Watermain's failure index modeling via Monte Carlo simulation and fuzzy inference system

Thikra Dawood, Emad Elwakil, Hector Mayol Novoa, José Fernando Gárate Delgado

Research output: Contribution to journalArticlepeer-review

Abstract

The aging and degradation of water supply systems are deemed serious problems that cause pipeline failure and breakages. The risk of watermains failure assessment is one of the key strategies that can pinpoint pipes at risk and maintain their sustainability. This research paper showcases a novel method for deterioration modeling in conjunction with quantifying the water network's failure index (FI). The methodology builds on various algorithms, computational intelligence, and interactions between numerous factors. It involves developing two intelligent models; the first is the Monte Carlo Simulation Model (MCSM) that is designed to estimate the deterioration indices (DIs) of watermains through intricate iterative simulations. The produced indices are then streamlined and channeled to the fuzzy engine to develop the second model, namely, the fuzzy inference system model (FISM). After designing the model's configuration, the DIs are mapped to 84 fuzzy-if-then-rules that are in turn mapped to output values; finally, the fuzzy consolidator generates one crisp number that represents the watermain's FI. The developed method is implemented on the water system of the City of El Pedregal in Peru. The results indicate a moderate risk of failure status, which corresponds to 62.3 FI. Moreover, the efficacy of this method is verified against the multiple linear regression (MLR) method and proved to be sound. This research provides insights for infrastructure managers in the aspects of when to intervene, what to maintain, replace, or rehabilitate, and how to focus their constrained funding on the most deserving assets.

Original languageEnglish
Article number106100
JournalEngineering Failure Analysis
Volume134
DOIs
StatePublished - Apr 2022

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).

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

Publisher Copyright:
© 2022 Elsevier Ltd

Keywords

  • Deterioration
  • Infrastructure
  • Modeling
  • Pipe Failure
  • Risk
  • Water Distribution Networks

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