An analytic network process condition assessment model for sewer pipelines

A. Hawari, F. Alkadour, Tarek Zayed

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

As sewer pipelines age, the need for their upgrading, maintaining, and repairing arises. Simultaneously, inadequate sewer pipelines might lead to catastrophic failures. Thus, decision makers must have a detailed knowledge on their network condition. Lack of awareness of the sewer network's condition is a major issue in Qatar where no attempts have been made to develop a proper tool for assisting decision makers in sewer pipeline rehabilitation planning. In order to give a precise prediction of the sewer pipelines' condition, all critical factors that might have an influence on their deterioration must be taken into consideration. This paper: (1) recognises the primary factors affecting sewer pipeline conditions in Qatar and (2) determines the degree to which each factor impacts on sewer pipeline conditions. Going through the literature and meeting with experts, the factors influencing sewer pipelines condition were first identified and grouped into three main categories, namely, physical, operational, and environmental factors. A total of 17 sub-factors were considered for sewer pipelines under gravity. Questionnaires were distributed to experts in Qatar to perform a pairwise comparison between the identified factors. Based on the questionnaire results, the importance weights of each factor were determined using the analytical network process technique. In order to validate the developed condition assessment model, data sets were obtained from the Ashghal Public Work Authority and compared with the model's output. This is a platform to help in building reliable condition assessment models for sewer pipelines in Qatar.
Original languageEnglish
JournalCivil-Comp Proceedings
Volume109
Publication statusPublished - 1 Jan 2015
Externally publishedYes

Keywords

  • Analytic network process
  • Condition assessment
  • Factor impact
  • Influencing factors
  • Model validation
  • Sewer pipelines

ASJC Scopus subject areas

  • Environmental Engineering
  • Civil and Structural Engineering
  • Computational Theory and Mathematics
  • Artificial Intelligence

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