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Methodology of homogeneous and non-homogeneous Markov Chains for modeling bridge element deterioration.
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    Final report.
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    Bridge management is an important activity of transportation agencies in the US and in many other countries. A critical aspect of bridge management is to reliably predict the deterioration of bridge structures, so that appropriate or optimal actions can be selected to reduce or minimize the deterioration rate and maximize the effect of spending for replacement or maintenance, repair, and rehabilitation (MR&R). In the US, Pontis is the most popular bridge management system used among the state transportation agencies. Its deterioration model uses the Markov Chain, with a statistical regression to estimate the required transition probabilities. This is the core part of deterioration prediction in Pontis. This report focuses on the Markov Chain model used in Pontis, which is vital to the understanding and implementation of the Pontis software. Emphasis has been made on the limitations of Pontis methodology, and establishing a new method for transition probability estimation. This is because predicting deterioration is the basis for decisionmaking with respect to MR&R. The next portion of this chapter presents a literature review on the subject of estimating transition probability matrix using Markov Chain for modeling deterioration in civil engineering facilities, such as bridges, pavements, and waste water systems.
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