Bayesian updating of infrastructure deterioration models

Yun Lu, Samer Madanat

    Research output: Contribution to journalArticle

    Abstract

    Deterioration forecasting plays an important role in the infrastructure management process. The precision of facility condition forecasting directly influences the quality of maintenance and rehabilitation decision making. One way to improve the precision of forecasting is by successive updating of deterioration model parameters. A Bayesian approach that uses inspection data for updating facility deterioration models is presented. As an empirical study with bridge deck data indicates, the use of this methodology significantly reduces the uncertainty inherent in condition forecasts.

    Original languageEnglish (US)
    Pages (from-to)110-114
    Number of pages5
    JournalTransportation Research Record
    Issue number1442
    StatePublished - Oct 1 1994

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    Deterioration
    Bridge decks
    Patient rehabilitation
    Inspection
    Decision making
    Uncertainty

    ASJC Scopus subject areas

    • Civil and Structural Engineering

    Cite this

    Bayesian updating of infrastructure deterioration models. / Lu, Yun; Madanat, Samer.

    In: Transportation Research Record, No. 1442, 01.10.1994, p. 110-114.

    Research output: Contribution to journalArticle

    Lu, Yun ; Madanat, Samer. / Bayesian updating of infrastructure deterioration models. In: Transportation Research Record. 1994 ; No. 1442. pp. 110-114.
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