Pipe Failure Prediction and Risk Modeling in Water Distribution Networks: A Critical Review | IConEST

Paper Detail

Title

Pipe Failure Prediction and Risk Modeling in Water Distribution Networks: A Critical Review

Authors

Dr. Thikra Dawood, Purdue University, United States of America
Assoc. 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

Abstract

Sustainable 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.

 Keywords

pipe failure, risk analysis, prediction models, water main deterioration, water main rehabilitation, infrastructure  

Citation

Dawood, 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 01 April 2020 from www.2019.iconest.net/proceedings/38/.

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