ABSTRACT
EXTENDED ABSTRACT: Deterioration, increase in loading demand and change in utilization have induced an unknown level of risk in the use of transport infrastructure systems. Bridges being a vital element of such systems, due to their very nature as well as their exposure to harsh environmental conditions, should be effectively managed for the benefit of the overall transport network. Predicting the future condition and reliability of the bridges is vitally important in this process. Probabilistic models have been developed to estimate and predict the extent of deterioration in, for example, concrete bridges. However, the input parameters of these models are fraught with uncertainties, thus severely limiting their accuracy, particularly over longer time frames. On the other hand, continuous innovations in the sensing and measurement technology have lead to the development of monitoring instruments that can provide continuous (or almost continuous) data regarding the actual structural performance in the time frame. This information cannot be used directly for the prediction of future performance, first because it typically pertains to a small number of specific locations, and secondly because it needs to be combined with a whole host of other knowledge components. Furthermore, uncertainties in the instruments/measurements and in the future behaviour of the structure and its interaction with the environment (e.g. including the effects of deterioration) also hinder the predictive capability of current modelling tools.
