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Smart Structures and Systems
  Volume 11, Number 1, January 2013, pages 103-122

Particle filter for model updating and reliability estimation of existing structures
Ikumasa Yoshida and Mitsuyoshi Akiyama

    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.
Key Words
    conditional reliability; update; failure probability; Particle Filter ;Bayesian
Ikumasa Yoshida : Department of Civil Engineering, Tokyo City University, Tokyo, 158-8557, Japan
Mitsuyoshi Akiyama : Department of Civil Engineering, Waseda University, Sendai, 980-8579, Japan

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