Bridge Life Cycle Cost Analysis (BLCCA) has received a great deal of attention, especially in the last decade. Currently, there is no consensus on the required level of detail in performing a BLCCA concerning the number of elements that should be studied to attain a certain level of accuracy. However, some analysts, as mentioned in NCHRP-483 report, suggest that considering three elements (substructure, deck, and superstructure) yields an adequately detailed description of most highway bridges. The majority of previous studies, however, focused more on developing algorithms for one individual element of the bridge or the bridge itself as one element, rather than all the components as a system. Such a system approach would make the empirical results more realistic. Thus, this paper's main objective is to develop a comprehensive BLCCA methodology using real data available in the National Bridge Inventory. Here, this inventory is primarily used for modeling the deterioration behavior of the bridge. The methodology predicts the agency and user costs using Genetic Algorithm for cost optimization, and Markov-Chain approach for deterioration modeling. Monte-Carlo Simulation is used for dealing with uncertainties. The BLCCA algorithm developed here can be a valuable tool for allocating limited public resources efficiently and maintaining all parts of the bridges functioning at acceptable levels. To validate the effectiveness of the suggested algorithm, results from a hypothetical case study are presented, which verify that the proposed methodology can be successfully applied to steel and concrete superstructure bridges that constitute the majority of bridges.
Abstract