Generation of Synthetic Water Distribution Data Using a Multiscale Generator-Optimizer
Publication: Journal of Pipeline Systems Engineering and Practice
Volume 14, Issue 1
Abstract
Rare or limited access to real-world data has widely been a stumbling block for the development and employment of design optimization and simulation models in water distribution systems (WDS). Primary reasons for such accessibility issues could include data unavailability and high security protocols. Synthetic data can play a major role as a reliable alternative to mimic and replicate real-world WDS for modeling purposes. This study puts forth a comprehensive approach to generate synthetic WDS infrastructural data by (1) employing graph-theory concepts to generate multitudinous WDS skeleton layouts through retaining the critical topological features of a given real WDS; and (2) assigning component sizes and operational features such as nodal demands, pump curves, pipe sizes, and tank elevations to the generated WDS skeleton layouts through a multiobjective genetic algorithm (GA)–based design optimization scheme. Thousands of such generated-optimized networks are statistically analyzed in terms of the fundamental WDS characteristics both collectively and granularly. An outstanding novelty in this study includes an automatedly integrated algorithmic function that attempts to (1) simultaneously optimize the generated network in a biobjective scheme, (2) rectify pipe intersections that violate pipeline embedding standards, and (3) correct the unusual triangular loops in the generator by honoring the conventional square-shaped loop connectivity in a WDS. The proposed modeling approach was demonstrated in this study using the popular Anytown water distribution benchmark system. Generation and optimization of such representative synthetic networks pave the way for extensive access to representative case-study models for academic and industrial purposes while the security of the real-world infrastructure data is not compromised.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request. Preliminary source code, data, and documentation are available at https://github.com/varsha2611/Water-Network-Generation-and-Optimization.
Acknowledgments
This research was supported by the National Science Foundation (NSF) under Grant No. 1745300. This study was also partly supported by King Saud University, Riyadh, Saudi Arabia, through Researchers Supporting Project No. RSP-2021/302. The results and conclusion presented in this paper are those of the authors and should not be interpreted as necessarily representing the official policies, either expressed or implied, of the United States Government. The authors are grateful to the NSF for this support.
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Published In
Journal of Pipeline Systems Engineering and Practice
Volume 14 • Issue 1 • February 2023
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© 2022 American Society of Civil Engineers.
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Received: Apr 4, 2022
Accepted: Oct 27, 2022
Published online: Dec 14, 2022
Published in print: Feb 1, 2023
Discussion open until: May 14, 2023
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