Deterioration Prediction of Urban Bridges on Network Level Using Markov-Chain Model

Bridges play an important role in urban transportation network. However, it is hard to predict the bridge deterioration precisely in Shanghai, because records of various bridge types with different maintenance status coexist in the same database and the bridge age span is also large. Therefore a Markov-chain model capable of considering maintenance factors is proposed in this study. Three deterioration circumstances are modeled including natural decay, conventional recoverable decay, and enhanced recoverable decay. Three components as well as the whole bridge are predicted including bridge deck system, superstructure, and substructure. The Markov-chain model proposed can predict not only the distribution of the percentage of different condition rating (CR) grades on network level in any year but also the deterioration tendency of single bridge with any state. Bridge data records of ten years were used to verify the model and also to find the deterioration tendency of urban bridges in Shanghai. The results show that the bridge conditions would drop rapidly if no recoverable repair treatments were conducted. Proper repair could slow down the deterioration speed. The enhanced recoverable repair could significantly mitigate the deterioration process and even raise the CR grades after several years of maintenance and repair.