An advanced probabilistic updating algorithm for life cycle analysis of civil structures

Abstract

Life cycle analysis (LCA) of civil structures is a framework which helps owners deciding whether or not a specific action is the most suitable in each time instant. This decision will always depend upon the curve risk vs. cost. Risk is the product of the probability of a specific limit state happens per its consequence. This probability will depend from structural resistance which is not constant in time. In order to follow this variation, visual inspections, nondestructive tests and monitoring systems are commonly used. However, a huge gap exists between the moment data is collected and the one in which it is included into the LCA framework. In this paper a methodology that considers the probabilistic updating of resistance curves with acquired data, through a Bayesian inference approach, is presented. The algorithm is then validated with a set of reinforced concrete beams which were loaded up to failure in laboratory.