The investigation of methods to assist decision-makers regarding bridge maintenance, rehabilitation, and restoration activities

The ability to predict the deterioration pattern of bridges can assist decision makers in determining when and whether to ignore, refurbish/rehabilitate, or replace a bridge. This dissertation formulates and applies two models, one deterministic and the other probabilistic, capable of predicting future condition ratings of the three main components of a bridge; wearing surface, superstructure, and substructure. The contribution to bridge deterioration by environment factors including freeze-thaw cycles, de-icing salts, and vehicular traffic, are also examined through analysis and comparison of deterioration of selected bridges from two contrasting regions in the Province of Ontario.A deterministic approach to formulating a failure prediction model incorporates a Family of Curves. This approach utilizes a least squares model to fit non-linear polynomial curves to historical bridge inspection data. A probabilistic approach to formulating a failure prediction model incorporates a Markovian Process which provides information on the probability of moving from one condition state (or rating) to another given the present condition state. Both of these models generate curves depicting deterioration patterns for the three main components of a bridge.Perhaps the most notable contribution of this work is the development of a method for generating failure prediction curves based on age of "original & renewed component." This approach excludes the effects of major repairs and provides the most realistic representation of bridge component deterioration. Success in testing the predictive ability of this approach on sampled bridges demonstrates the value to decision makers of the model developed in this research.U of I OnlyETDs are only available to UIUC Users without author permissio