TY - GEN
T1 - Damage initiation and propagation model for bridge members
AU - Ninomiya, Yohei
AU - Mizutani, Daijiro
AU - Kaito, Kiyoyuki
PY - 2016
Y1 - 2016
N2 - In this paper, in order to statistically analysis damage to bridge members and to forecast the initiation and the propagation of damage, a statistical damage initiation and propagation model is proposed. Specifically, the model is a composite model that the initiation process of damage and the propagation process of damage are expressed by different two types of model. When composing such a composite model, it is necessary that the time point of the transition from the initiation process to the propagation process. The time point is certain that the time point of the damage occurrence, however, the damage occurrence is not observed in general inspection works. Therefore, it is also proposed that the estimation method of the time point of damage occurrence, using the temporal discontinuity inspection data to bridges. Lastly, in order to confirm the validity of this study, an empirical analysis is carried out by applying actual inspection data.
AB - In this paper, in order to statistically analysis damage to bridge members and to forecast the initiation and the propagation of damage, a statistical damage initiation and propagation model is proposed. Specifically, the model is a composite model that the initiation process of damage and the propagation process of damage are expressed by different two types of model. When composing such a composite model, it is necessary that the time point of the transition from the initiation process to the propagation process. The time point is certain that the time point of the damage occurrence, however, the damage occurrence is not observed in general inspection works. Therefore, it is also proposed that the estimation method of the time point of damage occurrence, using the temporal discontinuity inspection data to bridges. Lastly, in order to confirm the validity of this study, an empirical analysis is carried out by applying actual inspection data.
KW - Asset management
KW - Bayesian estimation
KW - Big data analytics
KW - Deterioration model
KW - Hazard model
KW - Markov chain Monte Carlo method
KW - Metropolis-Hastings algorithm
KW - Risk assessment
KW - Statistical model
KW - Steel bridges
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UR - http://www.scopus.com/inward/citedby.url?scp=85018955007&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85018955007
T3 - IABSE Congress Stockholm, 2016: Challenges in Design and Construction of an Innovative and Sustainable Built Environment
SP - 1780
EP - 1787
BT - IABSE Congress Stockholm, 2016
PB - International Association for Bridge and Structural Engineering (IABSE)
T2 - 19th IABSE Congress Stockholm 2016: Challenges in Design and Construction of an Innovative and Sustainable Built Environment
Y2 - 21 September 2016 through 23 September 2016
ER -