Deterioration Prediction of Timber Bridge Elements Using the Markov Chain

Abstract

AbstractTimber bridges require high accumulated maintenance costs, which can be many times greater than their initial cost. Infrastructure managers need deterioration models to assist with making appropriate decisions concerning repair strategies and program maintenance schedules by accurately predicting the future condition of timber bridge elements. Markov chain–based models have been used extensively in modeling the deterioration of infrastructure facilities. These models can predict the condition of bridge elements as a probabilistic estimate. This paper presents the prediction of future condition of timber bridge elements using a stochastic Markov chain model. Condition data obtained from the Roads Corporation of Victoria, Australia, were used to develop transition probabilities. The percentage prediction method, regression-based optimization method, and nonlinear optimization technique were applied to predict transition matrices and transient probabilities from the condition data. The most suitable ...