Improving the Estimation of Markov Transition Probabilities Using Mechanistic-Empirical Models

Frontiers in Built Environment

Kaito, Kiyoyuki¹  Adey, Bryan T.²  Mizutani, Daijiro³  Lethanh, Nam⁴ 

[1] Department of Civil Engineering, Osaka University, Japan;Institute of Construction and Infrastructure Management, ETH Zurich, Switzerland;International Research Institute of Disaster Science, Tohoku University, Japan;POMPLUS Consulting Ltd., Vietnam

关键词: mechanistic-empirical corrosion models;    Markov chain models;    reinforced concrete bridges;    bayesian statistics;    Bridge management;   

DOI  :  10.3389/fbuil.2017.00058

学科分类：建筑学

来源: Frontiers

【 摘 要 】

In many current state-of-the-art bridge management systems, Markov models are used for both the prediction of deterioration and the determination of optimal intervention strategies. Although transition probabilities of Markov models are generally estimated using inspection data, it is not uncommon that there are situations where there is inadequate data available to estimate the transition probabilities. In this paper, a methodology is proposed to estimate the transition probabilities from mechanistic-empirical models for reinforced concrete elements. The proposed methodology includes the estimation of the transition probabilities analytically when possible and when not through the use of Bayesian statistics, which requires the formulation of a likelihood function and the use of Markov Chain Monte Carlo simulations. In an example the difference between the average condition predicted over a 100 year time period with a Markov model developed using the proposed methodology and the condition predicted using mechanistic-empirical models were found to be 54% of that when the state-of-the-art methodology, i.e. a methodology that estimates the transition probabilities using best fit curves based on yearly condition distributions, was used. The variation in accuracy of the Markov model as a function of the number of deterioration paths generated using the mechanistic-empirical models is also shown.

【 授权许可】

CC BY