TitlePipe Failure Prediction and Risk Modeling in Water Distribution Networks: A Critical Review |
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AuthorsDr. Thikra Dawood, Purdue University, United States of AmericaAssoc. Prof. Dr. Emad Elwakil, Purdue University, United States of America Lecturer Hector Mayol Novoa, National University of St Augustin of Arequipa, Peru Lecturer José Fernando Gárate Delgado, National University of St Augustin of Arequipa, Peru |
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AbstractSustainable assessment and management of water distribution systems represent substantial challenges for civil engineers and utility managers. These strategies not merely involve utilizing new techniques to monitor, repair, and/or rehabilitate the deteriorated pipes, but also intelligent modeling procedures for the consistent evaluation and quantification of the risk of failure in aging infrastructure. This paper provides the current state-of-the-art related to water pipe failure prediction and risk assessment, published in the last ten years (2009-2019). The mainstream of the current practice characterizes the structural deterioration and failure rates using various statistical techniques, whereas the remainder of research covers a proliferation of machine learning and soft computing applications to forecast and model the pipeline risk of failure. The review offers descriptions of the models together with their proposed methodologies, algorithms and equations, contributions and drawbacks, comparisons and critiques, and types of data used to develop the models. Finally, future work and research challenges are recommended to assist the civil engineering research community in setting a clear agenda for the upcoming research. |
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Keywordspipe failure, risk analysis, prediction models, water main deterioration, water main rehabilitation, infrastructure |
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CitationDawood, T., Elwakil, E., Novoa, H.M. & Delgado, J.F.G. (2019). Pipe Failure Prediction and Risk Modeling in Water Distribution Networks: A Critical Review. In M. Shelley & V. Akerson (Eds.), Proceedings of IConEST 2019--International Conference on Engineering, Science and Technology (pp. 38-44). Monument, CO, USA: ISTES Organization. Retrieved 19 April 2024 from www.2019.iconest.net/proceedings/38/. |
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