LAUSR

Abstract This paper estimates visual inspection quantitatively prior to its implementation in a Bridge Management System using a Value of Information (VoI) approach employing a Bayesian pre-posterior analysis. Information from a significant number of real bridges from Ireland and Portugal are considered in this regard following existing commercial practices. The variation of different parameters on the estimated VoI is investigated including the assumed probabilistic models of the prior bridge state, the likelihood of inspector assigned condition ratings and the economic setting surrounding the cost matrix for maintenance decision alternatives. The values of no information, perfect information and imperfect information are presented and the change in the optimal strategy based on such information is assessed. The effect of human imperfections in assessment and difference in condition rating scale are also estimated. The studies and findings of this paper are expected to allow a better insight for practising engineers and researchers working in bridge management.