Reliability analysis of prestressed concrete bridges located in a marine environment

Mitsuyoshi Akiyama, D. M. Frangopol, I. Yoshida

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

There are many kinds of uncertainties involved in the evaluation of corrosion process and deterioration of structural performance. Because of the presence of uncertainties, it is necessary that long-term structural performance be treated based on reliability concepts and methods. This paper presents a probabilistic framework for estimating the time-dependent reliability for existing prestressed concrete structures in a marine environment based on a non-linear filtering technique denoted Sequential Monte Carlo Simulation (SMCS). The results of manual measurement or automatic monitoring are used as observational information. The emphasis is placed on investigating the effects of the differences between manual measurement and automatic monitoring, and possible interruption periods of health monitoring on updated estimates of reliability of prestressed concrete bridges located in a marine environment.

Original languageEnglish
Title of host publicationApplications of Statistics and Probability in Civil Engineering -Proceedings of the 11th International Conference on Applications of Statistics and Probability in Civil Engineering
Pages573-580
Number of pages8
Publication statusPublished - 2011
Externally publishedYes
Event11th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP - Zurich
Duration: 2011 Aug 12011 Aug 4

Other

Other11th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP
CityZurich
Period11/8/111/8/4

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ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Statistics and Probability

Cite this

Akiyama, M., Frangopol, D. M., & Yoshida, I. (2011). Reliability analysis of prestressed concrete bridges located in a marine environment. In Applications of Statistics and Probability in Civil Engineering -Proceedings of the 11th International Conference on Applications of Statistics and Probability in Civil Engineering (pp. 573-580)