Updating life-cycle performance model of bridge based on inspection data

Jin Hyuk Lee, Kyung Hwa Cha, Sang Mi Ahn, Jung Sik Kong

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)


For the bridge maintenance strategy and planning, prediction of future performance based on the current performance must be required and it is possible more rational decision-making through the higher accuracy of the prediction model. While performing a detailed inspection of the entire bridge can reduce a significant part of the uncertainty, it is impossible to reduce the uncertainty of inspection result and it is always evaluated by probability. In this study, to solve this problem, a Bayesian update method is applied to the optimal maintenance strategy in Bridge Management System (BMS) considering the uncertainty of inspection data. Also, examples of application are presented, showing the effects of inspection and updating on the bridge maintenance strategies. In this study, application possibility and availability of domestic bridge management system are evaluated by referring to the proposed method in the existing trends.

Original languageEnglish
Title of host publicationIABSE Conference, Vancouver 2017
Subtitle of host publicationEngineering the Future - Report
PublisherInternational Association for Bridge and Structural Engineering (IABSE)
Number of pages4
ISBN (Electronic)9783857481536
Publication statusPublished - 2017
Event39th IABSE Symposium in Vancouver 2017: Engineering the Future - Vancouver, Canada
Duration: 2017 Sept 212017 Sept 23

Publication series

NameIABSE Conference, Vancouver 2017: Engineering the Future - Report


Other39th IABSE Symposium in Vancouver 2017: Engineering the Future


  • Bayesian
  • Bridge
  • Decision-making
  • Inspection
  • Maintenance
  • Uncertainty
  • Updating

ASJC Scopus subject areas

  • Building and Construction
  • Civil and Structural Engineering


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