Eulogi, M., Ostojin, S., Skipworth, P. et al. (2 more authors) (2020) Hydraulic optimisation of multiple flow control locations for the design of local real time control systems. Urban Water Journal, 18 (2). pp. 91-100. ISSN 1573-062X
Abstract
Local real-time control (RTC) represents a potentially cost-effective solution for stormwater management in urban drainage systems. Existing methodologies to select the location of flow control devices (FCDs) are limited to single gate systems and are based on analysis of activated storage volume capacity, without considering hydrodynamic processes or rainfall characteristics. In this paper, a new genetic algorithm (GA)–based methodology is developed to determine the optimal location of multiple FCDs in urban drainage networks, when assessing RTC performance through hydraulic analysis. The methodology is tested on a case study network, where a high number of possible FCD location arrangements are tested and compared, and the RTC effectiveness in reducing combined sewer overflows has been evaluated over a range of design storm events. Results demonstrate the capability of the proposed method in selecting robust FCD placement strategies, for example when designing local RTC systems to meet specific performance criteria.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
Keywords: | Flow control device location; real-time control; CSO volume reduction; in-sewer storage |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Civil and Structural Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 04 Feb 2021 14:30 |
Last Modified: | 04 Feb 2021 14:30 |
Status: | Published |
Publisher: | Taylor & Francis |
Refereed: | Yes |
Identification Number: | 10.1080/1573062x.2020.1860238 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:169882 |