Al-Saffar, M. and Husband, S. orcid.org/0000-0002-2771-1166 (2020) Long-term discolouration modelling for cast iron mains. Urban Water Journal, 17 (8). pp. 696-703. ISSN 1573-062X
Abstract
Water companies have been working to introduce strategies to reduce discolouration customer contacts via non-specialist ‘business as usual’ practices. A greater understanding of discolouration material behaviour, however, is still needed to accurately inform the mobilisation response and regeneration rates in mains of different materials. The Variable Condition Discolouration Model (VCDM) that tracks both accumulation and mobilisation processes has been validated in some pipe materials using long-term time series data. This paper investigates calibration for a 15 km cast iron (CI) main, using daily turbidity responses with VCDM parameter sensitivity and temporal stability investigated using a statistical approach comparing three periods of the data.
Results highlight the VCDM as widely applicable to determine long-term discolouration behaviour and improve behavioural understanding. In this case, analysis of different time periods indicates flow-conditioning not only improves network resilience but can also reduce mobilisation rates and discolouration risk.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020 Informa UK Limited, trading as Taylor & Francis Group. This is an author-produced version of a paper subsequently published in Urban Water Journal. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Discolouration modelling; VCDM; discolouration material; water distribution systems; trunk mains conditioning |
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) |
Funding Information: | Funder Grant number SEVERN TRENT WATER LIMITED None |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 11 Aug 2020 17:03 |
Last Modified: | 24 May 2022 11:34 |
Status: | Published |
Publisher: | Taylor & Francis |
Refereed: | Yes |
Identification Number: | 10.1080/1573062x.2020.1769689 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:164300 |