Efficient Algorithms and Models for Bayesian Updating in Structural Reliabilty

Abstract eng:
Bayesian updating enables one to consistently combine models with observations. In the context of structural reliability, it enables computing the conditional probability of system failure given measurement or monitoring results. Despite the huge potential for such updating, e.g. in geotechnical engineering or in the management of deteriorating structures, the method has seen limited applications in engineering practice. To a large extent, this was due to limitations of computational algorithms for performing Bayesian updating in the context of structural reliability, which have now been partly overcome by recent developments. This paper introduces the general concept of Bayesian updating in structural reliability and then summarizes a novel method that strongly enhances the versatility and efficiency of algorithms for computing the reliability conditional on observations. The method is illustrated by two examples.

• Export as: BibTeX | MARC | MARCXML | DC | EndNote | NLM | RefWorks
• Add to your basket