3D Modeling of Pipe Risk Index for a Sustainable Urban Water System

Thikra Dawood, Emad Elwakil, Hector Mayol Novoa, Jose Fernando Garate Delgado

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

Abstract

The risk assessment and modeling of watermains are complicated tasks, which are proportional to the intricacy of underground water networks. These networks are known to be nonlinear, dynamic, and involve a multitude of influential factors that cannot be measured accurately in any conventional metrics. In general, deterioration factors obtained from field inspections reports or from experts' survey have certain degrees of ambiguity and subjectivity. One of the potent methods that have emerged in the last four decades to solve civil infrastructure problems, is the fuzzy inference system (FIS). This method can encode the deterioration factors into risk indices while coping with the inaccuracy, ambiguity, and fuzziness of data. The objective of this paper is to develop a risk index model for water transmission pipes based on simulation and FIS. First, the input and output datasets of the proposed model are defined based on inspection reports and experts' questionnaire; both the input and output datasets are fed into the FIS engine. Second, the fuzzy logic control engine is designed by defining the membership functions and the rules in the fuzzy operator. The third step includes

Original languageEnglish
Title of host publication2021 IEEE Conference on Technologies for Sustainability, SusTech 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9780738124445
DOIs
StatePublished - 22 Apr 2021
Event8th IEEE Conference on Technologies for Sustainability, SusTech 2021 - Virtual, Online, United States
Duration: 22 Apr 202124 Apr 2021

Publication series

Name2021 IEEE Conference on Technologies for Sustainability, SusTech 2021

Conference

Conference8th IEEE Conference on Technologies for Sustainability, SusTech 2021
Country/TerritoryUnited States
CityVirtual, Online
Period22/04/2124/04/21

Bibliographical note

Funding Information:
This work is supported by the collaboration of the Universidad Nacional de San Agust?n (UNSA) in Arequipa.

Funding Information:
ACKNOWLEDGMENT 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:
© 2021 IEEE.

Keywords

  • Failure
  • Fuzzy Inference System
  • Modeling
  • Risk Index
  • Soft Computing
  • Water Pipelines

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