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タイトル: A competing Markov model for cracking prediction on civil structures
著者: Kobayashi, K.
Kaito, K.
Lethanh, N.
著者名の別形: 小林, 潔司
キーワード: Bayesian estimation
Markov Chain Monte Carlo
Gibbs sampling
Markov chain model
Infrastructure management
Pavement cracking processes
発行日: Oct-2014
出版者: Elsevier B.V.
誌名: Transportation Research Part B: Methodological
巻: 68
開始ページ: 345
終了ページ: 362
抄録: Cracks on the surface of civil structures (e.g. pavement sections, concrete structures) progress in several formations and under different deterioration mechanisms. In monitoring practice, it is often that cracking type with its worst damage level is selected as a representative condition state, while other cracking types and their damage levels are neglected in records, remaining as hidden information. Therefore, the practice in monitoring has a potential to conceal with a bias selection process, which possibly result in not optimal intervention strategies. In overcoming these problems, our paper presents a non-homogeneous Markov hazard model, with competing hazard rates. Cracking condition states are classified in three types (longitudinal crack, horizontal crack, and alligator crack), with three respective damage levels. The dynamic selection of cracking condition states are undergone a competing process of cracking types and damage levels. We apply a numerical solution using Bayesian estimation and Markov Chain Monte Carlo method to solve the problem of high-order integration of complete likelihood function. An empirical study on a data-set of Japanese pavement system is presented to demonstrate the applicability and contribution of the model.
著作権等: © 2014 Elsevier Ltd.
This is not the published version. Please cite only the published version. この論文は出版社版でありません。引用の際には出版社版をご確認ご利用ください。
URI: http://hdl.handle.net/2433/191023
DOI(出版社版): 10.1016/j.trb.2014.06.012
出現コレクション:学術雑誌掲載論文

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