Contemporary challenges in relation to design and assessment of concrete structures relate to the quantification of the influence of ageing phenomena and (changing) environmental circumstances in relation to life-cycle assessment and resilience in case of unforeseen events. Considering the strive towards more sustainable management strategies of structures, an adequate assessment of the time-dependent performance of the structures under actual (and changing) environmental conditions is of crucial importance in order to guarantee or extend the lifetime of concrete structures. Moreover, the resilience of structures becomes a crucial factor in relation to infrastructure management considering the enormous economic and environmental consequences that are associated with the unavailability or failure of these elements in the network. However, the performance prediction in relation to these aspects is far from trivial due to the complexity of the degradation phenomena in concrete structures, which are typically associated with significant uncertainties. Moreover the random nature of environmental influences and the influence of climate change, both also subjected to significant uncertainties, complicate the structural safety and resilience assessment. Bayesian updating techniques enable to incorporate additional information from inspection, testing and monitoring and enable to reduce the associated uncertainties. There is however a lack of a consistent treatment of this problem in the state-of-the-art literature in the research field and the project focuses on developing solutions for the formulated problem.