Computers and Concrete

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Remaining service life estimation of reinforced concrete buildings based on fuzzy approach

  • Cho, Hae-Chang (Department of Architectural Engineering, University of Seoul) ;
  • Lee, Deuck Hang (Department of Architectural Engineering, University of Seoul) ;
  • Ju, Hyunjin (Department of Architectural Engineering, University of Seoul) ;
  • Kim, Kang Su (Department of Architectural Engineering, University of Seoul) ;
  • Kim, Ki-Hyun (Department of Civil & Environmental Engineering, University of California) ;
  • Monteiro, Paulo J.M. (Department of Civil & Environmental Engineering, University of California)
  • Received : 2014.08.13
  • Accepted : 2015.04.15
  • Published : 2015.06.25
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Abstract

The remaining service life (RSL) of buildings has been an important issue in the field of building and facility management, and its development is also one of the essential factors for achieving sustainable infrastructure. Since the estimation of RSL of buildings is heavily affected by the subjectivity of individual inspector or engineer, much effort has been placed in the development of a rational method that can estimate the RSL of existing buildings more quantitatively using objective measurement indices. Various uncertain factors contribute to the deterioration of the structural performance of buildings, and most of the common building structures are constructed not with a single structural member but with various types of structural components (e.g., beams, slabs, and columns) in multistory floors. Most existing RSL estimation methods, however, consider only an individual factor. In this study, an estimation method for RSL of concrete buildings is presented by utilizing a fuzzy theory to consider the effects of multiple influencing factors on the deterioration of durability (e.g., concrete carbonation, chloride attack, sulfate attack), as well as the current structural condition (or damage level) of buildings.

Keywords

Acknowledgement

Supported by : National Research Foundation of Korea (NRF)

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