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KSCE Journal of Civil Engineering

, Volume 10, Issue 4, pp 243–253 | Cite as

Life cycle cost analysis based optimal maintenance and rehabilitation for underground infrastructure management

  • Seung-Hyun Chung
  • Tae-Hoon Hong
  • Seung-Woo Han
  • Jae-Ho Son
  • Sang-Youb LeeEmail author
Construction Management

Abstract

This study presents a sanitary sewer management decision-making framework incorporating demand forecasting and life cycle cost analysis. The framework provides the asset managers with an alternative approach in sewer management. It is designed to allow asset managers to better allocate limited funds for maintenance and rehabilitation by identifying possible problematic sewers and devising a maintenance plan to prevent costly sewer failures. Sewer demand forecasting model is developed using an artificial neural network. The forecasted sewer demand is then used to identify “critical” areas, where the current hydraulic capacity is less than the forecasted sewer demand. In such areas, an optimal maintenance and rehabilitation strategy is developed through the application of probabilistic dynamic programming in conjunction with Markov chain deterioration modeling.

Keywords

sewer management demand forecasting life cycle cost analysis 

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Copyright information

© KSCE and Springer jointly 2006

Authors and Affiliations

  • Seung-Hyun Chung
    • 1
  • Tae-Hoon Hong
    • 2
  • Seung-Woo Han
    • 3
  • Jae-Ho Son
    • 4
  • Sang-Youb Lee
    • 5
    Email author
  1. 1.Brown and CaldwellIrvineUSA
  2. 2.Construction Engineering & Management Research DepartmentKorea Institute of Construction TechnologyKorea
  3. 3.Dept. of Architectural EngineeringInha UniversityKorea
  4. 4.Dept. of Architectural EngineeringHongik UniversityKorea
  5. 5.Dept. of Real Estate ScienceKonkuk UniversitySeoulKorea

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