Aspects of modelling uncertainty in predicting chloride induced deterioration for concrete bridges

Abstract

Use of probabilistic performance models to estimate and predict the extent of deterioration in concrete structures is on the increase. Uncertainties associated with their input parameters have a strong influence on the effectiveness of these models. A method has been developed by the authors that uses information obtained through continuously monitoring the progress of deterioration to reduce the uncertainties associated with these models. This paper summarises the effects of various modelling uncertainties on the prior and posterior predicted performance. The effects of modelling uncertainties associated with health monitoring systems (ie instrument & measurement uncertainties) are also investigated for the posterior predicted performance.