Bayesian Theory-Based Seismic Failure Modes Identification of Reinforced Concrete Columns

Abstract

The aim of this research is to develop a probability method that can identify the flexure, shear or flexural-shear failure of RC columns. A total of 336 columns of cyclic load test results were collected, and a probabilistic model was constructed using the Bayesian procedure. Then, the model was simplified by Bayesian updating. The boundaries for each failure mode were selected through an internal search optimization. The results show that the Bayesian methodology can accurately predict the seismic failure modes of RC columns and the comparison of the identification with other methods underscore the validity of Bayesian method.

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