Statistical deterioration prediction model considering the heterogeneity in deterioration rates by hierarchical Bayesian estimation

Daijiro Mizutani, Kodai Matsuoka, Kiyoyuki Kaito

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

A variety of uncertainty affects the deterioration processes of infrastructure. Deterioration rates vary significantly according to the differences in the structural characteristics, use, and environmental conditions of infrastructure. In order to overcome the problem of overdispersion of deterioration rates caused by the heterogeneity of structures, the mixed Markov deterioration hazard model has been proposed considering the heterogeneity of deterioration rates among groups of infrastructures. In this study, it is assumed that the overdispersion of deterioration rates depend on the heterogeneity. Then, the mixed Markov deterioration hazard model that takes into account hierarchical heterogeneity is formulated, and a hierarchical Bayesian estimation method is proposed. Lastly, the validity of the proposed method is discussed through the empirical analysis of the visual inspection data of 823 reinforced concrete (RC) slabs of 151 bridges. The expected lifespan of all 823 RC slabs is about 26,9 years and the expected lifespan of the RC slabs varies from 6,2 to 72,5 years due to the heterogeneity of each RC slab. Finally, the expected deterioration processes of all 823 RC slabs considering the heterogeneity of deterioration rates are shown.

Original languageEnglish
Pages (from-to)394-401
Number of pages8
JournalStructural Engineering International: Journal of the International Association for Bridge and Structural Engineering (IABSE)
Volume23
Issue number4
DOIs
Publication statusPublished - 2013 Nov
Externally publishedYes

Keywords

  • Heterogeneity
  • Hierarchical Bayesian estimation
  • Mixed Markov hazard model
  • Statistical deterioration prediction
  • Visual inspection data

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Building and Construction

Fingerprint Dive into the research topics of 'Statistical deterioration prediction model considering the heterogeneity in deterioration rates by hierarchical Bayesian estimation'. Together they form a unique fingerprint.

Cite this