The authors present a pavement management framework that employs mechanistic performance submodels to predict pavement behavior. The performance submodels predict the development of pavement distresses in relation to traffic loading and pavement structure. This technique allows the effectiveness of pavement rehabilitation strategies to be evaluated in terms of individual distress modes. It also provides a foundation for a dynamic programming optimization scheme, which considers life-cycle costs for budget allocation. The performance submodels are devised within a probabilistic framework to incorporate uncertainty information on the factors governing pavement deterioration. The transition probabilities from one pavement state to another for a set of rehabilitation options are derived using the first-order reliability method (FORM). The methodology allows multiple distress mode condition to be considered using the concept of cut sets. These probabilities act as inputs to the optimization submodel, which determines the optimal rehabilitation alternative in terms of discounted life-cycle costs subjected to management and operational constraints.


  • English

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  • Accession Number: 00716491
  • Record Type: Publication
  • Files: TRIS, ATRI
  • Created Date: Feb 22 1996 12:00AM