Uncertainty assessment for the Bayesian updating process of concrete strength properties

Reassessment of infrastructure buildings has become an essential approach to deal with increasing traffic loads on ageing and verify the service-life those structures. Good estimation actual material properties is highly relevant for reliable structural reassessment. Although this holds all building materials, importance good parameter special concrete structures, where strength show relatively high variation nominal tend be too conservative. Modern design guidelines allow make use scientific methods such as Bayesian Updating enable a more realistic consideration in reassessment existing However, application experience are not yet reported much or rather vague [1]. The presented study focuses effect process parameters emphasis number sampling location test specimens well accuracy confidence obtained posterior distribution, since also includes certain margin uncertainty. investigation methodological potential uncertainty updating contribution uses batch 14 results compressive from drill cores along inherent measurement uncertainties testing procedure. After short review Bayes’ Theorem, Markov Chain Monte Carlo Method (MCMC) bootstrap methodology, combinations subsamples size 1, 3 5 were built provided procedure via MCMC determine distributions. series distributions subsample was used by evaluation scatter expected value, standard deviation %-quantile updated distribution. simulations adequate sample quantify arising limited observations.