Fuzzy- versus simulation-based life-cycle cost for sewer rehabilitation alternatives

Kashif Azeez, Tarek Zayed, Mohammad Ammar

Research output: Journal article publicationJournal articleAcademic researchpeer-review

5 Citations (Scopus)

Abstract

The ample framework to maintain infrastructure remains the continuous challenge in efficiently carrying out municipal duties. In North America, aging municipal infrastructure has reached the breaking point. This results in a large excess of infrastructure rehabilitation activities and cost escalation. Life-cycle cost (LCC) analysis, which can effectively deal with data vagueness and judgmental appraisal, is essential to evaluate various alternatives of infrastructure rehabilitation, particularly for sewers. Therefore, the objective of the present research is to develop LCC models using fuzzy and simulation approaches that deal with vague, imprecise, qualitative, linguistic, or incomplete data. Deterioration and cost data are collected for two sewer materials - PVC and concrete - with diameter ranges from 150 to 600 mm. The developed LCC models, with the help of an automated Microsoft Excel-based program, are utilized to select the best rehabilitation alternatives/scenarios. Results show that open-trench/sleeve, slip-lining, and pipe-bursting scenarios have the lowest LCC in spot-repair, renovation, and replacement categories, respectively. The developed models help academics and practitioners (for example, municipal engineers) plan suitable new installation/rehabilitation programs and their associated costs to avoid any unpleasant surprises.
Original languageEnglish
Pages (from-to)656-665
Number of pages10
JournalJournal of Performance of Constructed Facilities
Volume27
Issue number5
DOIs
Publication statusPublished - 1 Oct 2013
Externally publishedYes

Keywords

  • Deterioration
  • Fuzzy and simulation models
  • LCC
  • Rehabilitation alternatives
  • Sewer infrastructure

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Building and Construction
  • Safety, Risk, Reliability and Quality

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