Particle filter for model updating and reliability estimation of existing structures

Ikumasa Yoshida*, Mitsuyoshi Akiyama

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)


It is essential to update the model with reflecting observation or inspection data for reliability estimation of existing structures. Authors proposed updated reliability analysis by using Particle Filter. We discuss how to apply the proposed method through numerical examples on reinforced concrete structures after verification of the method with hypothetical linear Gaussian problem. Reinforced concrete structures in a marine environment deteriorate with time due to chloride-induced corrosion of reinforcing bars. In the case of existing structures, it is essential to monitor the current condition such as chloride-induced corrosion and to reflect it to rational maintenance with consideration of the uncertainty. In this context, updated reliability estimation of a structure provides useful information for the rational decision. Accuracy estimation is also one of the important issues when Monte Carlo approach such as Particle Filter is adopted. Especially Particle Filter approach has a problem known as degeneracy. Effective sample size is introduced to predict the covariance of variance of limit state exceeding probabilities calculated by Particle Filter. Its validity is shown by the numerical experiments.

Original languageEnglish
Pages (from-to)103-122
Number of pages20
JournalSmart Structures and Systems
Issue number1
Publication statusPublished - 2013 Jan


  • Bayesian
  • Conditional reliability
  • Failure probability
  • Particle Filter
  • Update

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering


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