Abstract

Managing the existing bridge infrastructure has become a major social and economic concern in North America. This is due to the critical conditions of the deteriorated bridges and the limited funds available to repair their deficiencies. Most transportation agencies make bridge investment decisions based on a combination of some form of quantitative data analysis and the subjective judgments of decision and policy makers. The subjective nature of the decision making process easily raises questions about whether the investment decisions are being developed in a fair, equitable and systematic manner. This dissertation presents a decision support methodology developed for the rehabilitation management of concrete bridges in general, and for bridge decks in particular. A probabilistic bridge condition assessment method is developed. This method is consistent with the current practice in bridge inspection and the Markovian approach to model deterioration. A means to rank bridge projects is presented, which makes use of a hierarchy structure to represent the problem and rank the different bridge projects using the Multi Attribute Utility Theory (MAUT). A method to evaluate the available rehabilitation strategies is discussed. This method uses a modified Analytic Hierarchy Process (AHP) and the Monte Carlo simulation technique to evaluate the weights for the different rehabilitation strategies available for each project. A decision making technique to select a recommended work program that maximizes benefits to the network and to the users is developed. The developed methodology has the potential to be extended to other bridge components and to be the foundation for a comprehensive bridge management system. The significant features of this methodology can be summarized as follows: (1) It is consistent with the current practice in bridge management condition assessment and deterioration modeling. (2) It employs a multiple-criteria decision making process; (3) it has the flexibility to allow engineers to utilize their experience and judgment in the decision making process; and (4) It combines the network and the project levels of the bridge management process and performs effectively within a limited budget.