Prediction of Water Pipe Failure Using Fuzzy Inference System

T. Dawood, E. Elwakil, H. M. Novoa, J. F.G. Delgado

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Recurrent incidences of pipeline failure bring about serious physical, economical, and environmental consequences. Therefore, developing pragmatic approaches to model the water distribution infrastructure is crucial for preserving these assets. The objective of this paper is to develop a pipe failure prediction model grounded in fuzzy inference system and the probability of failure analysis to estimate the rate of failure in water infrastructure. First, the attributes that contribute to water pipelines deterioration are identified. Second, the fuzzy logic engine is designed to simulate the defined codes and functions. Third, probability of failure schemes are generated to address the uncertainties and predict the risk associated with water pipes’ failure. The developed model was applied to the water network of the city of El Pedregal in Peru. This paper developed an automated tool, expected to improve the quality of decision making, as it can assist water utility managers and infrastructure engineers in optimizing their future plans.

Original languageEnglish
Title of host publicationProceedings of the Canadian Society of Civil Engineering Annual Conference 2021 - CSCE21 Structures Track Volume 1
EditorsScott Walbridge, Mazdak Nik-Bakht, Kelvin Tsun Ng, Manas Shome, M. Shahria Alam, Ashraf El Damatty, Gordon Lovegrove
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages7
ISBN (Print)9789811905100
StatePublished - 2023
EventAnnual Conference of the Canadian Society of Civil Engineering, CSCE 2021 - Virtual, Online
Duration: 26 May 202129 May 2021

Publication series

NameLecture Notes in Civil Engineering
ISSN (Print)2366-2557
ISSN (Electronic)2366-2565


ConferenceAnnual Conference of the Canadian Society of Civil Engineering, CSCE 2021
CityVirtual, Online

Bibliographical note

Funding Information:
This work is supported by the collaboration of the Universidad Nacional de San Agustín (UNSA) in Arequipa, Peru, and Purdue University in Indiana, USA through Discovery Park’s Center for the Environment (C4E).

Publisher Copyright:
© 2023, Canadian Society for Civil Engineering.


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