Influence of Dead-End Sections of Drinking Water Distribution Networks on Optimization of Booster Chlorination Systems
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Volume 145, Issue 12
Abstract
The impact of implementing an advanced water quality model for simulating the dead-end sections of drinking water distribution networks on the outcomes of booster chlorination optimization is investigated. An advection-dispersion-reaction transport model that accounts for the realistic spatial distribution of water demands along dead-end pipes is linked to a genetic algorithm to find the optimal layout and operation of booster chlorination stations. The objective function is formulated and solved to find the optimal locations and chlorine dosing schedules of the booster stations that minimize the total costs of design and operation of the booster system, while maintaining a sufficient residual throughout the distribution network. The results highlight the importance of considering dispersive solute transport, as well as the excessive residence times encountered in the dead-end branches in the water quality simulations conducted for network optimization problems. While this study addresses the optimization of booster chlorination systems, its implications extend to a wide array of network optimization applications, including pump scheduling for water quality optimization, optimal sensor placement for reactive contaminant detection, and design of real-time boost-response systems.
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Data Availability Statement
Some or all data, models, and/or code generated and/or used during the study are available in a repository or online (https://github.com/aabokifa/WUDESIM).
Acknowledgments
Partial support from the Lucy and Stanley Lopata Endowment and the McDonnell Academy Global Energy and Environmental Partnership (MAGEEP) at Washington University in St. Louis is gratefully acknowledged.
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Published In
Journal of Water Resources Planning and Management
Volume 145 • Issue 12 • December 2019
Copyright
©2019 American Society of Civil Engineers.
History
Received: Oct 3, 2018
Accepted: Mar 29, 2019
Published online: Sep 18, 2019
Published in print: Dec 1, 2019
Discussion open until: Feb 18, 2020
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