduce costs. To help designers select an appropriate approach in the context of gravity-driven water networks (GDWNs), this work assesses three cost-minimization algorithms on six moderate-scale GDWN test cases. Two algorithms, a backtracking algorithm and a genetic algorithm, use a set of discrete pipe diameters, while a new calculus-based algorithm produces a continuous-diameter solution which is mapped onto a discrete-diameter set. The backtracking algorithm finds the global optimum for all but the largest of cases tested, for which its long runtime makes it an infeasible option. The calculus-based algorithm's discrete-diameter solution produced slightly higher-cost results but was more scalable to larger network cases. Furthermore, the new calculus-based algorithm's continuous-diameter and mapped solutions provided lower and upper bounds, respectively, on the discrete-diameter global optimum cost, where the mapped solutions were typically within one diameter size of the global optimum. The genetic algorithm produced solutions even closer to the global optimum with consistently short run times, although slightly higher solution costs were seen for the larger network cases tested. The results of this study highlight the advantages and weaknesses of each GDWN design method including closeness to the global optimum, the ability to prune the solution space of infeasible and suboptimal candidates without missing the global optimum, and algorithm run time. We also extend an existing closed-form model of Jones (2011) to include minor losses and a more comprehensive two-part cost model, which realistically applies to pipe sizes that span a broad range typical of GDWNs of interest in this work, and for smooth and commercial steel roughness values.
Citation: Dardani, I. and Jones, G. F.: Algorithms for optimization of branching gravity-driven water networks, Drink. Water Eng. Sci., 11, 67-85, https://doi.org/10.5194/dwes-11-67-2018, 2018.
Publications Copernicus
Download
Short summary
This work is an outgrowth of engineering service learning at Villanova University in Pennsylvania, USA. Teams of students assess and collect data on site, and design and communicate information for clean water networks that benefit developing areas around the world. The design of a water network requires the selection of pipe diameters that satisfy pressure and flow requirements while minimizing cost. This work contrasts and compares results of several models and makes key recommendations.
This work is an outgrowth of engineering service learning at Villanova University in...
Share