Hierarchical Bayesian estimation of mixed hazard models

Daijiro Mizutani; Kodai Matsuoka; Kiyoyuki Kaito

doi:10.2749/222137813806481428

Hierarchical Bayesian estimation of mixed hazard models

Daijiro Mizutani, Kodai Matsuoka, Kiyoyuki Kaito

Human and Social Response Research Division

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

A variety of uncertainties affect the deterioration process of infrastructure. Deterioration rate is varying significantly according to the difference in the structural characteristics, use, and environmental conditions of infrastructures. The heterogeneity of structures causes the problem of overdispersion of the deterioration rate. In order to overcome the problem of overdispersion, the mixed Markov deterioration hazard model has been proposed considering the heterogeneity of deterioration rate among groups of infrastructures. In this study, it is assumed that the overdispersion depends on the heterogeneity of the deterioration rate among groups of infrastructures. Then, the mixed Markov deterioration hazard model that takes into account hierarchical heterogeneity is formulated, and a hierarchical Bayesian estimation method is proposed. The appropriateness of the proposed method is discussed through the empirical analysis of the visual inspection data of bridge slabs.

Original language	English
Title of host publication	Assessment, Upgrading and Refurbishment of Infrastructures
Publisher	International Association for Bridge and Structural Engineering (IABSE)
ISBN (Electronic)	9783857481239
DOIs	https://doi.org/10.2749/222137813806481428
Publication status	Published - 2013
Event	IABSE Workshop on Assessment, Upgrading and Refurbishment of Infrastructures - Rotterdam, Netherlands Duration: 2013 May 6 → 2013 May 8

Publication series

Name	Assessment, Upgrading and Refurbishment of Infrastructures

Conference

Conference	IABSE Workshop on Assessment, Upgrading and Refurbishment of Infrastructures
Country	Netherlands
City	Rotterdam
Period	13/5/6 → 13/5/8

Keywords

Heterogeneity
Hierarchical Bayesian estimation
Mixed Markov hazard model

ASJC Scopus subject areas

Civil and Structural Engineering
Building and Construction

Access to Document

10.2749/222137813806481428

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Hierarchical Bayesian estimation of mixed hazard models. / Mizutani, Daijiro; Matsuoka, Kodai; Kaito, Kiyoyuki.

Assessment, Upgrading and Refurbishment of Infrastructures. International Association for Bridge and Structural Engineering (IABSE), 2013. (Assessment, Upgrading and Refurbishment of Infrastructures).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Mizutani, D, Matsuoka, K & Kaito, K 2013, Hierarchical Bayesian estimation of mixed hazard models. in Assessment, Upgrading and Refurbishment of Infrastructures. Assessment, Upgrading and Refurbishment of Infrastructures, International Association for Bridge and Structural Engineering (IABSE), IABSE Workshop on Assessment, Upgrading and Refurbishment of Infrastructures, Rotterdam, Netherlands, 13/5/6. https://doi.org/10.2749/222137813806481428

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AB - A variety of uncertainties affect the deterioration process of infrastructure. Deterioration rate is varying significantly according to the difference in the structural characteristics, use, and environmental conditions of infrastructures. The heterogeneity of structures causes the problem of overdispersion of the deterioration rate. In order to overcome the problem of overdispersion, the mixed Markov deterioration hazard model has been proposed considering the heterogeneity of deterioration rate among groups of infrastructures. In this study, it is assumed that the overdispersion depends on the heterogeneity of the deterioration rate among groups of infrastructures. Then, the mixed Markov deterioration hazard model that takes into account hierarchical heterogeneity is formulated, and a hierarchical Bayesian estimation method is proposed. The appropriateness of the proposed method is discussed through the empirical analysis of the visual inspection data of bridge slabs.

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