Makana, L.O., Shepherd, W.J. orcid.org/0000-0003-4434-9442, Tait, S. orcid.org/0000-0002-0004-9555 et al. (4 more authors) (2022) Future inspection and deterioration prediction capabilities for buried distributed water infrastructure. Journal of Pipeline Systems Engineering and Practice, 13 (3). ISSN 1949-1190
Abstract
This paper examines the role of pipe deterioration prediction approaches for optimizing maintenance, repair, and rehabilitation of buried water supply, wastewater collection, and drainage networks. It is appreciated that there are other ancillary assets within water supply and wastewater collection and drainage networks, but these were not considered in this paper. Currently there are a range of asset condition assessment frameworks, mainly based on asset defect location, identification, and characterization. These are infrequently applied in practice, mainly due to the restricted availability of asset defect inspection data. This paper reviews current deterioration modeling approaches and highlights the crucial need for broader, richer data sets (including both asset and surrounding environment data) to inform the development and application of such approaches. This paper describes what could be considered as an expanded ideal data set for deterioration modeling at a network and individual asset scale and indicates emerging new inspection technologies that should be capable of meeting the enhanced data needs.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2022 American Society of Civil Engineers. |
Keywords: | Deterioration modeling; Defect classification; Inspection capabilities; Data needs; Water supply and wastewater collection networks |
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 Engineering and Physical Sciences Research Council EP/S016813/1 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 25 May 2022 12:37 |
Last Modified: | 31 May 2022 10:51 |
Status: | Published |
Publisher: | American Society of Civil Engineers (ASCE) |
Refereed: | Yes |
Identification Number: | 10.1061/(asce)ps.1949-1204.0000656 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:187329 |