Bayesian Nonparametric Modeling of Structural Health Indicators under Severe Typhoons and Its Application to Modeling Modal Frequency

AbstractStructural health indicators, such as modal frequencies, have been commonly utilized to interpret the health condition of monitored structures. This study modeled the relationship between structural health indicators and ambient conditions under severe typhoons. For this purpose, a two-stage...

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Bibliographic Details
Published in:Journal of aerospace engineering 2019-07, Vol.32 (4)
Main Authors: Kuok, Sin-Chi, Yuen, Ka-Veng
Format: Article
Language:English
Subjects:
Bayesian analysis
Concrete construction
Condition monitoring
Cyclones
Health
Indicators
Modelling
Nonparametric statistics
Reinforced concrete
Statistical analysis
Technical Papers
Typhoons
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Summary:AbstractStructural health indicators, such as modal frequencies, have been commonly utilized to interpret the health condition of monitored structures. This study modeled the relationship between structural health indicators and ambient conditions under severe typhoons. For this purpose, a two-stage Bayesian probabilistic procedure was established. In the first stage, the Bayesian spectral density approach (BSDA) is applied to identify the structural health indicators, namely the modal frequencies in this study, using the measured structural response. In the second stage, the Bayesian nonparametric general regression (BNGR) is introduced to model the relationship between the identified structural health indicators and some selected typhoon-induced ambient conditions. By using Bayesian model selection in conjunction with general regression, BNGR is able to select the most appropriate set of influencing/input variables for the prediction of the structural health indicators without prescribing any functional form. Full-scale measurements of a 22-story reinforced concrete (RC) building were used to demonstrate the efficacy of the procedure. The measurements consisted of over 280 h of structural response and the corresponding ambient conditions captured under the five most severe tropical cyclones that affected the region from 2011 to 2013. This study provides a promising framework for reliable interpretation of the variation of structural health indicators. Although the modal frequencies were considered in this study, the proposed two-stage procedure is applicable for other structural health indicators.
ISSN:0893-1321
1943-5525
DOI:10.1061/(ASCE)AS.1943-5525.0001023