Bayesian updated time-dependent chloride-induced corrosion assessment using redundancy factors

In order to assess the structural reliability and redundancy with respect to deterioration, it is required to select appropriate models which describe the deterioration process. The parameters associated with these models have to be estimated through statistical interference, which introduces uncertainties in parameter estimates. As the structural reliability indices which are incorporated in the reliability-based redundancy factor can be considered as random variable, this redundancy factor itself is a random variable as well. In case additional information becomes available, the distribution function can be updated by taking into account this extra information. In this contribution, a framework is developed, which allows for the incorporation of additional information in the uncertain reliability index and the associated redundancy factor through Bayesian updating. It is shown that in case additional information on a main variable is gathered, this has a significant effect on the (mean) value and uncertainty of the reliability index and the associated redundancy factor