Network Level Deterioration Modelling: A case study on masonry arch bridges

M. Imran Rafiq, Saenthan Sathananthan

    Research output: Chapter in Book/Conference proceeding with ISSN or ISBNConference contribution with ISSN or ISBNpeer-review


    The development of a methodology to model network level bridge deterioration using a Bayesian Belief Network (BBN) is presented in this paper. BBN’s are capable of handling complex relationships between elements (e.g. beams, columns, etc.) and the system (e.g. stock of bridges) by means of conditional
    probabilities specified on a fixed model structure. The advantages and limitations of BBN’s for such applications are discussed. The application of the methodology is presented through a case study on a group of UK railway masonry arch bridges. The condition of elements within a selected sample of bridges is used as input in the BBN, together with a set of conditional probabilities based on inspection experience, to yield, in probabilistic terms, the overall condition of the bridge group. Sensitivity of various input parameters, as well as underlying assumptions, on group performance is investigated, which can help with the prioritization of assessment and maintenance intervention activities.
    Original languageEnglish
    Title of host publicationBridge Maintenance, Safety, Management and Life-Cycle Optimization
    Subtitle of host publicationProceedings of the Fifth International IABMAS Conference, Philadelphia, USA, 11-15
    EditorsRichard Sause, Dam M. Frangopol, Chad Kusko
    Place of PublicationPhiladelphia, USA
    PublisherCRC Press
    Number of pages8
    Publication statusPublished - 7 Jul 2010


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