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Pavement permanent deformations due to lack of shear strength in mixture are a major reason of rutting. Any simple test to determine mixtures resistance to permanent deformation isn’t distinguished in the 1st level of SUPERPAVE mix design method and prevalent methods for evaluating mixture rut resistance are expensive and time-consuming. Two aggregate types, gradations, asphalt cements and filler types were used in this research to present a prediction model for rutting based on flow number. A mathematical model to estimate flow number of dynamic creep test was developed using model parameters and gyratory compaction slope. The model is validated using Neural Network and Genetic Algorithm and makes it possible to evaluate mixtures shear strength while optimum asphalt content is being determined in laboratory. So not only there is no need to expensive test instruments of rutting or dynamic creep but a remarkable time saving in mix design procedure is achievable.

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In this paper, self-consolidating concrete (SCC) mixtures are considered for airfield concrete pavements. A series of rheological, mechanical, transport and frost action durability tests were conducted on the prepared SCC mixtures with and without chemical air entraining agents (AEA). Mineral admixtures including slag, fly ash, silica fume and metakaolin were included in SCC mixtures. The results showed that application of mineral admixture led to significant improvements on the performance of airfield concrete pavement mixtures. Moreover, the performance of mixtures against frost action upgraded when AEA included in companion with the mineral admixtures.