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International audienceCarbonation is a widespread degradation of concrete and may be coupled with more severe degradations. In order to change from prescriptive requirements to performance based specifications for durability, through the equivalent performance concept, it is necessary to find relevant performance tests and indicators. Concrete mixtures of the reported study were designed complying with required binder contents and water–cement ratios to investigate the effects of binder composition, aggregate type and curing conditions. Early drying severely affected performances, as well as cement replacement by low-calcium fly ash. Aggregates had indirect effects on actual water content and curing. Porosity, gas permeability and chloride diffusivity were found as unreliable indicators for carbonation, since they only characterise compactness of concrete. An accelerated carbonation test is proposed as a performance test, as it is sensitive enough and results were consistent with natural carbonation in the studied exposure conditions. Another indicator, based on chloride diffusivity/initial CaO content ratio, could provide useful data for given aggregate mixes and curing conditions, as it takes into account compactness of concrete and chemical reactivity of binder

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One of the main objectives of the APPLET project was to quantify the variability of concrete properties to allow for a probabilistic performance-based approach regarding the service lifetime prediction of concrete structures. The characterization of concrete variability was the subject of an experimental program which included a significant number of tests allowing the characterization of durability indicators or performance tests. Two construction sites were selected from which concrete specimens were periodically taken and tested by the different project partners. The obtained results (mechanical behavior, chloride migration, accelerated carbonation, gas permeability, desorption isotherms, porosity) are discussed and a statistical analysis was performed to characterize these results through appropriate probability density functions

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